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--- title: Ethnopharmacological Value and Biological Activities via Antioxidant and Anti-Protein Denaturation Activity of Morinda lucida Benth and Momordica charantia L. Leaves Extracts from Benin authors: - Durand Dah-Nouvlessounon - Michaelle Chokki - Agossou Damien Pacôme Noumavo - Geta Cârâc - Bianca Furdui - Haziz Sina - Cheikna Zongo - Aly Savadogo - Lamine Baba-Moussa - Rodica-Mihaela Dinica - Farid Baba-Moussa journal: Plants year: 2023 pmcid: PMC10058355 doi: 10.3390/plants12061228 license: CC BY 4.0 --- # Ethnopharmacological Value and Biological Activities via Antioxidant and Anti-Protein Denaturation Activity of Morinda lucida Benth and Momordica charantia L. Leaves Extracts from Benin ## Abstract Momordica charantia Linn. ( Cucurbitaceae), the wild variety of bitter melon, and Morinda lucida Benth (Rubiaceae) were commonly used as a popular folk medicine in Benin. This study aimed to appreciate the ethnopharmacological knowledge and evaluate the antioxidant and anti-inflammatory effects of M. charantia and M. lucida leaves extracts. Semi-structured surveys supported by individual interviews were conducted with herbalists and traditional healers in southern Benin. The antioxidant activities were evaluated by a micro-dilution technique using ABTS and FRAP methods. These activities were supported by cyclic voltammetry analysis. The anti-inflammatory activity was evaluated by the albumin denaturation method. The volatile compounds were analysed by GC-MS analysis. All the respondents involved in this study have good knowledge of the two plants. We identify 21 diseases grouped into five categories of condition. The two plants’ extracts possess variable antioxidant capacity. Indeed, all the active extracts of M. charantia presented an IC50 < 0.078 mg/mL, while the extracts of M. lucida had an IC50 up to 0.21 ± 0.02 mg/mL. For anti-inflammatory activity, a dose-response activity ($p \leq 0.001$) was observed in the protein denaturation inhibition rate of the extracts. It should be noted that the highest inhibition rate (98.34 ± 0.12) of the albumin denaturation was observed with M. lucida dichloromethane extract. A total of 59 volatile compounds were identified by GC-MS analysis in the extracts of the two plants. The M. charantia ethyl acetate extract shows the presence of 30 different compounds with a relative abundance of $98.83\%$, while that of M. lucida shows 24 compounds with a relative abundance of $98.30\%$. These plants are potential candidates to discover new compounds with therapeutic properties that could be used to solve public health problems. ## 1. Introduction Africa is composed of several hundred different ethnic and linguistic groups who coexist in a highly diversified tropical environment. These different ethnic groups have very important knowledge used for their survival and to meet their health needs. Indigenous knowledge related to medicinal plants is a foundation of primary health care for treatment of several human and animal diseases among local communities, especially in developing countries [1,2]. However, nowadays, natural resources are considered very important, but they are insufficiently known. The vegetation is distributed in innumerable ecosystems; that of the humid forest and coastal regions has an impressive atmosphere and exuberance due to an extremely rich flora. Nearly 50,000 species of plants have been counted in Africa out of the 250,000 species existing throughout the world. Evidence indicates that up to $80\%$ of the population in developing countries use herbal medicines as the primary form of healthcare [3]. This could also justify the fact that in Africa, people have always traditionally had very rich knowledge thanks to the cultural and ecological diversity of the environment in which they live [4]. This knowledge is usually the sum of daily experiences and the knowledge of ethnic groups that forms the basis for decision-making in the face of health and livelihood issues. Thus, in several countries of the continent, plants constitute the main medicinal means for practical care in public health. In Benin in particular, the flora abounds in a diversity of plants used for food, crafts, cultural and medicinal purposes [5]. Among the species listed are Momordica charantia from the Cucurbitaceae family, and Morinda lucida from the Rubiaceae family. In Benin, both plants are used for the treatment of diabetes. Our previous work has proven the effectiveness of these two plants in the treatment of diabetes [6]. Other authors have also proven the use and therapeutic virtues of these two plants [7,8,9,10,11,12,13]. Inflammation is considered an important etiological factor in the development of both types 1 and 2 diabetes mellitus [14,15]. An excessive increase in reactive oxygen species (ROS) or reactive nitrogen species (RNS) accompanied by a decrease in antioxidants induces oxidative stress, which can lead to endothelial dysfunction, insulin resistance and alterations in the number of reactive oxygen species and function of pancreatic beta cells [16]. Therefore, phytochemicals with hypoglycemic, anti-inflammatory and antioxidant activities are suited for the treatment of diabetes [17]. This study aimed to improve the level of scientific knowledge on these species through an ethnopharmacological survey, and to elucidate the biological activity through the determination of the chemical composition of the two plants extracts with gas chromatography-mass spectrometry (GC-MS). Diverse biological activities, including anti-inflammatory and antioxidant activities, were evaluated. The effect of the reversibility of the antioxidant activity was evaluated by electrochemistry using cyclic voltammetry. ## 2.1.1. Socio-Cultural Characteristics of Respondents The ethnopharmacological surveys were carried out with 137 herbalists and traditional healers, including $20.44\%$ men and $79.56\%$ women. The age of the respondents varied between 18 and 65 years old. Respondents whose age was between 25 and 50 represent the vast majority, i.e., $52\%$ of respondents. The respondents were divided into five ethnic groups of which the “ouémè” ethnic group is the majority ($31.38\%$) and the “sèto” ethnic group is the minority ethnic group ($8.75\%$). ## 2.1.2. Knowledge of Plant Material All the respondents involved in this study have good knowledge of the two plants (Momordica charantia and Morinda lucida). The recognition criteria are essentially based on botanical characteristics, such as the appearance and shape of the plants, leaves and fruits. Indeed, the main recognition criterion is that M. charantia is a liana, while M. lucida is a plant that can reach 12m in height with large leaves. Both species are common in the study area, but there is a period of abundance (the rainy season) for M. charantia. On the other hand, M. lucida is available during both seasons of the year. Both species are found in their natural habitat, as well as on farms and in gardens. ## 2.1.3. Ethnopharmacological Data Related to the Use of the Two Species The two study plants are used in the treatment of human and animal diseases. Indeed, from the surveys, we identify 21 diseases grouped into five categories of conditions (digestive system diseases, microbial and parasitic diseases, gynaecological diseases, blood-related diseases and others). Some diseases are common to both plants species, while others are specific to each species. Among the common diseases treated, we have: malaria, microbial and parasitic infections, diabetes, inflammation, hypertension and strengthening of immunity. Table 1 presents the frequency of the diseases treated with M. charantia and M. lucida. For M. charantia, the most treated disease is measles ($100\%$), followed by dermatological problems with wounds included ($98.54\%$) and diabetes ($71.53\%$). For M. lucida, malaria is the most cited disease ($93.43\%$), followed by abdominal pain ($74.45\%$) and diabetes ($56.93\%$). In addition, different organs of the two plants are used either alone or in association with other plants. Indeed, the use proportions of each organ of the same plant in the formulation vary according to the plant and the diseases treated. For M. lucida, the leaves are the most used organs, followed by leaf + root mixtures. For M. charantia, only the leaves or the whole plant are used (Figure 1). As we mentioned above, the two species of plant are used in the composition of recipes for the treatment of certain diseases. Information concerning the type of recipe, the solvent used, the parts of the plant used, the method of preparation and the dosage are grouped in Table 2 and Table 3. ## 2.2.1. ABTS Method Table 4 presents the results of the antioxidant activity with the ABTS method. M. charantia and M. lucida extracts possess variable antioxidant capacity for ABTS inhibition. The highest percentage inhibition for the active extracts of M. charantia (50.52 ± $1.20\%$) was obtained with the acetone extract, while the lowest (3.86 ± $0.11\%$) was obtained with the methanolic extract. For M. lucida, the greatest percentage inhibition (48.27 ± $1.54\%$) was obtained with the ethanolic extract, while the lowest percentage inhibition (4.63 ± $1.41\%$) was obtained with the acetone extract. Methanol/HCl-PE: Methanol/HCl extract from the extraction of the residue obtained after extraction with petroleum ether. Methanol-EA: Methanol extract from the extraction of the residue obtained after extraction with Ethyl Acetate. ## 2.2.2. Ferric Reducing Antioxidant Power (FRAP) Table 5 presents the reducing power of Fe3+ ions by M. charantia and M. lucida extracts. Regarding ferric reducing antioxidant power, the obtained results indicate that higher sample concentrations (5 mg/mL) cause a greater value of inhibition percentage of the active extracts. For M. charantia, the highest inhibition value (60.75 ± $1.07\%$) was obtained with an ethanol–water extract, while with M. lucida, the methanol extract shows the highest value (60.24 ± $0.56\%$) of inhibition (Table 5). In comparison of the activity of the two plants, the same trend was observed with the IC50. Indeed, all the active extracts of M. charantia presented an IC50 < 0.078 mg/mL, while the extracts of M. lucida had an IC50 up to 0.21 ± 0.02 mg/mL. However, the comparison of the effect of the extracts shows that only the ethanol–water extract of M. charantia (60.75 ± $1.07\%$) is higher ($$p \leq 0.014$$) than that of M. lucida (58.23 ± $1.26\%$). ## 2.3. Cyclic Voltammetry Analysis of M. charantia and M. lucida Extracts The antioxidant activity potential of the plants’ leaf extracts in methanol using cyclic voltammetry technique has been investigated. Initial, the open circuit potential (OCP), which measures the equilibrium potential at the electrode surface, was registered (Figure 2) and can be used to quantify a samples’ redox potential, which is a function of its composition. The lower positive potentials for the M. charantia samples were from 0.074 ± 0.002 V, which increase up to 0.092 ± 0.003 V after 30 min. Compared with M. charantia, for the M. lucida samples, the potential started from 0.093 ± 0.003 V and increased up to 0.113 ± 0.008 V. These data indicate the overall redox potential of both plant extracts in methanol without any significant difference. Both systems were further investigated using the cyclic voltammetry (CV) technique at variable scan rates, between 0.01–0.2 V·s−1. The cyclic voltammograms registered for M. charantia and M. lucida in methanol are presented in Figure 3 at the scan rate of 0.01 V·s−1 and the scan rate of 0.2 V·s−1. The observed behaviour of the samples shows the electro-lower-inactivity of the methanol extracts in the selected potential range from −0.50 V to +0.35 V. The antioxidant capacity of the extract is highlighted by its redox profile from CV. There was an increase of the oxidation peak current with increasing scan rate. The increase in the anodic current is attributed to the presence of some active components (antioxidants) in the extracts. The additions of 1 mL plant extract were made volumetrically as the concentration of the compounds of extracts was not possible to be calculated. In the M. lucida sample, the anodic current is 1.63 μA at the scan rate of 0.200 V·s−1, and depending on the scan rate applied in general, it increases. In the M. charantia sample, the anodic current is 1.86 μA at the scan rate of 0.200 V·s−1. A linear relationship was obtained between the cathodic peak current and the square root of the scan rate, suggesting a diffusion-controlled electrode process for oxygen reduction in methanol. Both anodic areas of the cyclic voltammograms show the total content of the antioxidant compounds, allowing discrimination between the different extracts. We can conclude that the extracts undergo an irreversible oxidation in the same conditions, for the anodic peak, with the current increasing with different values (13.3 μA for M. charantia and 3.08 μA for M. lucida). However, of more interest is the cathodic current registered for the samples, when the values are bigger than the anodic current up to -10 μA, and lower at a smaller scan rate. Reduction peaks were observed at all scan rates and shifted to a more negative value as the scan rate decreased in both plants’ systems. These dates confirm that all reduction compounds are active species working for redox exchange and the resulting oxidants could be active again for new electronic activity. The CV technique can also be helpful to determine the mechanism of free radical scavenging activity because of their potential use in traditional medicine. The results are consistent with the spectroscopic results, which emphasize that plant extracts have no different antioxidant compounds (Figure 4). ## 2.4. Anti-Inflammatory Activity of M. charantia and M. lucida Extracts The results of protein denaturation inhibition are shown in Table 6. The protein denaturation inhibition rate of the extracts at different concentrations increases with increasing extract concentration. A dose-response activity is therefore observed. For M. charantia, the inhibition rates vary from 93.09 ± $1.17\%$ (aqueous extract) to 99.53 ± $0.08\%$ (methanolic extract). Although the methanolic extract presented the highest percentage of inhibition, it was the dichloromethane extract that presented the lowest IC50 (0.10 ± 0.02 mg/mL), thus showing the strongest ability to inhibit albumin denaturation. Contrary to the observation made with M. charantia, it is the aqueous extract of M. lucida that presented the lowest IC50 (0.11 ± 0.01 mg/mL), thus showing the strongest activity of the extracts of M. lucida. However, it should be noted that the highest inhibition rate (98.34 ± 0.12) of the albumin denaturation was observed with the dichloromethane extract. The interaction between the extracts and the plants is variable ($p \leq 0.001$). The compared effect of M. charantia extracts shows a difference between the inhibition rate of the aqueous extract with the ethanol, methanol, dichloromethane ($p \leq 0.001$), ethyl acetate and acetone ($$p \leq 0.033$$) extracts. A variation in the inhibition rate was also observed with the M. lucida extracts, with the lowest variation between the ethyl acetate and chloroform extract ($p \leq 0.05$). ## 2.5. Gas Chromatography Coupled with Mass Spectrometry (GC-MS) GC-MS was performed on the ethyl acetate and acetone extracts of each plant species (M. charantia M. lucida). The results show that the quality and the quantity of the volatile compounds vary according to the extracts and the plants (Table 7). A total of 59 volatile compounds were identified and quantified in the extracts of the two plants. For M. charantia, the GC-MS analysis of the ethyl acetate extract shows the presence of 30 different compounds with a relative abundance of $98.83\%$. The main compounds in this extract are: 2,6-Bis (1,1-dimethylethyl)-4-(1-oxopropyl)phenol ($27.03\%$), followed by Ethyl iso-allocholate ($14.33\%$), 3,9,14,15-Diepoxypregn-16-en-20-one, 3,11,18-triacetoxy ($11.26\%$) and Benzothiophene-2-carboxylic acid, 4,5,6,7- tetrahydro-7-hydroximino-3-[2-(4-morpholyl)-1-oxoethylamino]-, ethyl ester ($10.54\%$), which have at least a relative abundance of $10\%$. The GC-MS analysis of the acetone extract shows the presence of 23 different compounds with a relative abundance of $99.03\%$. For M. lucida, the GC-MS analysis of the ethyl acetate extract shows the presence of 24 different compounds with a relative abundance of $98.30\%$. On the other hand, that of the acetone extract reveals the presence of 25 volatile compounds with a total relative abundance of $96.49\%$. The most abundant compounds in this extract are: N,N’-Bis(Carbobenzyloxy)-lysine methyl (ester) with an abundance of $22.84\%$, followed by 17-Hydroxy-3,20-dioxopregna-1,4, 9[11]-trien-21-yl acetate ($20.02\%$) and 6β-Hydroxyfluoxymesterone ($14.31\%$). ## 3. Discussion The ethnopharmacological studies carried out made it possible to enroll a total of 137 herbalists and traditional healers, including $20.44\%$ men and $79.56\%$ women. All of the herbalists are women, and $100\%$ of traditional healers are men. This could be explained by the fact that in Benin, selling in public markets is much more an activity reserved for women. The main respondents are therefore women from rural areas and are mostly illiterate. Indeed, according to several authors, rural populations, mostly illiterate, possess medicinal knowledge of plants [18,19]. Rehman et al. [ 18] reported that in tribal communities in Pakistan, traditional healers possess a lot of information about medicinal plants. In these regions, medicinal plants are important for the indigenous people, providing access to basic healthcare [20]. In our study, this illiterate nature of the respondents is also observed by other authors [21] who affirm that the use of medicinal plants remains the main means of treatment for people of a certain social class. The age of the respondents varied between 18 and 65 years old. However, respondents whose age was between 25 and 50 represent the vast majority, i.e., $52\%$ of respondents. It is especially accepted in Africa that they are the wise men, the people of a certain age, who hold the traditional knowledge of treating illnesses. In addition, the medicinal virtues of plants are ancestral knowledge that is transmitted from generation to generation [22]. This is justified by the proportion of $64.23\%$ of respondents who have experience of between 16 and 30 years in the field of medicinal plant exploitation. This seniority in the field of the exploitation of medicinal plants confirms the richness of the information collected with consensus factors very close to the value 1. A consensus factor close to this value shows the degree of homogeneity and accuracy of the information [23]. Both plant species are used in the treatment of several diseases, such as diabetes, cancer, infectious diseases (microbial and viral infection) and inflammatory diseases, to treat chronic wounds and to strengthen immunity. Some authors in other countries in Asia [24], America [25] and the West African sub-region [26,27,28] had already reported the efficacy of these two species in the treatment of these diseases. Lakouéténé et al. [ 29] reported that a species can be used for one or more pathologies. It is evident through the results of this ethnopharmacological study that the two plants are used by the study population to effectively treat several pathologies. In this context, research must accompany this attitude of the population for better management of diseases. For both species, the leaves are the most used organs for the treatment of these diseases. These observations have also been made by other authors, such as [30,31]. Indeed, the intense picking of the leaves does not present any danger to the plant. According to Ouattara [32], removing $50\%$ of a tree’s leaves does not significantly affect its survival. In addition, various methods of preparation (decoction, maceration, and trituration) have been observed in the use of these plants. Decoction is used more than the other methods of preparation. Bla et al. [ 30] also noticed that this mode of preparation is used more than the others. In addition, the organs of these plants are used in the formulation of several recipes. M. charantia and M. lucida are used for specific mono recipes or in association with other plants. Mono-specific recipes were in the majority compared to plant associations. This trend is confirmed in other studies [32], who reported 24 medicinal recipes, 21 of which are mono-specific, i.e., $87.5\%$. The phytochemistry of plants using GC-MS revealed the richness of the extracts of the two plants in volatile compounds through the identification of more than 58 volatile compounds with variable relative abundances. 2,6-Bis (1,1- dimethylethyl)-4-(1-oxopropyl)phenol ($27.03\%$) was the more abundant compound found in the both extracts. This compound was also identified in jujube fruits by Wang et al. [ 33] with good antioxidant activity. Zeb [34] also reported its antioxidant activity in edible oils. Apart from this compound, ethyl iso-allocholate was also found in all the extracts of both plants with a relative abundance of $14.33\%$. Other authors, including Haider et al. [ 35] and Jasso de Rodríguez et al. [ 36], isolated this compound in other plant species, Adiantum capillus-Veneris and Psacalium paucicapitatum, respectively. This compound (Ethyl iso-allocholate) of steroidal nature has been reported as a potential therapeutic agent, as it has diuretic, anti-inflammatory, anticancer and antimicrobial activities [35,36,37]. Chokki et al. [ 6] also reported that the antimicrobial activity observed with these plants would be attributed to their chemical composition. Other studies [38,39] have shown that these plants contain various active metabolites known to have many biological activities. The extracts of M. charantia, as well as those of M. lucida prevented the denaturation of the protein used in this study at percentage inhibitions ranging up to 99.53±$0.08\%$ for the methanolic extract of M. charantia. Among these metabolites, flavonoids were found in all the extracts of the two plants [6]. The flavonoids present in these extracts could be the basis for the better activity demonstrated by these extracts because flavonoids have been considered to possess significant anti-inflammatory properties, both in vitro and in vivo [40,41]. Ethyl iso-allocholate found in all the extracts was reported for its anti-inflammatory activity [35]. Several authors, such as Lee et al. [ 42], proved the anti-inflammatory activity of M. charantia. Indeed, these authors showed that LPS-induced phosphorylation and nuclear translocation of NF-κB may be inhibited in the presence of M. charantia. Ayertey et al. [ 43] have shown, by using macrophages, that the anti-inflammatory effect of M. lucida may be due to inhibition of pro-inflammatory mediators, such as serotonin and histamine, inhibition of pro-inflammatory cytokines (IL-1b and TNF-a), inflammatory enzyme expressions (iNOS and COX-2) and their products (NO and PGE2). These authors [43] also established that M. lucida extracts attenuated systemic inflammation (with fever) induced by LPS in rats and upregulated the anti-inflammatory cytokine, IL-10. Another study [44,45] demonstrated that cucurbitane-type triterpenoids compounds isolated from M. charantia could inhibit the production of IL-6 in LPS-stimulated bone marrow-derived dendritic cells, and the authors attributed these anti-inflammatory effects to interactions of hydrogen bonds between the protein residues and hydroxyl groups and sugar rings of triterpenoids compounds. There is an intrinsic relationship between diabetes, oxidative stress and inflammation [46]. Indeed, the antioxidant activity of the extracts of the two plants was evaluated in vitro by different methods. The extracts showed good antioxidant activity with ABTS and FRAP methods. Ayertey et al. [ 43] reported that M. lucida extracts showed a strong antioxidant property compared to the positive control. In our study, cyclic voltammetry was used to evaluate the reversible antioxidant effect of M. charantia and M. lucida. Electrochemical methods, such as voltammetry and amperometry, have been used to determine the total antioxidant capacity of the extracts [47,48,49]. The open circuit potential (OCP), which measures the equilibrium potential at the electrode surface, can be used to quantify a samples’ redox potential, which is a function of its composition [50]. It was registered in this study and the results obtained with M. charantia and M. lucida indicate that the overall redox potential of both plant extracts in methanol have no significant difference. Cyclic voltammetry (CV) can yield much more information about multiple species in the electrolyte than OCP by qualitative or quantitative determination [48]. The antioxidant capacity of the extract is highlighted by its redox profile from CV. The anodic area of CVs can be correlated with the antioxidant capacity of the extracts [51]. Both anodic areas of cyclic voltammograms show the total content of antioxidant compounds, allowing discrimination between different extracts. We can conclude that the extracts undergo an irreversible oxidation in the same conditions for the anodic peak. The CV technique can also be helpful to determine the mechanism of free radical scavenging because of their potential use in traditional medicine. ## 4.1. Ethnopharmacological Study Area The study was carried out in the form of surveys, which were conducted in southern Benin in the departments of Ouémé and Plateau. The study area belongs to the Guinean zone, which is located between 6°25′–7°30′ N and 2°33′–2°58′ E, where the rainfall regime is bimodal (April-June and September-November), with an average rainfall of 1200 mm per year. The average temperature varies from 25 °C to 29 °C and the air humidity from $69\%$ to $97\%$. The vegetation formations of the area have been strongly affected by various agricultural activities and now form a mosaic of cultivated land and some relics of forest [52]. Specifically, the department of Ouémé is characterized by ferralitic, clayey–sandy, alluvial and colluvial soils, with essentially entropized vegetation made up of a few forest relics in places. There is also a grassy savannah, meadows, marshy raffia formations and some mangroves. The Plateau department is characterized by tropical ferruginous soils, bar land on the continental terminal and very deep and humus-rich clay soils. The climate is of the Sudano-Guinean type [53]. The populations of the study area are mainly composed of the Fon, Goun, Ouémè, Yoruba, Nago and Tori ethnic groups. They are mostly farmers whose main crops are maize, cassava, groundnut, cowpea and palm oil. They also engage in trade, fish farming and animal breeding. ## 4.2. Ethnopharmacology Survey The ethnopharmacological survey was conducted among five ethnic groups (Goun, Ouémè, Yoruba, Tori and Sèto) of the selected villages. The choice of villages and ethnic groups was made according to a few considerations, such as: the accessibility of the area (village), the level of use of these plants in the broad sense, the socio-cultural particularities and the openness and adhesion of traditional healers and herbalists to participate in the survey. The respondents (traditional healers and herbalists) were sampled according to the method used by Assogbadjo et al. [ 54]. It consisted of addressing a question to 30 individuals from each ethnic group. The question was whether the individual knew both M. charantia and M. lucida. The sample size was determined by the binomial distribution formula described by Dagneli [55]. n=U1−a/22×p1−pd2 n is the sample size, p is the proportion of respondents who gave a positive answer (yes), d is the margin error of the evaluation and U1−/2 is the value of the random variable for probability 1−/2. For a probability of 0.975 (or = 0.05), U1−/2 ≈ 1.96. The ethnopharmacological surveys were conducted according to the methodology described by Legba et al. [ 56] and include semi-structured free surveys. The free semi-structured surveys were carried out in the form of open interviews with herbalists and traditional healers using a pre-established form. The free surveys were conducted both individually and in groups, while semi-structured surveys were conducted only in groups. In both types of survey, occasional discussions were also conducted for additional information. Various information on knowledge, the diseases treated, the recipes, the organs used, the dosages, the side effects and contraindications of the two plants under study (M. charantia and M. lucida) were collected and documented during the investigations in-field. ## 4.3.1. Chemicals The extraction solvents, ammonium salt [2,2-azinobis (3-ethylbenzothiazoline-6-sulfonic acid)] (ABTS), phosphate bovine serum (PBS), bovine serum albumin (BSA), Butylhydoxytoluene (BHT) and ascorbic acid, were purchased from Sigma Aldrich (Steinheim, Allemagne). Diclofenac was obtained from Symed Pharm. Pvt., Ltd., Hyderabad, India. All the other chemicals and reagents used were of analytical reagent grade. ## 4.3.2. Plant Material The leaves of the plants used were locally grown. The M. lucida leaves samples were collected from Agata (06°30′28″ N, 002°38′44″ E), which is located in the department of Oueme, Benin, while those of M. charantia were collected from Dangbo (06°35′19″ N, 002°33′15″ E) located in the same department. The fresh samples collected were sent to the national herbarium. The samples were identified by the Researcher (Prof. YÉDOMONHAN Hounnankpon) in charge of the identification of plant species at the national herbarium of Benin. Voucher specimens No. AAC8100/HNB and No. AAC8101/HNB for M. lucida and M. charantia, respectively, were deposited at the Benin national herbarium, University of Abomey-Calavi, Cotonou, Benin. All the samples were collected in June 2022 in the morning at 7 a.m. They were air-dried (23 ± 2 °C) for two weeks before being powdered using a grinder Retsch-type SM $\frac{2000}{1430}$/Upm/Smf, Haan, Germany. ## 4.3.3. Preparation of Plants Extracts The samples were prepared by extraction with different polar solvents (water, water–ethanol 30:70 (v/v) methanol, methanol/$1\%$ HCl, ethanol, acetone, ethyl acetate and dichloromethane) and non-polar solvents (chloroform and petroleum ether). For the polar solvents, 1 g of powder in 100 mL of solvent was subjected to ultrasonication (35 kHz) at room temperature for 2 h. The same operation was carried out with non-polar solvents under the reflux system. A total of 24 extracts were thus obtained, 12 per plant. In addition, the residues obtained after the ethyl acetate and petroleum ether extractions were extracted again using methanol and methanol/$1\%$ HCl, respectively. These extracts were coded Methanol-EA and Methanol/HCl-PE. Each mixture was filtered through Whatman N° 1 paper (125 mm ø, Cat No. 1001 125) and concentrated under reduced pressure using a rotary evaporator before being oven dried at 40 °C. The aqueous extract was lyophilized to dryness. ## 4.3.4. Antioxidant Activity of Extracts by the ABTS Essay The antioxidant activity was carried out according to the protocol described by Cudalbeanu et al. [ 57]. It is based on the discoloration of the stable radical cation ABTS+· [2,2′-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid)] into ABTS. The ABTS radical cation stock solution was prepared by mixing an equal quantity (5 mL) of a 7.8 mM solution of ABTS and a 140 mM potassium persulfate solution. The mixture was kept in the dark for 12 h at room temperature. The solution was then diluted to obtain an absorbance between 1.1 ± 0.02 units at 734 nm. Fresh ABTS radical cation solutions were prepared for each run. A quantity of 100 µL of each extract at 500 µg/mL was mixed with 100 µL of the ABTS solution in a 96-well microplate. The same operation was realized for ascorbic acid (250 µg/mL) used as a reference. The absorbance was then measured at 734 nm after 30 min of incubation. All the assays were performed in triplicate. ## 4.3.5. Ferric Reducing Antioxidant Power (FRAP) Essay The reducing power was determined according to the method of Chio et al. [ 58]. Briefly, various concentrations of the extracts in 0.5 mL samples were mixed with 1 mL of a phosphate buffer (0.2 M, pH 6.6) and 1 mL of $1\%$ potassium hexaferricyanide [K3Fe(CN)6], and the mixture was incubated at 50 °C for 30 min. Afterwards, 1 mL of $10\%$ trichloroacetic acid was added to the mixture, which was then centrifuged at 3000× g for 10 min. Finally, 1 mL of the upper layer of the solution was mixed with 0.2 mL of $0.1\%$ FeCl3, the mixture was left to rest away from light and the absorbance was measured at 700 nm. The same operation was realized with BHT (0–100 µg/mL) used as a reference. The antioxidant activity linked to reducing power was expressed as antioxidant power (AP) following the formula AP=Abs Extract−Abs blankAbs Extract×100 ## 4.3.6. Evaluation of the Reversible Effects of the Antioxidant Activity of M. charantia and M. lucida Extracts by the Cyclic Voltammetry Technique Electrochemical investigations using cyclic voltammetry (CV) were used to assess possible reversible effects of the antioxidant activity of M. charantia and M. lucida leaf extracts. The electrochemical system consisted of an electrochemical cell (20 mL) with three electrodes: a carbon glass electrode as a working electrode, Ag/AgClsat (E0 = 0.194 V/NHE) as a reference electrode and a Pt wire as a counter electrode. The measurements were carried out at room temperature with the Bio-logic SP-150 galvanostatic potentiostat (Claix, France). The applied potential was E = ±1 V vs. Ag/AgClsat, varying the scan rate between 10 and 200 mV/s. The working electrode was polished with the BASi® polishing kit (alumina and diamond sludge) followed by washing with methanol after each voltammetry experiment. Quercetin was also analysed as the main component of the extracts. Fresh solutions of M. charantia and M. lucida leaf extracts at 1 mg/mL and quercetin (10−3 M) were prepared in methanol. UV-Vis spectra were recorded before and after the cyclic voltammetry experiments using the Specord 210 Plus dual-beam spectrophotometer (Analytik Jena, Jena, Germany). The spectra were performed in the wavelength range of 200–700 nm using 1 cm quartz cells. ## 4.3.7. Anti-Inflammatory Activity by Inhibiting Protein Denaturation The anti-inflammatory effect of the extracts of the two plants was evaluated in vitro by looking for the thermal denaturation of albumin by an adaptation of the protocol described by Sangita et al. [ 59]. The reaction mixture (250 μL) consisted of 10 μL of albumin, 140 μL of phosphate buffer (PBS, pH 6.4) and 100 μL of extracts of 20 mg/mL concentrations. In a 96-well microplate, a series of 10 successive dilutions ($\frac{1}{2}$) of each extract was made from sample solutions at 20 mg/mL dissolved in methanol or water. The mixtures were incubated in the dark for 15 min and then heated at 70 °C for 5 min. After cooling, their absorbance was measured at 660 nm against a blank prepared under the same reaction conditions by replacing the extracts with the same volume of solvent. Diclofenac (0-100 µg/mL), an anti-inflammatory, was used as the standard. For each concentration, three [03] tests were carried out. The effect of the extracts on the thermal denaturation of albumin at 70 °C was expressed by the inhibition rate, calculated according to the formula below Inhibitory rate=AbsC−AbsE ×100AbsC AbsC: variation of absorbance at 660 nm of control, AbsE: variation of absorbance at 660 nm of the extracts. ## 4.4. GC-MS Analysis This analysis was carried out to search for and identify the volatile compounds contained in two types of extracts from each plant. These are the ethyl acetate and acetone extracts of the two plants (M. charantia and M. lucida). After dissolving the extracts in methanol (1 mg/mL), the extract solution was filtered using a 0.45-µm diameter PTFE filter. GC-MS analyses were performed on a Varian 4000 electron impact mass spectrometer using a Varian CP-8400 injector. The 30 m × 0.25 mm-Factor four column capillaries had a particle size of 0.25 µm (Varian). The injection volume was 100 µL with the injection temperature set at 250 °C. The flow rate of helium gas through the column was 1 mL/min, the ions were generated at an electron impact (EI) of 70 kV, the temperature of the ion source was set at 200 °C and the mass range was m/z 50–1000. The column temperature was kept isothermal at 70 °C for 2 min and then raised to 300 °C at a rate of 10 °C/min. Authentic assay standards were used to compare the retention time and retention index with the detected compounds. The compounds were identified against the baseline mass spectra (National Institute of Standard and Technology Mass Spectral v2.1). ## 4.5. Data Processing and Statistical Analysis The data from the field surveys were coded and entered into an Excel 2007 database. These data were analysed with SPSS software (Statistical Package for the Social Sciences) version 16.0 to determine the descriptive statistics in terms of percentage and mean. The consensus factor (Fic) was used to assess the degree of homogeneity of information [23]. It is calculated by the formula [1]Fic=Nur−NtNur−1 with Nur being number of reported uses per disease category and Nt being total number of species used for treatment. The values range from 0 to 1, where 1 indicates the highest level of consent. The experimental results were presented as the mean ± standard deviation (SD) of three parallel measurements. The graphs were presented using GraphPad Prism 7.00 software. A multivariate variance analysis followed by Duncan’s test was performed. Values of $p \leq 0.05$ were considered statistically significant. ## 5. Conclusions Several actions falling within the framework of the valorisation of M. charantia and M. lucida, two plants used within the Beninese population, have been undertaken. An ethnopharmacological survey made it possible to identify endogenous knowledge related to the traditional use of these two plants in the treatment of infectious and metabolic diseases. The volatile molecules contained in the leaves of M. charantia and M. lucida have been researched. This analysis revealed the richness of the extracts of the two plants in volatile compounds with variable relative abundances. 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--- title: How Fast Do “Owls” and “Larks” Eat? authors: - Ludovica Verde - Annamaria Docimo - Giovanni Chirico - Silvia Savastano - Annamaria Colao - Luigi Barrea - Giovanna Muscogiuri journal: Nutrients year: 2023 pmcid: PMC10058363 doi: 10.3390/nu15061437 license: CC BY 4.0 --- # How Fast Do “Owls” and “Larks” Eat? ## Abstract Chronotype is a reflection of an individual’s preference for sleeping, eating and activity times over a 24 h period. Based on these circadian preferences, three chronotype categories have been identified: morning (MC) (lark), intermediate (IC) and evening (EC) (owl). Chronotype categories have been reported to influence dietary habits; subjects with EC are more prone to follow unhealthy diets. In order to better characterize the eating habits of subjects with obesity belonging to three different chronotype categories, we investigated eating speed during the three main meals in a population of subjects with overweight/obesity. For this purpose, we included 81 subjects with overweight/obesity (aged 46.38 ± 16.62 years; BMI 31.48 ± 7.30 kg/m2) in a cross-sectional, observational study. Anthropometric parameters and lifestyle habits were studied. Chronotype score was assessed using the Morningness–Eveningness questionnaire (based on their scores, subjects were categorized as MC, IC or EC). To investigate the duration of main meals, a dietary interview by a qualified nutritionist was conducted. Subjects with MC spend significantly more time on lunch than subjects with EC ($$p \leq 0.017$$) and significantly more time on dinner than subjects with IC ($$p \leq 0.041$$). Furthermore, the chronotype score correlated positively with the minutes spent at lunch ($$p \leq 0.001$$) and dinner ($$p \leq 0.055$$, trend toward statistical significance). EC had a fast eating speed and this, in addition to better characterizing the eating habits of this chronotype category, could also contribute to the risk of developing obesity-related cardiometabolic diseases. ## 1. Introduction According to the latest reports of the World Health Organization (WHO), obesity is on an unstoppable increase worldwide, tripling in the last forty years [1]. The increased health risks brought on by excess body weight make it a major global health issue. It is known that obesity is a multifactorial disease in which lifestyle, socio-economic, genetic, endocrine, and several other factors intervene [2]. Despite the confirmed associations between obesity and its markers, there is an ongoing search for new factors to manage and slow the epidemic. Recent studies show that eating habits and obesity seem to be influenced also by chronotype [3,4,5], which reflects an individual’s preference for the timing of sleeping, eating, and activity in a 24 h period [6]. Morning, evening, and intermediate chronotypes are the three main categories of chronotypes. Subjects with morning chronotype (also called “lark”) prefer to rise early and tend to carry out activities earlier in the day. Contrarily, subjects with evening chronotype (also called “owl”) typically wake up later and prefer to schedule their peak activity during the late afternoon or evening. Between the morning and evening chronotypes, there are subjects with intermediate chronotype. Subjects with the intermediate chronotype tend to have a circadian rhythm that is somewhat more flexible with mixed characteristics. Therefore, they have greater flexibility in adapting to the demands of daily life, without any particular time slot being particularly problematic for them [6]. Nutrients, metabolic processes, and circadian rhythms are all interconnected. Because subjects with evening chronotype tend to engage in nighttime behaviors that are not in tune with the cycle of light and dark, they frequently experience circadian misalignment. Delay in meal timing and a habit of skipping breakfast has been often detected in subjects with evening chronotype [4]. In addition, engagement with excessive consumption during nighttime, lower protein and vegetables intake, as well as increased sucrose, sweets, caffeine, and alcohol intake characterize these subjects [4,7]. Probably as a consequence of this circadian misalignment and unhealthy lifestyle habits, subjects with evening chronotype have been reported to have more health problems, such as psychological disorders, gastrointestinal diseases, and higher mortality than the morning chronotype. Finally, evening chronotype has also been identified as a risk factor for the development of obesity-related cardiometabolic diseases [8,9]. In contrast, subjects with morning chronotype seem to have better, more protective dietary behavior, as indicated by regular consumption of breakfast and fresh and minimally processed foods, such as fruit, vegetables, fish, and dairy products [7]. As well as chronotype, eating behavior plays a crucial role in obesity-related cardiometabolic disease prevention and management due to its influence on energy balance and close interaction with other factors, such as nutrigenomics and psychology [10]. Eating behaviors are defined as the broad spectrum of behaviors related to eating lifestyle, including mealtimes, food preparation methods and eating speed. Of note, eating speed is one of the elements that accompanies the lives of modern consumers under time pressure. Therefore, consumers worldwide choose easy-to-prepare, often highly processed meals and spend long hours in front of screens both at work and in their leisure time. In this context, previous studies have shown that slow eating correlates with lower energy intake [11]. Actual evidence has also indicated the importance of slowing down consumption as a necessary factor in improving eating behavior [11]. Therefore, slow eating could be correlated with a lower incidence of obesity [10]. Many experimental studies have found that eating speed is correlated with obesity risk [10]. In a feasibility study in 21 participants randomly assigned to consume a 600 kcal meal at either a “normal” or “slow” rate (6 versus 24 min), Hawton et al. showed that slow eating could influence satiety, appetite and play a role in hormonal pathways [12]. Taking this evidence into account, an increasing number of studies have examined the interaction between eating speed and metabolic syndrome, diabetes, non-alcoholic fatty liver disease and cardiovascular disease [13,14,15]. All results showed a positive relationship between eating speed and these diseases and highlighted the need to analyze them in relation to obesity. Since subjects with evening chronotype are more likely to present unhealthy eating habits, while subjects with morning chronotype are more likely to have healthy and protective habits, we aimed to better characterize nutritional habits of subjects with overweight/obesity belonging to the different chronotype categories, investigating the eating speed during the three main meals. ## 2.1. Design and Setting This cross-sectional, observational research included participants from the Obesity, Programs of nutrition, Education, Research and Assessment of the best treatment (OPERA) project as well as patients at the Federico II University Hospital’s Endocrinology/Obesity Outpatient Clinic in Naples, Italy [16]. The research was authorized by Federico II University’s Ethical Committee (n. $\frac{5}{14}$) and was carried out in accordance with the Declaration of Helsinki, which is the code of ethics for human experimentation adopted by the World Medical Association. All research participants received a thorough explanation of the study’s purpose, and their written informed consent was obtained. Recruitment consisted of an informational interview in which the details of the research were explained to the subjects, and they were encouraged to participate in the study. ## 2.2. Participants Eligible participants for the study were adult subjects aged 18–75 years with normal liver, cardiopulmonary and kidney function as determined by interview. Additionally, we excluded patients who were taking medications for cardiovascular, renal, or pulmonary illnesses. Trained nutritionists assessed anthropometric parameters and asked standard questions including demographic information, personal medical history and lifestyle habits. ## 2.3. Anthropometric Assessment The assessment period was from 8 to 12 a.m. Following an overnight fast, measurements were taken from each individual. The same qualified nutritionist conducted the anthropometric measurements. The subjects were measured wearing light clothing and without shoes. Height was measured with a stadiometer placed on a wall. Body weight was calculated with a calibrated scale. According to the National Center for Health Statistics [17], waist circumference was measured to the nearest 0.1 cm using a non-elastic tape measure at the natural indentation or at a point midway between the lower edge of the rib cage and the iliac crest if no natural indentation was evident. The hip circumference was measured while the subject was standing on one side and the measurement was taken from the widest point. For both measurements, subjects were standing with feet close together, arms along the sides and body weight evenly distributed. The subject had to be relaxed, and the measurements were taken at the end of a normal exhalation. Each measurement was repeated twice; if the measurements did not differ by more than 1 cm from each other, the average was calculated. If the difference between the two measurements exceeded 1 cm, the two measurements were repeated. The waist circumference was then divided by the hip circumference to determine the waist-to-hip ratio. ## 2.4. Lifestyle Habits Participants who regularly exercised at least 30 min per day (YES/NO) were defined as physically active, as we have reported in detail in previous studies [5,8,15]. ## 2.5. Eating Speed Assessment As we have reported in detail in a previous study, eating speed was assessed for each main meal (breakfast, lunch and dinner) [15]. A face-to-face interview with a qualified nutritionist was performed to collect information about meal duration (minutes) and eating habits (habitual consumed foods and beverages) at the main meals (breakfast, lunch, and dinner). According to median value of meal duration, subjects were classified into two groups based on the following meals duration: fast eating group (FEG) (breakfast < 10 min, lunch < 20 min, and dinner < 20 min) or slow eating group (SEG) (breakfast ≥ 10 min, lunch ≥ 20 min, and dinner ≥ 20 min). ## 2.6. Chronotype Assessment The Morningness–Eveningness Questionnaire (MEQ) was used to determine the chronotype of the subjects [18]. The MEQ consists of 19 multiple-choice questions about sleep patterns and daily functioning, including when participants feel most productive in physical or mental tasks, most tired, and most energized. Individuals were classified as morning (59–86), intermediate (42–58), or evening (16–41) chronotypes based on the sum of their individual items, which gave a total score ranging from 16 to 86 [18]. ## 2.7. Statistical Analysis Statistical analysis was performed according to standard methods using the Statistical Package for Social Sciences software 26.0 (SPSS/PC; SPSS, Chicago, IL, USA). The Kolmogorov–Smirnov test was used to assess the data distribution, and data that were not normally distributed were normalized using the logarithm. While categorical variables were expressed as frequency or percentage (N, %), continuous variables with normal distribution were given as mean ± standard deviation. One-way ANOVA and unpaired Student’s t test were used to analyze differences between groups (FEG and SEG and chronotype categories) for continuous variables. Chi-square test (χ2) was used to analyze differences between groups (FEG and SEG) for categorical factors. Using Pearson r correlation coefficients, we examined the relationships between chronotype score and eating speed during the major meals. The p values were considered significant at $p \leq 0.05.$ ## 3. Results The main clinical characteristics of the study population are reported in Table 1. Eighty-one participants (28 men and 53 women) were included in the analyses. They were aged 46.38 ± 16.62 years and presented a mean BMI of 31.48 ± 7.30 kg/m2. Mean waist circumference of included subjects was 99.42 ± 20.64 cm while mean waist-to-hip ratio was 0.92 ± 0.13. Only a small fraction of the subjects was physically active (14, $17.3\%$). ## 3.1. Chronotype Categories in the Study Population and Degree of Obesity According to the Same Categories Chronotype categories in the study population were distributed as follows: 14 ($17.3\%$) subjects had morning chronotype, 40 ($49.4\%$) had intermediate chronotype, and 27 ($33.3\%$) had evening chronotype (Figure 1). The mean BMI of subjects divided into chronotype categories were as follows: 30.22 ± 5.53 kg/m2 for morning chronotype, 31.12 ± 6.01 kg/m2 for intermediate chronotype, and 32.00 ± 7.82 kg/m2 for evening chronotype. No differences were observed in BMI between the chronotype categories ($$p \leq 0.704$$) (Figure 2). ## 3.2. Clinical Characteristics According to Eating Speed at Main Meals Table 2 shows the main characteristics of the entire study population according to the eating speed at breakfast, lunch and dinner. No significant differences were observed in terms of gender proportion, age, anthropometric parameters, and physical activity between FEG and SEG at breakfast, lunch and dinner. The only exceptions were a significantly higher waist circumference in the SEG group compared to the FEG group at lunch (0.96 ± 0.13 vs. 106.60 ± 11.27 cm; $$p \leq 0.041$$) and a significantly higher waist-to-hip ratio in the SEG group compared to the FEG group at both lunch (0.96 ± 0.13 vs. 0.90 ± 0.12; $$p \leq 0.041$$) and dinner (0.96 ± 0.13 vs. 0.89 ± 0.12; $$p \leq 0.039$$). ## 3.3. Chronotype Categories According to Eating Speed at Main Meals Table 3 shows the differences in chronotype categories according to eating speed during the three main meals. No significant differences were observed in terms of chronotype categories between FEG and SEG at breakfast. At lunch, there was a significant difference in chronotype categories between FEG e SEG ($$p \leq 0.025$$). The same difference was observed at dinner describing a p value (0.050) close to but not quite statistically significant as supporting a trend toward statistical significance. ## 3.4. Differences in Eating Speed of Main Meals between Chronotype Categories In particular, subjects with morning chronotype spend significantly more time on lunch than subjects with evening chronotype (18.93 ± 5.94 vs. 12.96 ± 6.39 min; $$p \leq 0.017$$) and significantly more time on dinner than subjects with intermediate chronotype (19.64 ± 5.71b vs. 15.25 ± 4.52; $$p \leq 0.041$$) (Table 4). ## 3.5. Correlation Studies Simple and after-adjustment for BMI and age correlations between the chronotype score and the minutes spent eating breakfast, lunch and dinner are shown in Table 5. The chronotype score correlated positively with the minutes spent at lunch ($$p \leq 0.001$$) and dinner ($$p \leq 0.055$$, trend toward statistical significance). The positive correlation with minutes spent at lunch was maintained even after correction for confounding factors ($$p \leq 0.002$$) ## 4. Discussion This cross-sectional observational study provides the first evidence to support the different eating speeds between the chronotype categories in subjects with overweight/obesity. In particular, the main finding of our study was that subjects with the morning chronotype spent significantly more time at lunch than subjects with the evening chronotype and significantly more time at dinner than subjects with the intermediate chronotype. In addition, the chronotype score was positively correlated with the minutes spent at lunch, i.e., as the time spent eating meals increases, the score indicating a morning chronotype increases (and vice versa). There is a growing interest in the behavioral phenotypes linked to the development of obesity, with the purpose of better detailing the aspects on which we can intervene to improve the current treatment of this condition and its cardiometabolic complications. Eating speed has attracted attention as an indicator of appetite and satiety: a fast eating speed is thought to indicate greater motivation to eat, and more rapid deceleration over the course of the meal is thought to indicate a stronger response to internal satiety signals [19]. Experimental studies that manipulated eating speed in a controlled setting confirmed that fast eating speed is associated with greater food intake [20,21], and this higher food intake, certainly in conjunction with many other factors, could facilitate the development of obesity. In our population of subjects with overweight/obesity, this seems to be confirmed, as the FEG group is superior in absolute numbers for all three main meals, suggesting that a fast eating speed is a characteristic often present in individuals suffering from obesity. Of interest, eating speed has a substantial heritable component, as reported in a study of twin pairs where the heritability of eating speed was high (0.62; $95\%$ CI: 0.45, 0.74) [22]. In addition, research in animal models [23] and humans [24] has found that circadian rhythms are also partly genetically determined. The length of an individual’s circadian period can be significantly shorter or longer than the average 24 h period [25]. The extremes of this normal variation appear to be strongly driven by genetics, along with other features of circadian periodicity in humans; sensitivity to zeitgebers (environmental stimuli that synchronize the biological rhythms of organisms with their environment) has also been shown to be genetically variable [26]. Individual variations in phase, phase entrainment angle and period, together with environmental factors and age, contribute to the so-called “chronotype”, each person’s unique daily activity pattern. In the general population, these strong genetic determinants are presumably the sum of many small-effect genetic variations [24]. It has already been reported in the literature that subjects with evening chronotype have an overall unhealthier lifestyle. Subjects with an evening chronotype are more frequently smokers, sedentary, consume more processed foods and have a lower adherence to the Mediterranean diet [27]. These and other evening chronotype-related factors could contribute to the risk of developing obesity-related cardiometabolic diseases [9,28,29]. Our study adds a new element to this disadvantageous picture of the evening chronotype, that is, a fast eating speed. This, according to what has been previous reported, could be part of a partly genetically predetermined set-up that includes both chronotype and eating speed. In particular, our results show that subjects with evening chronotype had a faster eating speed at lunch than subjects with morning chronotype. This is probably because lunch is, by social habits, the main meal in the study population (Italy), and since the evening chronotype is marked by poorer eating habits, it is likely to be characterized by a frugal meal, made with ready-to-eat or fast-food meals. We would also like to emphasize the fast eating speed at dinner of subjects with intermediate chronotype compared to subjects with morning chronotype. The intermediate chronotype is less described in the literature, and the limited evidence on it indicates that this chronotype category has mixed general characteristics. However, in our study, subjects with intermediate chronotype seemed to have an eating speed more similar to that of subjects with evening chronotype, and thus representing almost half of our population, it could be another category of subjects that should be given more attention during clinical evaluations. Finally, we found a positive correlation between chronotype score and minutes spent eating lunch. This reinforced the fact that in obesity, subjects with a lower chronotype score (i.e., those who had a greater preference for nighttime versus daytime activities) tended to eat faster at lunch than those with a higher chronotype score. Although this emphasizes the importance of expanding assessments of the eating behaviors of subjects with obesity, the correlation does not provide cause-and-effect relationships, and further studies are needed to replicate the data found in the current study. The limitations of our study should be noted. We had no data on meal size; thus, the fast eaters could be such because they consumed smaller meals than the slow eaters. However, we did not observe differences in BMI; thus, we did not expect major differences in the meals (quality and quantity) consumed between the two groups. Another limitation of the study is that it did not include a “chewing count” for each bite of food or a timekeeping of the meals. However, the introduction of the counting or timing could have influenced the participants’ chewing or eating speed, moving away from a real-life study. For this reason, the most reliable way to assess eating speed was retrospectively, i.e., asking the person to remember how long it took them to eat a meal they had already eaten, as previously reported [15]. This mode of assessment was more reliable, as there was no possibility of the subjects altering their eating behavior, knowing that they were being watched or timed. A strength of our study is the novelty of the discovery, which anticipates future research in the field of the behavioral aspects that characterize obesity. Since it does not seem that obesity will stop growing, further efforts are certainly needed to intervene on new factors that favor the development of this pathology. Evening chronotype as well as eating speed are both well-known predisposing factors for the development of obesity-related cardiometabolic diseases. Finding new solutions to modify these behavioral aspects could play an important role in future anti-obesity complications strategies. Further study is required to develop effective interventions to manipulate eating speed over the long-term by using a variety of techniques, such as environmental changes, behavioral training beginning in infancy, and changes to food texture. ## 5. Conclusions The findings of this study contribute to a better characterization of the eating habits of subjects with the evening chronotype, who were shown to eat faster than subjects with the morning chronotype. As these connections have an influence on the possibility of developing cardiometabolic diseases, the interaction between chronotype and eating speed in subjects with obesity is significant. 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--- title: 'Transcranial Doppler Echography Measurement in Hemodialysis Patients: The Potential Role of Angiotensin II Receptor Blockades on Cerebrovascular Circulation' authors: - Kyoko Maesato - Shuzo Kobayashi - Takayasu Ohtake - Yasuhiro Mochida - Kunihiro Ishioka - Machiko Oka - Hidekazu Moriya - Sumi Hidaka journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10058379 doi: 10.3390/jcm12062295 license: CC BY 4.0 --- # Transcranial Doppler Echography Measurement in Hemodialysis Patients: The Potential Role of Angiotensin II Receptor Blockades on Cerebrovascular Circulation ## Abstract Background: Although hemodialysis (HD) patients have an elevated risk of strokes, there are few reports about transcranial doppler (TCD) echography measurements. It is well-known that angiotensin II receptor blockades (ARBs) protect against cardiovascular complications. In this study, we measured intracranial artery (ICA) velocity using TCD echography and studied the associated factors with its velocity in HD patients by a comparison with or without ARBs. Methods: We conducted a cross-sectional study in a single hospital. We included 61 patients who had measurable ICA velocity by TCD echography. Among them, the ARB usage group consisted of 22 subjects, whilst the non-ARB usage group consisted of 39 subjects. Results: Patients in the ARB (+) and ARB [-] groups did not show any difference in basic characteristics. ICA blood flow velocity in all intracranial arteries tended to show greater values in the ARB group than those in the non-ARB group. Particularly, blood velocity in the middle cerebral artery (MCA) (maximal flow velocity) statistically increased in the ARB group, respectively. In a univariate analysis, MCA maximum velocity was significantly associated with ARB usage ($$p \leq 0.011$$) and low hematocrit levels ($$p \leq 0.045$$). The multivariate analysis chose only ARB usage as an independent factor associated with left MCA maximum velocity ($$p \leq 0.022$$). Conclusions: We showed that dialysis patients with ARBs have significantly higher ICA blood velocity. ARBs might have a potential benefit for maintaining ICA blood flow in HD patients. ## 1. Introduction It is well-known that there is a higher risk of cardiovascular and/or cerebrovascular complications in HD patients than in the general population, although the cerebrovascular mortality rate in HD patients has decreased every year in Japan, being $5.5\%$ in 2007 in contrast to $10.8\%$ in 1990 [1]. It should be noted that there are many reports concerning the vasoprotective effects of the renin–angiotensin aldosterone blockade. Reports from the HOPE study [2] and LIFE study [3] demonstrated that angiotensin-converting enzyme inhibitors (ACE-I) or angiotensin II type 1 (AT1) receptor blockades (ARBs) could effectively decrease the incidence of strokes in patients at risk. Moreover, there are a few reports about intima–media thickness (IMT) regression with candesartan [4]. Another report showed the anti-inflammatory and neuroprotective effect of ARBs in a brain ischemia–reperfusion model [5]. Transcranial Doppler (TCD) echography is a useful tool to assess intracranial vascular disease in the general population, especially high-risk patients. However, to our knowledge, little information is available regarding TCD measurements of HD patients. Therefore, in this study, we measured intracranial artery (ICA) blood flow using TCD echography in HD patients and compared the data with the reference data of ICA velocity obtained from the general population. Furthermore, we evaluated the effectiveness of ARBs on ICA velocity. ## 2.1. Patients We performed this cross-sectional study at a single HD center in our hospital ($$n = 134$$). Patients with maintenance HD for at least a 3 month period were eligible for entry into the study. The exclusion criteria were as follows: [1] a history of cerebrovascular disease and brain MRA abnormality; [2] a history of chronic atrial fibrillation; [3] failed ICA blood flow measurement by TCD echography due to a narrow temporal bone window, creating an inability to detect arterial signals; and [4] disagreed to be examined by TCD echography (Figure 1). All patients had AVF as a vascular access and none used CVC. We examined the univariate association between ICA blood flow and several factors. ARB usage was adopted in the process; thus, we divided our patients into two groups, with a comparison according to ARB usage with respect to MCA velocity. The ARB usage group consisted of 22 subjects and the non-ARB usage group consisted of 39 subjects. All subjects gave informed consent and the ethical committee of our hospital approved the present study (approval number: TGE01984-024). ## 2.2. Method We measured ICA velocity with TCD echography on non-HD days. This method can measure the cerebral vessel flow velocity (maximal flow velocity (Vmax) = peak systolic flow velocity; minimal flow velocity (Vmin) = end diastolic flow velocity). Using temporal, occipital acoustic windows, we measured the flow velocity of the ICA as follows: bilateral middle cerebral artery (MCA); bilateral vertebral artery (VA); and basilar artery (BA). The mean flow velocity (Vmean) was calculated as Vmin + $\frac{1}{3}$(Vmax − Vmin). The pulsatility index (PI) was calculated as (Vmax − Vmin)/Vmean. The resistive index (RI) was calculated as (Vmax − Vmin)/Vmax. As the diameter of cerebral arteries is fixed, the PI and RI are influenced by peripheral small artery resistance. We calculated the Vmean, PI and RI for every intracranial artery and compared them in two groups. Due to a few reports showing a laterality of intracranial artery flow velocity, especially during cognitive tasks [6], we compared these data separately. On the same day, we examined both carotid arteries using a 7.5 MHz linear array transducer with high-resolution B-mode echography (Aloka, Tokyo, Japan). The carotid arteries were examined bilaterally in the areas of the common carotid arteries (1 cm proximal to the dilatation of the carotid bulb), carotid bifurcation (1 cm proximal to the flow divider) and the internal carotid arteries (1 cm distal to the flow divider), according to the method reported by Kobayashi et al. [ 7]. Intima–media thickness (IMT) was defined as the distance between the leading edge of the lumen–intima echography of the near wall and the leading edge of media–adventitia echography. We then measured the maximum and minimum flow velocity (CCA Vmax) of the common carotid arteries. Two well-trained sonographers performed these measurements. To enhance the reproducibility of the measurements, they used a standardized complementary interrogation. We calculated the body mass index (BMI) on the same day using the following formula: BMI = body weight (kg)/(height (m))2. Blood samples were drawn from the arterial site of the arteriovenous fistula at the beginning of a dialysis session on a dialysis day. We measured serum calcium, inorganic phosphate (IP), hemoglobin (Hb), hematocrit (Hct), total protein (TP), albumin (Alb), total cholesterol (T-Cho), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein (LDL-C), high-sensitive C-reactive protein (hsCRP), β2-microglobulin (β2MG) and plasma fibrinogen levels. We calculated corrected calcium using the following formula: estimated calcium concentration = serum calcium (mg/dL) + (4-serum albumin concentration). As hsCRP was not normally distributed, we used logarithmically transformed hsCRP. We measured the blood pressure at the beginning of each HD session on the upper arm of the non-venous arterial fistula side. ## 2.3. Statistical Analysis The continuous data were expressed as the mean ± SD. According to an initial result that concluded ARB usage was significantly associated with ICA velocity, we divided our patients into two groups, ARB use or not, and compared them using the Student’s t-test. A univariate regression analysis was performed to assess the predictive factors for ICA velocity. Multiple linear regression analyses were performed to examine the relationship between ICA velocity and the significant factors from the univariate regression analysis. A value of $p \leq 0.05$ was considered to be statistically significant. All statistical analyses were performed using SPSS version 11.0 (Tokyo, Japan). ## 3.1. Patient Characteristics From 134 patients, we included 61 (44 male; 17 female) patients in this study. Table 1 shows the basic characteristics of the patients. Of the patients, 37 ($60\%$) took a form of hypertensive. The numbers of patients given ARBs, calcium channel blockers, angiotensin-converting enzyme inhibitors (ACE-Is), αβ-blockers, β-blockers or α-blockers were 22, 34, 5, 17, 2 and 8, respectively. Of the 5 patients taking ACE-Is, 4 were also taking an ARB. This study was conducted when calcimimetics were not available. A total of 25 patients ($41\%$) were taking vitamin D. The patients used the following various types of ARB: losartan, 14 patients; candesartan, 1 patient; valsartan, 2 patients; telmisartan, 3 patients; and telmisartan plus losartan, 2 patients. There was no difference in basic characteristics between patients with ARBs and without ARBs (Table 2). We used Hct instead of Hb for rheological reasons. When we compared the ICA blood flow velocity with that of the non-HD general population as described by Barntt et al. [ 8] and Krejza et al. [ 9], the HD patients showed comparable figures (Table 3). ## 3.2. Doppler Echography Measurements The validities of the TCD measurements in this study via intra- and inter-observer differences were $5.4\%$ and $4.3\%$, respectively. The TCA Doppler measurements showed significantly higher maximum flow velocity levels (Vmax) in MCA in the ARB group compared with those in the non-ARB group (Table 4). Bilateral IMT tended to be smaller in the ARB group, although it was not statistically significant in the levels. For each of the measurements of cerebral arterial blood flow obtained by TCD echography and for each factor, only the left MCA Vmax was significantly correlated with ARB usage (Table 4). In the univariate regression analysis, ARB usage ($r = 0.443$; $$p \leq 0.011$$) and low Hct levels (r = −0.357; $$p \leq 0.045$$) were found to be statistically significant factors associated with left MCA Vmax (Table 5). The multivariate regression analysis chose only ARB usage as an independent association factor (Table 6). ## 4. Discussion The present study showed statistically significant higher MCA blood flow velocity in patients with ARB usage than without ARB usage in HD patients. Although statistically not significant, the patients with ARBs tended to have a higher velocity in all intracranial arteries and lower IMT in carotid arteries than the patients without ARBs. In the univariate and multivariate regression analyses, ARB usage alone was an independent factor for high blood velocity of MCA. Our results could mean that ARBs also have a vasoprotective effect on intracranial arteries in HD patients, similar to other reports [2,3] in the general population. The brain has both angiotensin 1 (AT1) and angiotensin 2 (AT2) receptor subtypes. The AT1:AT2 receptor ratio varies substantially with certain brain areas or nuclei, but in most locations, the AT1 receptor is predominant. The classical actions of angiotensin II in the brain include short- and long-term osmoregulation and the control of blood pressure. Under pathological conditions, the expression of the AT2 receptor is known to increase in brain tissue [5]. There are a few mechanisms regarding preserving brain perfusion by angiotensin II receptor blockade, including: [1] ARBs act directly as cerebral vasodilators [4]; [2] ARBs cause outward remodeling in resistance arteries [4]; [3] anti-inflammatory, anti-hyperplasia, anti-fibrous mechanisms promoting the regeneration of the neuron effect by stimulating the AT2 receptor [5]; [4] reducing the expression of the transcription factors c-fos and c-jun (in vivo) and an anti-apoptosis effect [5]; and [5] AT2 receptor-mediated activation of the transcription factor nuclear factor-κB in Schwann cells, leading to enhanced remyelination [5]. This effectiveness of ARBs not only accelerates the process of tissue repair, but also improves functional recovery [5] in brain tissue. Moreover, ARBs are known to improve dyslipidemia by lowering the serum levels of total cholesterol, LDL cholesterol and lipid peroxides (LPO) [10]. In our study, although the ARB usage group showed a higher intracranial flow velocity, there was no difference in the PI and RI between the two groups. The reason is still unknown. However, the influence of ARBs may have been greater on Vmax than Vmin, meaning that there was an effect on peripheral small artery resistance at the cardiac systole. In a general population study that included 598 patients with minor ischemic strokes or transient ischemic attacks, the mean flow velocity in the MCA was significantly correlated with age, male sex, diabetes, total serum cholesterol and hypertension [11]. Hypertensive patients who did not receive HD treatment showed a lower flow velocity in intracranial arteries than non-hypertensive patients [5]. Age and anemia are also associated factors for ICA blood flow velocity, correlating negatively and positively, respectively, as reported in previous literature [12]. The reason we used the left MCA in this study was that it was easier to obtain various parameter values by pulsed Doppler than from the right MCA. Regarding the left–right difference in cerebral blood flow, it has been reported that there is no association with AVF [13]. One theory as to the reason for the left–right difference in the MCA is that the rotation of the cervical spine may significantly affect vertebral artery blood flow [14], thus leading to changes in the blood flow in the basilar artery [15] and MCA [16]. In addition, an autopsy evaluation of the left–right difference in cerebral arterial flow showed significant cerebral infarction and ventricular atrophy in the left side of the brain. The same article also reported that the left cerebral infarction and ventricular atrophy were caused by overwork due to the presence of language centers in the left cerebral hemisphere and differences in the right and left branches of the carotid arteries in the aortic arch [17]. The TCD echography used in this study did not technically evaluate the arterial diameter and we cannot say whether it supported the report in the above article. An assessment of obstruction of MCA using TCD echography has already been standardized in the general population. However, to the best of our knowledge, no such data are available for HD patients. Therefore, a standardized assessment of MCA obstructions using TCD echography is still obscure. As it has been reported that asymptomatic lacunar infarction is more prevalent in CKD patients prior to HD induction [18], TCD Doppler measurements may be a valuable tool to detect poor conditions in ICA perfusion and to know whether ARBs may be effective against brain protection in high-risk groups such as CKD patients. This study had several limitations. This was a single-center, small study. Although we were able to identify the factors significantly associated with the outcome (such as ARB) at a conventional significant threshold of $p \leq 0.05$, we could not adjust for multiple testing with the sample size. Therefore, based on the current study findings, a confirmatory study with a larger sample size may be warranted. Furthermore, the cross-sectional nature of our observations precluded cause–effect inferences about the links between ICA blood flow velocity and ARBs. In terms of assessing intra-individual variations, there were limitations in terms of the study using Doppler echography. Unlike CT and MRI, TCD is a useful tool that can provide information on the dynamic state of cerebral blood flow, but it requires advanced skills of technologists and there are large disparities among technologists and facilities. For this reason, we decided to conduct this study within one facility. Securing an approach window from the temporal region to observe the middle cerebral artery is particularly difficult with older women and many cases were not available for examination. In addition, because cerebral blood flow is affected by arrhythmia, cardiac output, fluid balance, carotid arteriosclerosis, previous strokes, aging and awareness activity, we chose a cross-sectional research approach on this occasion. In this study, the coefficient of variations for the intra- and inter-observer variations were $5.4\%$ and $4.3\%$, respectively. On the other hand, for the reasons mentioned above, cerebral blood flow velocity values measured by TCD echography may fluctuate and frequent TCD echography examinations may lead to confusion. Therefore, in the present study, we tested and cross-sectionally evaluated outpatients on non-dialysis days, when the fluid balances were relatively stable. To assess intra-individual variability in the future, TCD echography should be performed regularly under similar conditions and changes over time should be evaluated if the same subjects do not suffer a stroke. We showed the ICA blood flow in more than fifty HD patients; the strength of the associations of ICA flow with ARBs that appeared from our study form a basis for conducting cohort and intervention studies. ## 5. Conclusions We successfully performed TCD Doppler measurements for ICA blood flow velocity despite severe atherosclerotic conditions in HD patients. Moreover, ARBs may have beneficial effects on brain perfusion, particularly in MCA, in HD patients. ## References 1. 1. The Japanese Society for Dialysis Therapy An Overview of Regular Dialysis Treatment in JapanThe Japanese Society for Dialysis TherapyTokyo, Japan2007. An Overview of Regular Dialysis Treatment in Japan (2007) 2. 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--- title: The Relationship Between Depression, Anxiety, and Stress Levels and Eating Behavior in Emergency Service Workers journal: Cureus year: 2023 pmcid: PMC10058381 doi: 10.7759/cureus.35504 license: CC BY 3.0 --- # The Relationship Between Depression, Anxiety, and Stress Levels and Eating Behavior in Emergency Service Workers ## Abstract Introduction It is seen that shift work causes various biological, psychological, and behavioral problems in individuals. This study aimed to determine the eating attitudes and behaviors of health workers working in shifts in a stressful environment such as the emergency service and to examine the relationship between depression, anxiety, and stress levels and eating behaviors (emotional eating, restrictive eating, and external eating) in terms of sociodemographic and clinical characteristics. Material and Methods Sociodemographic data form; Depression, Anxiety, and Stress Scale (DASS); and Dutch Eating Behavior Questionnaire (DEBQ) were used. The study sample consisted of 92 employees (doctor, nurse, emergency medical technician (EMT), medical secretary, and security, staff) who were actively on duty in the emergency department of Alanya Alaaddin Keykubat University Medical Faculty Training and Research Hospital. Results In our study, when the eating behavior of emergency service workers was evaluated in terms of "emotional, external, and restricted eating" sub-dimensions, depression ($$p \leq 0.043$$), anxiety ($$p \leq 0.017$$), increased stress levels ($$p \leq 0.002$$), being female ($$p \leq 0.022$$), nurse-emergency medical technician profession ($$p \leq 0.001$$), working in 24-hour shifts ($$p \leq 0.001$$), and diet history ($$p \leq 0.013$$) were associated with "emotional eating." In addition, an increase in depression levels ($$p \leq 0.048$$), being single ($$p \leq 0.015$$), working in 24-hour shifts ($$p \leq 0.005$$), a decrease in age ($p \leq 0.001$) with "extrinsic eating," an increase in body mass index (BMI) ($$p \leq 0.020$$) and waist circumference ($$p \leq 0.049$$), and diet history ($p \leq 0.001$) were associated with "restricted eating." Conclusions In our study, among the sociodemographic factors, being female, being single, working in 24-hour shifts, diet history, nurse-EMT profession, and undergraduate education level were found to increase the tendency to develop eating behavior problems. An increase in depression levels, being single, working in 24-hour shifts, and a decrease in age were associated with "extrinsic eating." There is a correlation between depression, anxiety, and stress scores and emotional eating scores. Additionally, we found significant correlations between body mass index, waist circumference, diet history, and restricted eating scores. In the approach to eating behavior problems, it is important to determine the individual eating behavior disorder. Due to the increased risk of eating behavior disorder in those who work in long shifts such as 24 hours, it will be possible to organize work programs and increase the quality of service. ## Introduction An important part of the factors that disrupt the physiological and psychological balance of individuals, causing stress, originates from work life [1]. Working in the emergency department requires being in contact with many patients with different conditions and their relatives and making the right clinical decisions, in a timely manner. Emergency health service employees work in shifts to provide 24-hour uninterrupted health service. Shift work can adversely affect the work and personal life of individuals by disrupting the health of individuals at various levels physiologically and psychologically [2]. It is reported that the shift work system causes both stress and a decrease in the skill levels of coping with stress [3]. Stressful work environments cause a wide variety of psychiatric problems. One of the most important problems that may occur due to shift work is changes in eating behavior and eating disorders [4]. Numerous studies investigating the relationship between stress and eating behavior have shown that stress is associated with changes in food intake in adults and children [4]. While the increase in glucocorticoids caused by acute stress may decrease hypothalamic-pituitary axis activity and eating, in the case of chronic stress, high glucocorticoids can increase food intake by acting as a stimulant. It has been reported that high levels of stress are associated with a number of binge-eating episodes and excessive weight gain [5]. It has been reported that stress affects the amount of food consumed and the selected food types [4], causing an increase in the consumption of unhealthy foods, especially those with high fat and sugar content [6]. Individuals use different coping methods to cope with the stressor. Emotional eating behavior can act as a coping mechanism for many. It is thought that those with emotional eating behavior are more likely to overeat under stress than those without emotional eating behavior [7]. In addition, it has been reported that individuals with emotional eating behavior increase, in response to stress factors, food cravings and the consumption of foods containing high carbohydrates and fats [7]. Depressive symptoms and anxiety symptoms, such as stress, are psychiatric conditions that are highly associated with changes in eating behavior such as the loss of appetite and overeating. A number of studies, using different instruments to measure emotional eating, have also demonstrated an association between binge eating and weight gain in response to negative emotions (depressed and anxious) [8]. Studies have shown that individuals with depressive symptoms generally have dysfunctional coping strategies and are prone to develop abnormal eating behaviors accompanied by episodes of binge eating to reduce negative mood states [8]. Disordered eating behavior refers to problematic eating behaviors such as binge eating or purging and restrictive eating that are less frequent and less severe than those required for a diagnosis of an eating disorder and may be a leading marker for an eating disorder diagnosis [9]. Impaired eating behaviors, other than eating disorders such as anorexia nervosa, bulimia, and binge eating, which can be diagnosed with direct signs and symptoms, can be ignored as a health problem. It is seen that shift work causes various biological, psychological, and behavioral problems in individuals. This study aimed to determine the eating attitudes and behaviors of health workers working in shifts in a stressful environment such as the emergency room and to examine the relationship between depression, anxiety, and stress levels and eating behaviors (emotional eating, restrictive eating, and external eating) in terms of sociodemographic and clinical characteristics. ## Materials and methods Study group Between November 2022 and December 2022, 98 employees (doctor, nurse, emergency medical technician (EMT), medical secretary, security staff, and nursing aide) were included in the study. Employers who were at least primary school graduates did not use psychotropic drugs for at least one month for any reason and gave written consent to participate in the study. They were actively on duty in the emergency department of Alanya Alaaddin Keykubat University Medical School. After giving informed consent, participants filled out the sociodemographic questionnaire; Depression, Anxiety, and Stress Scale (DASS); and Dutch Eating Behavior Questionnaire (DEBQ) [3]. Those who had difficulties in performing the tests applied in the study and had cognitive impairment to a degree that made it difficult to comply with the research guidelines, those who did not actively work in the emergency room during the study period, and those with alcohol and substance use disorders were excluded from the study. Six participants were excluded from the study (four due to antidepressant use and two for incomplete filling of the forms), and study was performed with 92 participants. All participants were informed about the research by the two expert psychiatrists who conducted the study, their written consent was obtained, and they were evaluated according to DSM-5 criteria, and Structured Clinical Interview for DSM-5 (SCID-5-CV) was administered [10], because of the exclusion of another psychiatric disease. Scales used in the research Sociodemographic Questionnaire It is a form created by researchers who question the demographic characteristics of the participants (age, gender, educational status, and marital status) and their characteristics such as body mass index (BMI), waist circumference, and diet history. DASS DASS is a self-report scale developed by Lovibond and Lovibond [1995] to assess participants' symptoms of depression, anxiety, and stress [11]. It consists of three subgroups (depression, anxiety, and stress) and contains a total of 21 items. The Turkish validity and reliability study of the scale was conducted by Sarıçam [2018] [12]. The Cronbach alpha coefficients of the subgroups of DASS-21, which have three factors, depression, anxiety, and stress, were determined as 0.84 for anxiety, 0.87 for depression, and 0.85 for stress. High scores obtained in the application of the scale indicate that the severity of the symptoms increases. DEBQ DEBQ is developed by Van Strien et al. [ 13], and the Turkish validity and reliability study of the questionnaire was conducted by Bozan et al. [ 2011] [14]. A questionnaire of 33 items, it consists of three subscales that assess emotional eating behaviors (e.g., do you eat sweets when you are unhappy?), external eating behaviors (e.g., do you eat more than you normally would if your food smells very good?), and restricted eating behaviors (e.g., do you eat less than you would like to not gain weight?). The items in the questionnaire are evaluated with a five-point Likert scale. Although the scale does not have a cutoff point, the high total scores reflect a negativity related to the eating behavior [13,14]. Ethics committee approval Ethics committee approval of the study was obtained from the Non-Interventional Clinical Research Ethics Committee of the Alanya Alaaddin Keykubat University Medical Faculty Training and Research Hospital, with the decision number of $\frac{2022}{10}$-03. An informed consent form was signed by all participants, and the study was conducted in accordance with the Declaration of Helsinki. Statistical analysis Descriptive Statistics Mean and standard deviation were used for normally distributed continuous variables and frequencies and percentages for interquartile range and categorical variables. To determine the normality of continuous variables, Shapiro-Wilk and Kolmogorov-Smirnov tests were used. For normally distributed independent variables, the difference between groups for DEBQ scores was compared with Student's t-test. For the comparison of DEBQ scores for professions, the one-way analysis of variance (ANOVA) test was performed, and the pairwise comparisons were performed with the post hoc Tukey-Tukey's B honestly significant difference (HSD) test. Tests for the correlation of DEBQ scores with DEBQ scores and other parameters were calculated by the partial correlation analysis and controlled for confounding variables. To evaluate all analyses, a $95\%$ confidence interval and a significance level of $p \leq 0.05$ were determined. The statistical analyses were made using the Statistical Package for Social Sciences (SPSS) 22.0 (IBM SPSS Statistics, Armonk, NY) software. ## Results The sociodemographic characteristics and clinical scale scores of the participants Of the 92 participants (mean age of 31.65±7.97), $42.4\%$ were female, and $57.6\%$ were male. Their average working time in the emergency department was 5.19±5.51 years, and their average monthly working time was 13.88±4.68 days. While the average body mass index of the participants was 25.64±4.70 kg/m2, the average waist circumference was 34.28±5.36 inches (Table 1). Table 1 \| Unnamed: 0 \| Unnamed: 1 \| n \| % \| \| --- \| --- \| --- \| --- \| \| Profession \| Medical Secretary \| 10 \| 10.9 \| \| Profession \| Emergency Medical Technician \| 5 \| 5.4 \| \| Profession \| Nurse \| 27 \| 29.3 \| \| Profession \| Physician \| 26 \| 28.3 \| \| Profession \| Security Staff \| 6 \| 6.5 \| \| Profession \| Nursing Aide \| 13 \| 14.1 \| \| Profession \| Others \| 5 \| 5.4 \| \| Sex \| Female \| 39 \| 42.4 \| \| Sex \| Male \| 53 \| 57.6 \| \| Education \| Primary School \| 2 \| 2.2 \| \| Education \| High School \| 15 \| 16.3 \| \| Education \| University \| 22 \| 23.9 \| \| Education \| Bachelor's Degree \| 53 \| 57.6 \| \| Marital Status \| Single \| 59 \| 64.1 \| \| Marital Status \| Married \| 32 \| 34.8 \| \| Marital Status \| Divorced/Widow \| 1 \| 1.1 \| \| Shift Type (Hour) \| 24 \| 61 \| 66.3 \| \| Shift Type (Hour) \| 8-16 \| 7 \| 7.6 \| \| Shift Type (Hour) \| 12-24 \| 22 \| 23.9 \| \| Shift Type (Hour) \| 16-8 \| 2 \| 2.2 \| \| Waist Circumference (cm) \| Waist Circumference (cm) \| 87.07 \| 13.61 \| \| Diet History \| No \| 47 \| 51.1 \| \| Diet History \| Yes \| 45 \| 48.9 \| \| Alcohol Consumption \| No \| 48 \| 52.2 \| \| Alcohol Consumption \| Yes \| 44 \| 47.8 \| \| Smoking \| No \| 37 \| 40.2 \| \| Smoking \| Yes \| 55 \| 59.8 \| \| \| \| Mean \| SD \| \| Age \| Age \| 31.65 \| 7.97 \| \| Body Mass Index (kg/m2) \| Body Mass Index (kg/m2) \| 25.64 \| 4.70 \| \| Working Duration in the Emergency Room (Year) \| Working Duration in the Emergency Room (Year) \| 5.19 \| 5.51 \| \| Average Working Duration per Month (Day) \| Average Working Duration per Month (Day) \| 13.88 \| 4.68 \| \| DASS Scale: Depression Score \| DASS Scale: Depression Score \| 6.55 \| 4.99 \| \| DASS Scale: Anxiety Score \| DASS Scale: Anxiety Score \| 4.04 \| 3.84 \| \| DASS Scale: Stress Score \| DASS Scale: Stress Score \| 6.60 \| 4.93 \| \| DASS Scale: Total Score \| DASS Scale: Total Score \| 17.20 \| 12.54 \| \| DEBQ: Restricted Eating Score \| DEBQ: Restricted Eating Score \| 23.90 \| 8.23 \| \| DEBQ: Emotional Eating Score \| DEBQ: Emotional Eating Score \| 27.27 \| 13.67 \| \| DEBQ: External Eating Score \| DEBQ: External Eating Score \| 31.71 \| 6.93 \| \| DEBQ: Total Score \| DEBQ: Total Score \| 82.47 \| 20.85 \| Comparison of Dutch Eating Behavior Questionnaire scores based on sociodemographic characteristics The DEBQ emotional eating scores (6.917, $$p \leq 0.022$$) and total scores (11.251, $$p \leq 0.010$$) were higher in females compared to males. The DEBQ total scores were (9.268, $$p \leq 0.034$$) higher in those with a bachelor's degree compared to those without. Comparing married participants, single participants had a higher external eating (4.006, $$p \leq 0.015$$) total score (9.246, $$p \leq 0.042$$). Emotional eating (9.070, $$p \leq 0.001$$), external eating (4.228, $$p \leq 0.005$$), and total DEBQ scores (12.770, $$p \leq 0.005$$) were higher in those who work 24-hour shifts, comparing to others. The DEBQ restricted eating scores (7.760, $p \leq 0.001$), emotional eating scores (7.080, $$p \leq 0.013$$), and total eating scores (17.659, $p \leq 0.001$) were higher in those with a diet history, compared to those without (Table 2). Table 2 \| DEBQ Scores and Sociodemographic Characteristics \| DEBQ Scores and Sociodemographic Characteristics.1 \| Mean \| SD \| Mean Difference \| 95% Confidence Interval \| 95% Confidence Interval.1 \| χ2 Value/Fisher \| p \| \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| \| DEBQ Scores and Sociodemographic Characteristics \| DEBQ Scores and Sociodemographic Characteristics \| Mean \| SD \| Mean Difference \| Lower Limit \| Upper Limit \| χ2 Value/Fisher \| p \| \| Restricted Eating Score \| Female \| 25.00 \| 9.24 \| 1.906 \| -1.675 \| 5.486 \| 4.288 \| 0.292 \| \| Restricted Eating Score \| Male \| 23.09 \| 7.39 \| 1.906 \| -1.675 \| 5.486 \| 4.288 \| 0.292 \| \| Emotional Eating Score \| Female \| 31.26 \| 15.59 \| 6.917 \| 1.041 \| 12.793 \| 5.154 \| 0.022 \| \| Emotional Eating Score \| Male \| 24.34 \| 11.34 \| 6.917 \| 1.041 \| 12.793 \| 5.154 \| 0.022 \| \| External Eating Score \| Female \| 32.69 \| 6.63 \| 1.711 \| -1.188 \| 4.610 \| 0.578 \| 0.244 \| \| External Eating Score \| Male \| 30.98 \| 7.11 \| 1.711 \| -1.188 \| 4.610 \| 0.578 \| 0.244 \| \| DEBQ Total Score \| Female \| 88.95 \| 20.99 \| 11.251 \| 2.784 \| 19.717 \| 0.398 \| 0.010 \| \| DEBQ Total Score \| Male \| 77.70 \| 19.60 \| 11.251 \| 2.784 \| 19.717 \| 0.398 \| 0.010 \| \| Restricted Eating Score \| Not University Graduate \| 22.46 \| 9.18 \| -2.501 \| -5.933 \| 0.932 \| 1.643 \| 0.151 \| \| Restricted Eating Score \| University Graduate \| 24.96 \| 7.37 \| -2.501 \| -5.933 \| 0.932 \| 1.643 \| 0.151 \| \| Emotional Eating Score \| Not University Graduate \| 24.95 \| 14.88 \| -4.032 \| -9.731 \| 1.666 \| 1.206 \| 0.163 \| \| Emotional Eating Score \| University Graduate \| 28.98 \| 12.56 \| -4.032 \| -9.731 \| 1.666 \| 1.206 \| 0.163 \| \| External Eating Score \| Not University Graduate \| 30.13 \| 7.24 \| -2.740 \| -5.604 \| 0.124 \| 1.040 \| 0.061 \| \| External Eating Score \| University Graduate \| 32.87 \| 6.51 \| -2.740 \| -5.604 \| 0.124 \| 1.040 \| 0.061 \| \| DEBQ Total Score \| Not University Graduate \| 77.13 \| 21.54 \| -9.268 \| -17.840 \| -0.696 \| 0.417 \| 0.034 \| \| DEBQ Total Score \| University Graduate \| 86.40 \| 19.61 \| -9.268 \| -17.840 \| -0.696 \| 0.417 \| 0.034 \| \| Restricted Eating Score \| Single \| 24.50 \| 8.21 \| 1.719 \| -1.866 \| 5.303 \| 0.115 \| 0.343 \| \| Restricted Eating Score \| Married \| 22.78 \| 8.29 \| 1.719 \| -1.866 \| 5.303 \| 0.115 \| 0.343 \| \| Emotional Eating Score \| Single \| 28.43 \| 12.50 \| 3.340 \| -2.597 \| 9.276 \| 1.746 \| 0.267 \| \| Emotional Eating Score \| Married \| 25.09 \| 15.60 \| 3.340 \| -2.597 \| 9.276 \| 1.746 \| 0.267 \| \| External Eating Score \| Single \| 33.10 \| 6.02 \| 4.006 \| 0.824 \| 7.189 \| 4.115 \| 0.015 \| \| External Eating Score \| Married \| 29.09 \| 7.81 \| 4.006 \| 0.824 \| 7.189 \| 4.115 \| 0.015 \| \| DEBQ Total Score \| Single \| 85.68 \| 18.96 \| 9.246 \| 0.335 \| 18.157 \| 1.966 \| 0.042 \| \| DEBQ Total Score \| Married \| 76.44 \| 23.11 \| 9.246 \| 0.335 \| 18.157 \| 1.966 \| 0.042 \| \| Restricted Eating Score \| Others \| 23.29 \| 9.14 \| \| 20.10 \| 26.48 \| 0.146 \| 0.865 \| \| Restricted Eating Score \| Nurse-EMT \| 24.31 \| 8.51 \| \| 21.24 \| 27.38 \| 0.146 \| 0.865 \| \| Restricted Eating Score \| Physician \| 24.19 \| 6.79 \| \| 21.45 \| 26.94 \| 0.146 \| 0.865 \| \| Emotional Eating Score \| Others \| 21.24 \| 9.10 \| \| 18.06 \| 24.41 \| 6.919 \| 0.002 \| \| Emotional Eating Score \| Nurse-EMT \| 32.94 \| 16.28 \| \| 27.07 \| 38.81 \| 6.919 \| 0.002 \| \| Emotional Eating Score \| Physician \| 28.19 \| 12.26 \| \| 23.24 \| 33.14 \| 6.919 \| 0.002 \| \| External Eating Score \| Others \| 29.35 \| 6.84 \| \| 26.97 \| 31.74 \| 3.287 \| 0.042 \| \| External Eating Score \| Nurse-EMT \| 33.25 \| 6.04 \| \| 31.07 \| 35.43 \| 3.287 \| 0.042 \| \| External Eating Score \| Physician \| 32.88 \| 7.46 \| \| 29.87 \| 35.90 \| 3.287 \| 0.042 \| \| DEBQ Total Score \| Others \| 73.38 \| 17.47 \| \| 67.29 \| 79.48 \| 6.398 \| 0.003 \| \| DEBQ Total Score \| Nurse-EMT \| 90.50 \| 22.54 \| \| 82.37 \| 98.63 \| 6.398 \| 0.003 \| \| DEBQ Total Score \| Physician \| 84.46 \| 18.73 \| \| 76.90 \| 92.03 \| 6.398 \| 0.003 \| \| Restricted Eating Score \| 24-hour shift \| 23.67 \| 7.60 \| -0.683 \| -4.310 \| 2.945 \| 0.586 \| 0.709 \| \| Restricted Eating Score \| Others \| 24.35 \| 9.48 \| -0.683 \| -4.310 \| 2.945 \| 0.586 \| 0.709 \| \| Emotional Eating Score \| 24-hour shift \| 30.33 \| 14.45 \| 9.070 \| 4.032 \| 14.107 \| 4.381 \| 0.001 \| \| Emotional Eating Score \| Others \| 21.26 \| 9.63 \| 9.070 \| 4.032 \| 14.107 \| 4.381 \| 0.001 \| \| External Eating Score \| 24-hour shift \| 33.13 \| 6.93 \| 4.228 \| 1.305 \| 7.151 \| 0.249 \| 0.005 \| \| External Eating Score \| Others \| 28.90 \| 6.10 \| 4.228 \| 1.305 \| 7.151 \| 0.249 \| 0.005 \| \| DEBQ Total Score \| 24-hour shift \| 86.77 \| 21.05 \| 12.770 \| 3.980 \| 21.561 \| 0.971 \| 0.005 \| \| DEBQ Total Score \| Others \| 74.00 \| 17.90 \| 12.770 \| 3.980 \| 21.561 \| 0.971 \| 0.005 \| \| Restricted Eating Score \| No Diet History \| 20.11 \| 7.29 \| -7.760 \| -10.784 \| -4.737 \| 0.001 \| <0.001 \| \| Restricted Eating Score \| Diet History \| 27.87 \| 7.29 \| -7.760 \| -10.784 \| -4.737 \| 0.001 \| <0.001 \| \| Emotional Eating Score \| No Diet History \| 23.81 \| 11.09 \| -7.080 \| -12.626 \| -1.535 \| 5.541 \| 0.013 \| \| Emotional Eating Score \| Diet History \| 30.89 \| 15.22 \| -7.080 \| -12.626 \| -1.535 \| 5.541 \| 0.013 \| \| External Eating Score \| No Diet History \| 30.72 \| 6.45 \| -2.010 \| -4.867 \| 0.847 \| 0.991 \| 0.166 \| \| External Eating Score \| Diet History \| 32.73 \| 7.32 \| -2.010 \| -4.867 \| 0.847 \| 0.991 \| 0.166 \| \| DEBQ Total Score \| No Diet History \| 73.83 \| 16.83 \| -17.659 \| -25.521 \| -9.797 \| 2.783 \| <0.001 \| \| DEBQ Total Score \| Diet History \| 91.49 \| 20.98 \| -17.659 \| -25.521 \| -9.797 \| 2.783 \| <0.001 \| \| Restricted Eating Score \| No Alcohol \| 22.69 \| 8.73 \| -2.540 \| -5.933 \| 0.854 \| 0.708 \| 0.141 \| \| Restricted Eating Score \| Alcohol \| 25.23 \| 7.53 \| -2.540 \| -5.933 \| 0.854 \| 0.708 \| 0.141 \| \| Emotional Eating Score \| No Alcohol \| 26.27 \| 15.03 \| -2.093 \| -7.775 \| 3.590 \| 2.338 \| 0.466 \| \| Emotional Eating Score \| Alcohol \| 28.36 \| 12.08 \| -2.093 \| -7.775 \| 3.590 \| 2.338 \| 0.466 \| \| External Eating Score \| No Alcohol \| 31.13 \| 6.88 \| -1.216 \| -4.094 \| 1.663 \| 0.072 \| 0.404 \| \| External Eating Score \| Alcohol \| 32.34 \| 7.00 \| -1.216 \| -4.094 \| 1.663 \| 0.072 \| 0.404 \| \| DEBQ Total Score \| No Alcohol \| 79.29 \| 21.91 \| -6.640 \| -15.223 \| 1.942 \| 0.700 \| 0.128 \| \| DEBQ Total Score \| Alcohol \| 85.93 \| 19.28 \| -6.640 \| -15.223 \| 1.942 \| 0.700 \| 0.128 \| \| Restricted Eating Score \| Nonsmoker \| 23.41 \| 9.11 \| -0.831 \| -4.326 \| 2.664 \| 3.580 \| 0.638 \| \| Restricted Eating Score \| Smoker \| 24.24 \| 7.66 \| -0.831 \| -4.326 \| 2.664 \| 3.580 \| 0.638 \| \| Emotional Eating Score \| Nonsmoker \| 28.95 \| 15.22 \| 2.800 \| -2.976 \| 8.577 \| 2.800 \| 0.338 \| \| Emotional Eating Score \| Smoker \| 26.15 \| 12.53 \| 2.800 \| -2.976 \| 8.577 \| 2.800 \| 0.338 \| \| External Eating Score \| Nonsmoker \| 32.92 \| 6.88 \| 2.028 \| -0.885 \| 4.941 \| 0.031 \| 0.170 \| \| External Eating Score \| Smoker \| 30.89 \| 6.90 \| 2.028 \| -0.885 \| 4.941 \| 0.031 \| 0.170 \| \| DEBQ Total Score \| Nonsmoker \| 84.81 \| 23.89 \| 3.920 \| -5.389 \| 13.229 \| 4.065 \| 0.403 \| \| DEBQ Total Score \| Smoker \| 80.89 \| 18.60 \| 3.920 \| -5.389 \| 13.229 \| 4.065 \| 0.403 \| Comparison of Dutch Eating Behavior Questionnaire scores based on professions The DEBQ emotional eating score ($$p \leq 0.002$$), external eating score ($$p \leq 0.042$$), and total scores ($$p \leq 0.003$$) of the participants who were divided into three groups as nurse-emergency medical technician, doctor, and other emergency service workers (security, staff, and secretary) were significantly different. In order to determine which groups have difference, the statistical significance level was reduced to p≤0.017, and the pairwise comparisons were performed with the post hoc Tukey-Tukey's B HSD test (Table 3). Emotional eating scores (11.702, $$p \leq 0.001$$) and DEBQ total scores (17.118, $$p \leq 0.002$$) were higher in nurse-emergency medical technician group compared to other emergency service personnel. Table 3 \| Clinical Scale Scores \| Professions \| Unnamed: 2 \| Mean Difference \| SE \| 95% CI \| 95% CI.1 \| p \| \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| \| Clinical Scale Scores \| Professions \| \| Mean Difference \| SE \| Lower Limit \| Upper Limit \| p \| \| DEBQ Restricted Eating Score \| Others \| Nurse-EMT \| -1.018 \| 2.048 \| -6.76 \| 4.72 \| 0.873 \| \| DEBQ Restricted Eating Score \| Others \| Doctor \| -0.898 \| 2.167 \| -6.97 \| 5.17 \| 0.910 \| \| DEBQ Restricted Eating Score \| Nurse-EMT \| Others \| 1.018 \| 2.048 \| -4.72 \| 6.76 \| 0.873 \| \| DEBQ Restricted Eating Score \| Nurse-EMT \| Physician \| 0.120 \| 2.196 \| -6.03 \| 6.27 \| 0.998 \| \| DEBQ Restricted Eating Score \| Physician \| Others \| 2.167 \| 2.167 \| -5.17 \| 6.97 \| 0.910 \| \| DEBQ Restricted Eating Score \| Physician \| Nurse-EMT \| 2.196 \| 2.196 \| -6.27 \| 6.03 \| 0.998 \| \| DEBQ Emotional Eating Score \| Others \| Nurse-EMT \| -11.702 \| 3.167 \| -20.58 \| -2.83 \| 0.001 \| \| DEBQ Emotional Eating Score \| Others \| Physician \| -6.957 \| 3.350 \| -16.34 \| 2.43 \| 0.101 \| \| DEBQ Emotional Eating Score \| Nurse-EMT \| Others \| 11.702 \| 3.167 \| 2.83 \| 20.58 \| 0.001 \| \| DEBQ Emotional Eating Score \| Nurse-EMT \| Physician \| 4.745 \| 3.395 \| -4.77 \| 14.26 \| 0.346 \| \| DEBQ Emotional Eating Score \| Physician \| Others \| 6.957 \| 3.350 \| -2.43 \| 16.34 \| 0.101 \| \| DEBQ Emotional Eating Score \| Physician \| Nurse-EMT \| -4.745 \| 3.395 \| -14.26 \| 4.77 \| 0.346 \| \| DEBQ External Eating Score \| Others \| Nurse-EMT \| -3.897 \| 1.666 \| -8.56 \| 0.77 \| 0.056 \| \| DEBQ External Eating Score \| Others \| Physician \| -3.532 \| 1.762 \| -8.47 \| 1.40 \| 0.117 \| \| DEBQ External Eating Score \| Nurse-EMT \| Others \| 3.897 \| 1.666 \| -0.77 \| 8.56 \| 0.056 \| \| DEBQ External Eating Score \| Nurse-EMT \| Physician \| 0.365 \| 1.786 \| -4.64 \| 5.37 \| 0.977 \| \| DEBQ External Eating Score \| Physician \| Others \| 3.532 \| 1.762 \| -1.40 \| 8.47 \| 0.117 \| \| DEBQ External Eating Score \| Physician \| Nurse-EMT \| -0.365 \| 1.786 \| -5.37 \| 4.64 \| 0.977 \| \| DEBQ Total Score \| Others \| Nurse-EMT \| -17.118 \| 4.856 \| -30.72 \| -3.51 \| 0.002 \| \| DEBQ Total Score \| Others \| Physician \| -11.079 \| 5.137 \| -25.47 \| 3.31 \| 0.084 \| \| DEBQ Total Score \| Nurse-EMT \| Others \| 17.118 \| 4.856 \| 3.51 \| 30.72 \| 0.002 \| \| DEBQ Total Score \| Nurse-EMT \| Physician \| 6.038 \| 5.206 \| -8.55 \| 20.62 \| 0.480 \| \| DEBQ Total Score \| Physician \| Others \| 11.079 \| 5.137 \| -3.31 \| 25.47 \| 0.084 \| \| DEBQ Total Score \| Physician \| Nurse-EMT \| -6.038 \| 5.206 \| -20.62 \| 8.55 \| 0.480 \| Correlation of Depression, Anxiety, and Stress Scale scores with Dutch Eating Behavior Questionnaire scores DASS depression scores were positively correlated with DEBQ emotional eating scores ($r = 0.194$ and $$p \leq 0.070$$) and external eating scores ($r = 0.219$ and $$p \leq 0.041$$). DASS anxiety scores were positively correlated with DEBQ emotional eating scores ($r = 0.245$ and $$p \leq 0.021$$) and DEBQ total scores ($r = 0.245$ and $$p \leq 0.021$$). DAS stress scores show a positive correlation with DEBQ emotional eating scores at the level of $r = 0.316$, positively ($$p \leq 0.002$$), and with DEBQ total scores at a level of $r = 0.319$ ($$p \leq 0.002$$). DASS total scores were positively correlated with DEBQ emotional eating scores ($r = 0.277$ and $$p \leq 0.009$$) and DEBQ total scores by ($r = 0.272$ and $$p \leq 0.010$$) (Table 4). Table 4 \| Unnamed: 0 \| Unnamed: 1 \| DASS Depression Score \| DASS Anxiety Score \| DASS Stress Score \| DASS Total Score \| Restricted Eating Score \| Emotional Eating Score \| External Eating Score \| \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| \| DASS Depression Score \| r \| 1.0 \| \| \| \| \| \| \| \| DASS Depression Score \| p \| \| \| \| \| \| \| \| \| DASS Anxiety Score \| r \| 0.693 \| 1.0 \| \| \| \| \| \| \| DASS Anxiety Score \| p \| 0.0 \| \| \| \| \| \| \| \| DASS Stress Score \| r \| 0.791 \| 0.712 \| 1.0 \| \| \| \| \| \| DASS Stress Score \| p \| 0.0 \| 0.0 \| \| \| \| \| \| \| DASS Total Score \| r \| 0.922 \| 0.866 \| 0.929 \| 1.0 \| \| \| \| \| DASS Total Score \| p \| 0.0 \| 0.0 \| 0.0 \| \| \| \| \| \| DEBQ Restricted Eating Score \| r \| -0.008 \| 0.162 \| 0.126 \| 0.097 \| 1.0 \| \| \| \| DEBQ Restricted Eating Score \| p \| 0.945 \| 0.131 \| 0.242 \| 0.368 \| \| \| \| \| DEBQ Emotional Eating Score \| r \| 0.194 \| 0.245 \| 0.316 \| 0.277 \| 0.29 \| 1.0 \| \| \| DEBQ Emotional Eating Score \| p \| 0.07 \| 0.021 \| 0.003 \| 0.009 \| 0.006 \| \| \| \| DEBQ External Eating Score \| r \| 0.219 \| 0.09 \| 0.175 \| 0.183 \| -0.014 \| 0.335 \| 1.0 \| \| DEBQ External Eating Score \| p \| 0.041 \| 0.405 \| 0.103 \| 0.087 \| 0.895 \| 0.001 \| \| \| DEBQ Total Score \| r \| 0.176 \| 0.245 \| 0.319 \| 0.272 \| 0.587 \| 0.88 \| 0.531 \| \| DEBQ Total Score \| p \| 0.1 \| 0.021 \| 0.002 \| 0.01 \| 0.0 \| 0.0 \| 0.0 \| Correlation of anthropometric and work characteristics with Dutch Eating Behavior Questionnaire scores Age shows a negative correlation with DEBQ external eating scores (-0.428, $$p \leq 0.000$$). Body mass index shows a positive correlation with DEBQ restricted eating scores ($r = 0.284$ and $$p \leq 0.008$$). Waist circumference was positively correlated with DEBQ restricted eating scores ($r = 0.271$ and $$p \leq 0.011$$) (Table 5). Table 5 \| Unnamed: 0 \| Unnamed: 1 \| DEBQ Restricted Eating Score \| DEBQ Emotional Eating Score \| DEBQ External Eating Score \| Age \| Working Duration in the Emergency Room (Year) \| Average Working Duration per Month (Day) \| Body Mass Index (BMI) \| Waist Circumference \| \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| \| DEBQ Restricted Eating Score \| r \| 1.0 \| \| \| \| \| \| \| \| \| DEBQ Restricted Eating Score \| p \| \| \| \| \| \| \| \| \| \| DEBQ Emotional Eating Score \| r \| 0.201 \| 1.0 \| \| \| \| \| \| \| \| DEBQ Emotional Eating Score \| p \| 0.061 \| \| \| \| \| \| \| \| \| DEBQ External Eating Score \| r \| -0.053 \| 0.37 \| 1.0 \| \| \| \| \| \| \| DEBQ External Eating Score \| p \| 0.628 \| 0.0 \| \| \| \| \| \| \| \| Age \| r \| 0.106 \| -0.156 \| -0.428 \| 1.0 \| \| \| \| \| \| Age \| p \| 0.329 \| 0.15 \| 0.0 \| \| \| \| \| \| \| Working Duration in the Emergency Room (Year) \| r \| -0.089 \| -0.013 \| -0.229 \| 0.651 \| 1.0 \| \| \| \| \| Working Duration in the Emergency Room (Year) \| p \| 0.411 \| 0.906 \| 0.033 \| 0.0 \| \| \| \| \| \| Average Working Duration per Month (Day) \| r \| -0.019 \| -0.235 \| -0.151 \| 0.159 \| 0.031 \| 1.0 \| \| \| \| Average Working Duration per Month (Day) \| p \| 0.859 \| 0.028 \| 0.163 \| 0.141 \| 0.775 \| \| \| \| \| Body Mass Index (BMI) \| r \| 0.284 \| 0.05 \| -0.113 \| 0.114 \| 0.183 \| 0.02 \| 1.0 \| \| \| Body Mass Index (BMI) \| p \| 0.008 \| 0.644 \| 0.299 \| 0.293 \| 0.09 \| 0.856 \| \| \| \| Waist Circumference \| r \| 0.271 \| -0.082 \| -0.196 \| 0.209 \| 0.194 \| 0.051 \| 0.879 \| 1.0 \| \| Waist Circumference \| p \| 0.011 \| 0.448 \| 0.069 \| 0.052 \| 0.072 \| 0.639 \| 0.0 \| \| \| DEBQ Total Score \| r \| 0.513 \| 0.871 \| 0.575 \| -0.202 \| -0.103 \| -0.216 \| 0.098 \| -0.022 \| \| DEBQ Total Score \| p \| 0.0 \| 0.0 \| 0.0 \| 0.061 \| 0.344 \| 0.045 \| 0.364 \| 0.839 \| ## Discussion In our study, we found that females, singles, those with a bachelor's degree, nurses and emergency medical technician group, those who worked in 24-hour shifts, and those with a history of diet had higher DEBQ total scores. On the other hand, restricted eating scores were high for only the ones with a history of diet, which are single participants and those who worked in 24-hour shifts. In addition, while there was a significant positive relationship between restricted eating scores and body mass index and waist circumference, a significant negative relationship was found between age and extrinsic eating scores. When the relationship between depression, anxiety, and stress levels and eating behavior is evaluated, a positive and significant relationship was found between DASS total scores and DEBQ total scores. Similar to our results, it has been shown in many studies that emotional eating is more common in females than in males [15]. Also, there are studies showing that being slim in females is idealized due to factors such as social environment and media, and this can facilitate the development of eating behavior disorders; also, emotion-focused coping styles that females use more can cause eating disorders such as impaired eating behavior and binge-eating disorder [16]. Our results show that female employees working in a stressful environment such as the emergency room have a greater risk of developing eating behavior disorders compared to male colleagues. In our study, external eating scores and total eating scores were higher in single participants compared to married ones. In the study by Bussolotti et al., who reported that being married is a negative feature for eating disorders, it was reported that interpersonal functionality should be considered rather than being married or single in the development of eating disorders [17]. In our study, higher eating scores were determined in participants with undergraduate education compared to participants with undergraduate education level. Participants who had a bachelor's degree had higher eating scores compared to participants with a lower degree of education. However, we did not find any difference when comparing the subgroups (emotional, external, and restricted eating) with each other. In the study by Ulusoy [2022] conducted in Turkey, it was reported that the emotional eating scores of individuals with university and higher graduate degrees were higher than the participants with lower degrees of education [18]. In the study by Gökensel-Okta et al. [ 2022], higher restricted eating scores were reported in university graduates than in high school and secondary school graduates [19]. Sample selection can be the reason for the different results of these studies. Also, a limitation of our study is the fact that most of the participants in our study had a bachelor's degree may have affected our results and the generalizability of the study. In our study, emotional eating, external eating, and total eating scores were found to be higher in emergency service workers who work in "24-hour" shifts. Studies have reported that shift workers tend to eat more meals and snacks later in the day and consume more calories and fat, including sweets, sugary drinks, and low-fiber foods, in their diets [20]. In our study, emotional eating and total eating scores were higher in nurses and emergency medical technicians compared to other participants. Similar to our study results, a cross-sectional study of Canadian nurses working in shifts reported an increase in the frequency of snack consumption and eating behavior problems [21]. The work environment can be an important consideration when assessing the impact of diet on health outcomes in a shift worker population. It has been reported that nurses change their diet regimens, especially after they start working in shifts [22]. In our study also, we found that especially, nurses have a more tendency to develop eating disorders among emergency service workers. Studies done in different countries investigating the relationship between age and eating behavior show that restricted eating behavior [23] and emotional eating behavior decrease with age [24]. In our study, we found that external eating decreases with age. In a study conducted in Spain, consistent with our study results, the only eating behavior associated with age was external eating, which decrease with age [25]. Our results suggest that individuals tend to prefer healthy foods rather than external characteristics such as appearance and smell in their nutritional preferences as they get older. In the absence of alternative behaviors, eating can be considered as a natural reward or satisfaction habit in order to cope with negative emotions. In our study, we show that there is a correlation between depression, anxiety, and stress scores and emotional eating scores. Emotional eating has been associated with depressive symptoms, particularly atypical depression [26]. Unlike depressive disorders accompanied by the loss of appetite, depression with atypical features is characterized by increased appetite, which can lead to weight gain [10]. Individuals with atypical depression tend to develop abnormal eating behaviors such as emotional eating, that is, overeating in response to negative emotions. In their study, Ozier et al. reported that emotional eating may be a mediating factor between depression and body mass index [26]. Contrary to these studies, no relationship was found between body mass index and emotional eating in our study. In our study, the mean BMI of the participants was close to normal (25.64±4.70), and our results are in line with the study by Geliebter and Aversa, who reported that individuals with a BMI below 25 kg/m2 reduced their food intake in negative emotional states while individuals with a BMI above 25 kg/m2 increased their food intake [27]. In our study, a significant correlation was found between body mass index, waist circumference, diet history, and restricted eating scores. Obesity, which is the most basic findings of an increase in body mass index and waist circumference, is a health problem often accompanied by depression and anxiety, as well as psychological eating patterns such as emotional eating, addictive eating behaviors, and binge eating. Studies in the literature mostly focus on the relationship between emotional eating and obesity. The results of our study indicate that restricted eating may also be associated with obesity. Studies have reported that dietary restriction may be the most important predictor of overeating during stress [28]. In our study, emotional eating, restricted eating, and total eating scores were found to be higher in emergency service workers with a diet history, which is consistent with the literature. In situations where changes in eating habits are observed under stressful conditions, behavioral patterns have been shown to occur in two opposite ways. In situations where stress is experienced chronically, a person may increase food intake in response to stress, which can lead to weight gain or decreased food intake, which can lead to weight loss [29]. There is no clear consensus in the literature as to whether stress leads to increased or decreased calorie intake, but it seems likely that stress is associated with changes in food choice, such as higher-calorie desserts and fatty foods [30]. In their study investigating the relationship between stress and eating behavior, Snoek et al. found strong evidence showing a decrease in the consumption of vegetables at main meals and an increase in the consumption of high-calorie snack foods between meals in individuals with higher stress levels [30]. In our study, stress scores were correlated with emotional eating and total eating scores, in line with the literature. Well-being trainings to be given to individuals working in the emergency department to cope with stress will contribute significantly to the reduction of the tendency to develop eating behavior problems and eating disorders in this specific group. Strength and limitation Our study has a small sample size and was conducted in one center only, which complicates the generalizability of our results. Future studies with larger sample sizes including multiple centers are necessary in this field. To the best of our knowledge, our study is the first article to evaluate primary eating behaviors and related factors in emergency service workers in our country. The fact that our study examined eating behavior problems in a specific sample group, such as emergency service workers, rather than the general population constitutes one of the unique aspects of our study. Another strength of our study is that emergency workers who are actively on duty were included in the study, and all participants were evaluated by two psychiatrists. ## Conclusions In our study, among the sociodemographic factors, being female, being single, working in 24-hour shifts, diet history, nurse-EMT profession, and undergraduate education level were found to increase the tendency to develop eating behavior problems. At the same time, when evaluated in terms of "emotional, external, and restricted eating" sub-dimensions, being a female, nurse-EMT profession, working in 24-hour shifts, and diet history show a relationship with "emotional eating." An increase in depression levels, being single, working in 24-hour shifts, and a decrease in age were associated with "extrinsic eating." There is a correlation between depression, anxiety, and stress scores and emotional eating scores. Additionally, we found significant correlations between body mass index, waist circumference, diet history, and restricted eating scores. Restricted eating may also be associated with obesity. In the approach to eating behavior problems, it is important to determine the individual eating behavior disorder. Due to the increased risk of eating behavior disorder in those who work in long shifts such as 24 hours, it will be possible to organize work programs and increase the quality of service. ## References 1. 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--- title: Dietary Supplement, Containing the Dry Extract of Curcumin, Emblica and Cassia, Counteracts Intestinal Inflammation and Enteric Dysmotility Associated with Obesity authors: - Vanessa D’Antongiovanni - Matteo Fornai - Laura Benvenuti - Clelia Di Salvo - Carolina Pellegrini - Federica Cappelli - Stefano Masi - Luca Antonioli journal: Metabolites year: 2023 pmcid: PMC10058382 doi: 10.3390/metabo13030410 license: CC BY 4.0 --- # Dietary Supplement, Containing the Dry Extract of Curcumin, Emblica and Cassia, Counteracts Intestinal Inflammation and Enteric Dysmotility Associated with Obesity ## Abstract Intestinal epithelial barrier (IEB) impairment and enteric inflammation are involved in the onset of obesity and gut-related dysmotility. Dietary supplementation with natural plant extracts represents a useful strategy for the management of body weight gain and systemic inflammation associated with obesity. Here, we evaluate the efficacy of a food supplement containing the dry extract of Curcumin, Emblica and Cassia in counteracting enteric inflammation and motor abnormalities in a mouse model of obesity, induced by a high-fat diet (HFD). Male C57BL/6 mice, fed with standard diet (SD) or HFD, were treated with a natural mixture (Curcumin, Emblica and Cassia). After 8 weeks, body weight, BMI, liver and spleen weight, along with metabolic parameters and colonic motor activity were evaluated. Additionally, plasma LBP, fecal calprotectin, colonic levels of MPO and IL-1β, as well as the expression of occludin, TLR-4, MYD88 and NF-κB were investigated. Plant-based food supplement administration [1] counteracted the increase in body weight, BMI and metabolic parameters, along with a reduction in spleen and liver weight; [2] showed strengthening effects on the IEB integrity; and [3] reduced enteric inflammation and oxidative stress, as well as ameliorated the colonic contractile dysfunctions. Natural mixture administration reduced intestinal inflammation and counteracted the intestinal motor dysfunction associated with obesity. ## 1. Introduction Obesity is a pathological condition characterized as excessive fat accumulation, resulting from an imbalance between energy intake and its consumption [1]. At present, obesity represents a public health problem for its involvement in multiple chronic diseases, such as type 2 diabetes, hypertension and cardiovascular diseases [1,2]. In addition, obesity is often associated with digestive disturbances, including infrequent bowel movements and constipation, which negatively impact the patients’ quality of life and complicate their clinical management [3]. Several lines of evidence well demonstrated that the presence of a low-grade systemic inflammation, commonly defined as “meta-inflammation”, resulting from increased pro-inflammatory cytokine and chemokine secretion from adipocytes and adipose tissue-associated macrophages, seems to contribute to the impairment of insulin signaling, immune function and lipid metabolism, as well as a remarkable morphofunctional remodelling of the enteric neuromuscular compartment, resulting in bowel motor dysfunctions [2,4,5]. In particular, pre-clinical studies on high-fat diet (HFD)-fed mice showed that alterations in intestinal microbiota composition and the presence of an increased intestinal permeability represent among the main factors influencing early inflammatory events associated with obesity and metabolic dysfunction [6,7,8]. Indeed, the presence of an imbalanced gut microbiota composition has been reported to elicit fluctuations in the intestinal epithelial barrier (IEB) integrity, thus facilitating the translocation of immunogenic products (i.e., lipopolysaccharide (LPS), whole bacteria and other toxins) into the mucosa and the bloodstream, triggering the onset and maintenance of a meta-inflammation that is typically observed in obese patients [9,10,11]. Of note, the chronicization of such inflammatory conditions has an impact on the physiological functions of different organs, thus contributing to the development of several comorbidities associated with obesity [5]. At present, the pharmacological tools aimed at managing obesity and related comorbidities are not satisfactory in terms of efficacy, safety and long-lasting weight loss. In this regard, pre-clinical and clinical studies have focused their attention on the potential beneficial effects of natural derivates, such as crude extracts and products isolated from plants, as a viable way to manage obesity and related disorders. In recent years, several in vivo studies performed on a murine model of diet-induced obesity showed that dietary supplementation with natural drugs, such as Curcumin, Emblica and Cassia, might exert anti-obesity activity, counteracting body weight gain and systemic inflammation associated with obesity [12,13,14]. Of note, current studies on the putative beneficial effects of natural products supplementation on intestinal functional disorders and enteric inflammation associated with obesity are lacking. Therefore, the present research project was designed to assess the effect of a dietary supplement, containing the dry extract of Curcumin, Emblica and Cassia, in preventing and counteracting the intestinal motor dysfunction and the onset of enteric inflammation in a mouse model of diet-induced obesity. ## 2.1. Animals Five-week-old C57BL/6 male mice (body weight: 20–22 g) were provided by ENVIGO S.r.l (San Pietro al Natisone UD, Italy) and used during all the study’s procedures. Animals were divided into groups of five in cages in a climate-controlled environment, with a 12-h light cycle, at 22–24 °C and 50–$60\%$ humidity, and they were not used for at least a week. All experimental procedures involving mice were carried out following the Declaration of Helsinki, the EU Regulation $\frac{2010}{63}$/EU for animal experimentation, and the European Community Council Directive $\frac{86}{609}$, as well as the International Medical Association’s Code of Ethics. The University of Pisa’s Ethics Council for Animal Experimentation and the Italian Ministry of Health have both given their approval for the studies (Authorization No. $\frac{987}{2020}$-PR). All efforts to reduce and minimize the number of animals and their suffering were carried out. Animal studies are reported in compliance with the ARRIVE [15]. Animals were distributed randomly across groups to create groups of the same size. ## 2.2. Animal Model of Diet-Induced Obesity and Experimental Design To induce the obesity, for 8 weeks, mice were fed with HFD ($60\%$ calories from fat) or standard diet (SD, $18\%$ calories from fat). HFD diet included $18.3\%$ kcal from proteins, $21.4\%$ kcal from carbohydrates and $60.8\%$ kcal from fat, whereas SD provided $24\%$ kcal from proteins, $18\%$ kcal from fat and $58\%$ kcal from carbohydrates. Animals were randomly divided into ten groups, each composed of ten mice as follow: SD or HFD plus vehicle for a total of 8 weeks (treatment 4 + 4 weeks), SD or HFD treated with food supplement containing three plants (Curcuma longa—$46\%$ w/v; Cassia mimosoides var. Nomame—$15.5\%$ w/v; and Phyllanthus emblica—$15.5\%$ w/v) starting from the fifth week (treatment 4 + 4 weeks), and SD or HFD plus each individual component of food supplement starting from the fifth week (treatment 4 + 4 weeks). Dietary supplement and each plant contained in the supplement were administered via oral gavage at the following doses: dietary supplement—107 mg/Kg/die; Curcuma longa (Curcuma L.)—49 mg/Kg/die; Cassia mimosoides var. Nomame (Cassia M.)—16 mg/Kg/die; and Phyllanthus emblica (P. emblica)—16 mg/Kg/die. The natural mixture and each individual components were provided by Snep S.p. A, Pisa, Italy. Starting from the first day of the study, body weight was recorded once a week. At the end of the study, the animals were anaesthetized and sacrificed. Blood samples and tissue samples were collected and then stored at −80 °C for the following analyses. ## 2.3. Measurement of Body Mass Index and Evaluation of Metabolic Parameters Body mass index (BMI) was calculated as body weight (g) divided by body length (mm) squared (BMI = body weight/body length2), as described by Smemo et al. [ 16]. Blood samples were obtained from the tail vein the day of sacrifice, after an overnight fast. Glycated hemoglobin (HbA1c), cholesterol and triglycerides were evaluated using the Multicare Insensor (BSI Srl; Arezzo, Italy), following manufacturer’s instructions [17]. ## 2.4. Recording of Colonic Contractile Activity The contractile activity of colonic longitudinal smooth muscle preparations was recorded, as previously reported [18], with minor changes. Following sacrifice, by making an incision above the anal end, the colon was promptly removed and put in Krebs solution. Segments of colon were opened along the mesenteric insertion and mucosal/submucosal layers were removed. Colonic samples were slitted along the longitudinal axis into slices of around 4-mm in width and 10-mm in length. The preparations were set up in organ baths containing Krebs solution at 37 °C, bubbled with $5\%$ CO2 and $95\%$ O2, and connected to isometric transducers (constant load = 0.5 g). BIOPAC MP150 (Biomedica Mangoni; Pisa, Italy) registered the mechanical activity. The Krebs solution was prepared as indicated in the following, with values represented as mM: KCl—4.7; NaCl—113; KH2PO4—1.2; CaCl2—2.5; MgSO4—1.2; NaHCO3—25; glucose—11.5 (pH 7.4 ± 0.1). Each preparation was allowed to equilibrate for at least 30 min, with washings every ten minutes. To deliver electrical stimulation using a BM-ST6 stimulator (Biomedica Mangoni, Pisa, Italy), a pair of coaxial platinum electrodes were placed 10 mm from the longitudinal axis of each preparation. After the equilibration time, electrical stimuli were repeatedly applied to each preparation, and experiments began when repeatable responses were obtained (generally after three stimulations). Thanks to previous experiments, the appropriate electrical stimulation frequency (10 Hz) and exogenous substance P concentration were selected. The neurogenic NK1 contractions were recorded in colonic specimens maintained in Krebs solution, containing N-ω-nitro-L-arginine methylester (L-NAME, nitric oxide synthase inhibitor, 100 µM), guanethidine (adrenergic blocker, 10 µM), 5-fluoro-3-[2-[4-methoxy-4-[[(R)-phenylsulphinyl]methyl]-1-piperidinyl]ethyl]-1H-indole (GR159897, NK2 receptor antagonist, 1 µM), (R)-[[(2-phenyl-4-quinolinyl)carbonyl]amino]-methyl ester benzeneacetic acid (SB218795, NK3 receptor antagonist, 1 µM) and atropine sulphate (muscarinic receptor antagonist, 1 µM), to assess neurogenic contraction, whereas the myogenic activity was detected maintaining the specimens in Krebs solution with the addition of tetrodotoxin (TTX, 1 µM) and stimulating with exogenous substance P (SP, 1 µM). ## 2.5. Evaluation of Plasma Lipopolysaccharide Binding Protein Lipopolysaccharide binding protein (LPB) level in plasma was measured by ELISA (Prodotti Gianni; Milan, Italy), as previously described [10,19]. For the procedure, blood samples were centrifuged for 5 min at 4000 rpm at 2–8 °C and, after the centrifugation, supernatants were collected. Aliquots (100 µL) were used for the procedure. LBP levels were expressed as ng/mL of plasma. ## 2.6. Quantification of Plasma Myeloperoxidase and Colonic Interleukin-1β Levels Plasmatic myeloperoxidase (MPO) levels, positively linked to obesity-related inflammation and insulin resistance induced by the diet [20,21], was measured by ELISA (Prodotti Gianni; Milan, Italy), as previously described [22]. Blood samples were centrifuged for 5 min at 4000 rpm at 2–8 °C and, after the centrifugation, supernatants were collected. Aliquots of 100 μL were used for the assays. MPO levels were expressed as ng/mL of plasma. Tissue IL-1β levels were quantified, as previously described [23], using a commercial ELISA Kit (Abcam; Cambridge, United Kingdom). Colon tissues, previously collected and stored at −80° C, were briefly thawed, weighed, and homogenized in PBS (0.4 mL/20 mg of tissue) at 4 °C, and centrifuged for 5 min at 10,000× g. Aliquots of 100 µL were used to conduct the experiment. IL-1β levels were indicated as picograms per milligram (pg/mg) of protein. ## 2.7. Assay of Faecal Calprotectin Calprotectin, a calcium binding protein of neutrophil granulocytes regarded as an index of neutrophil infiltration in the intestinal mucosa, was assessed in faecal samples. Briefly, freeze-dried faecal pellets were reconstituted in 1 mL PBS, along with 50 μL of $1\%$ (wt/vol) ascorbic acid (Sigma; St Louis, MO, USA). Samples were then homogenized for ten minutes (4 °C). Homogenates were diluted with 2 mL lysis buffer ($0.1\%$ sodium dodecylsulfate, $0.5\%$ sodium deoxycholate, $0.02\%$ sodium azide, 5 mM disodium ethylenediaminetetraacetic acid, and 1× Halt protease/phosphatase inhibitor cocktail [Thermo Fisher Scientific Inc.; Waltham, MA, USA] in PBS). Homogenates were further homogenized for 30 s and centrifuged (5800× g, 10 min, 4 °C), and supernatants were frozen in liquid nitrogen and stocked at −80 °C. Faecal calprotectin levels were determined using mouse calprotectin enzyme-linked immunosorbent assay kit and analyzed in accordance with the manufacturer’s instructions. ## 2.8. Western Blot Assays Colonic tissues were lysed as previously reported [24,25]. Briefly, tissues were weighed and then homogenized in lysis buffer (50 mg in 400 µL), using a polytron homogenizer (QIAGEN; Milan, Italy). Homogenates were centrifuged at 12,000 rpm for 15 min at 4 °C, and supernatants were then separated from pellets and conserved at −80 °C. Bradford assay was performed to quantify total proteins. Subsequently, proteins were separated onto a pre-cast 4–$20\%$ polyacrylamide gel (Mini-PROTEAN TGX gel, Biorad, Hercules, CA, United States) and transferred to PVDF membranes (Trans-Blot TurboTM PVDF Transfer packs, Biorad, Hercules, CA, USA). Membranes were blocked with $3\%$ BSA diluted in Tris-buffered saline (TBS, 20 mM Tris-HCl, PH 7.5, 150 mM NaCl) with $0.1\%$ Tween 20. Primary antibodies against glyceraldehyde 3-phosphate dehydrogenase (GAPDH, 5174S, Cell Signaling, Massachusetts, USA), occludin (ab167161, Abcam, Cambridge, UK), toll-like receptor (TLR)-4 (ab22048, Abcam, Cambridge, UK), nuclear factor kB p65 (NF-κB-p65, sc-8008, Santa Cruz, Dallas, USA) and myeloid-differentiation primary response-gene 88 (MyD88, sc-136970, Santa Cruz, Dallas, USA) were used. Secondary antibodies were bought from Abcam (anti-mouse ab97040 and anti-rabbit ab6721). Protein bands were revealed with ECL reagents (Clarity Western ECL Blotting Substrate, Biorad, Hercules, CA, USA). iBright Analysis software was used to perform the densitometry analysis. ## 2.9. Statistical Analysis The statistical analysis was performed only for studies where each group size was at least $$n = 6$.$ In particular, the results are presented as mean ± standard error of the mean (S.E.M.). Two-way ANOVA or one-way ANOVA was used to assess statistical significance, followed by Tukey’s post hoc tests. Significant differences were obtained with p values < 0.05. All statistical procedures were performed by two different operators, blinded to the treatment, using GraphPad Prism 7.0 software (GraphPad Prism; San Diego, CA, USA). ## 3.1. Plant-Based Food Supplement Counteracts the Body Weight Gain and BMI in Obese Mice HFD mice showed a significant increase in body weight compared to SD animals (Figure 1A). Dietary supplementation with either the natural mixture or each individual component (Curcuma L., Cassia M. and P. emblica) significantly counteracted the body weight gain in HFD-fed mice (Figure 1A). In SD-fed mice, neither the dietary supplement nor the administration of each individual component influenced body weight gain throughout the 8 weeks, as compared with SD animals (Figure 1A). At the end of week 8, BMI was significantly increased in HFD mice compared to SD mice (Figure 1B). Supplementation with the natural mixture significantly counteracted such an increase in HFD-fed mice, while each individual component slightly affected this parameter (Figure 1B). Plant-based food supplement administration and each individual component did not affect BMI in SD-fed mice (Figure 1B). ## 3.2. Dietary Supplementation with Curcumin, Emblica and Cassia Reduces Spleen and Liver Weight Mice fed with HFD for 8 weeks showed a significant increase in spleen and liver weight compared to SD mice (Figure 1C,D). The weight of the spleen and liver were significantly reduced in HFD-fed mice administered with dietary supplement for 8 weeks (Figure 1C,D). Of note, supplementation with Curcuma L., Cassia M. and P. emblica significantly reduced liver weight, but not spleen weight in HFD mice (Figure 1C,D). No significant differences were observed for spleen and liver weight between SD group and the natural mixture treated-SD mice (Figure 1C,D). ## 3.3. Plant-Based Food Supplement Ameliorated Metabolic Parameters in HFD Mice After 8 weeks of HFD diet, mice showed a significant increase in HbA1c, cholesterol and triglycerides levels compared to SD mice (Figure 2A–C). The supplementation with the dietary supplement for 8 weeks determined a significant reduction in all the assayed parameters in HFD animals, while there was no significant difference in metabolic parameter levels between the SD group and the SD mice treated with the natural mixture (Figure 2A–C). Figure 1: Effects of natural mixture, Curcuma L., Cassia M. and P. emblica on body weight (A), BMI (B), liver weight (C) and spleen weight (D) in HFD- and SD-fed mice. Each column shows the mean ± SEM (n = 10). Two-way and one-way ANOVA, and Tukey post hoc test results are as follows: —p < 0.05 for significant difference vs. the SD group, and a—p < 0.05 for significant difference vs. the HFD group. Abbreviations: BMI—body mass index; HFD—high fat diet; SD—standard diet.* Figure 2: Effects of natural mixture, Curcuma L., Cassia M. and P. emblica on cholesterol (A), triglycerides (B) and glycated hemoglobin (C) in HFD- and SD-fed mice. Each column shows the mean ± SEM (n = 6). One-way ANOVA and Tukey post hoc test results are as follows: —p < 0.05 for significant difference vs. the SD group, and a—p < 0.05 for significant difference vs. the HFD group. Abbreviations: HbA1c—glycated haemoglobin; HFD—high fat diet; SD—standard diet.* ## 3.4. Plant-Based Food Supplement Ameliorates the Intestinal Barrier Integrity Mice fed with HFD for 8 weeks displayed a significant increase in LBP plasma levels, along with a reduction in colonic occludin levels, as compared with SD animals (Figure 3A,B). Food supplementation with natural mixture or with Curcuma L. and P. emblica alone determined a normalization of LBP and occludin expression (Figure 3A,B). Plant-based food supplement administration and each individual component did not affect plasma LBP levels and the expression of occludin in SD-fed mice (Figure 3A,B). ## 3.5. Dietary Supplementation with Curcumin, Emblica and Cassia Reduces Plasmatic MPO and Tissutal IL-1β Levels in HFD Mice After 8 weeks of HFD diet, mice showed an increase in circulating MPO levels, as compared with SD animals (Figure 3C). Dietary supplementation with the natural mixture or each individual component significantly reduced plasmatic MPO levels in HFD mice (Figure 3C). IL-1β levels also increased in colonic tissues from HFD mice compared to SD mice (Figure 3D). Plant-based food supplement administration and Curcuma L. significantly counteracted such an increase in HFD-fed mice (Figure 3D). Of note, each individual component did not affect the assayed parameters in SD-fed mice (Figure 3C,D). ## 3.6. Plant-Based Food Supplement Reduced Faecal Calprotectin Levels in Obese Mice HFD resulted in a significant increase in faecal calprotectin levels, as compared with SD (Figure 3E). Supplementation with the natural mixture and P. emblica alone led to a significant reduction in faecal calprotectin in HFD mice, as compared to control HFD mice (Figure 3E). Of note, food supplement administration and each individual component did not affect calprotectin values in SD-fed mice (Figure 3E). ## 3.7. Dietary Supplementation with Curcumin, Emblica and Cassia Reduces Colonic Expression of TLR-4, MyD88 and NF-κB Colonic tissues from HFD animals showed an increase in TLR-4 expression, compared to SD mice (Figure 4A). Supplementation with the natural mixture or each individual component significantly reduced TLR-4 expression in obese mice (Figure 4A). In addition, in obese mice, the colonic expression of MyD88 and NF-kB increased, as compared with SD group (Figure 4B,C). Treatment with food supplement or with Curcuma L. or P. emblica alone determined a significant reduction in MyD88 and NF-kB expression in HFD mice (Figure 4B,C). Of note, food supplement administration and each individual component did not affect the above parameters in SD-fed mice (Figure 4A–C). ## 3.8. Plant-Based Food Supplement Counteracted Colonic Dysmotility in Obese Mice During the equilibration period, some colonic preparations developed spontaneous contraction. Such contractile activity of low amplitude remained stable during the experiment and did not interfere with the motor responses evoked by electric stimuli (ES). Electrically elicited responses consisted of phasic contractions which were, in some cases, followed by after-contractions of variable amplitude. Colonic preparations from mice fed with HFD for 8 weeks, maintained in Krebs solution with 10 μM guanethidine, 100 μM L-NAME, 1 μM atropine, 1 μM GR159897 and 1 μM SB218795, showed a significant increment of electrically evoked NK1-mediated tachykininergic contractions, compared to SD animals (Figure 5A). Dietary supplementation with the natural mixture or each individual component determined a normalization of colonic contractile responses, counteracting the overactivity of the tachykininergic system (Figure 5A). The stimulation, induced by exogenous substance P (SP) of colonic preparations from SD and HFD mice, untreated and treated with natural mixture, elicited contractions of similar magnitude, suggesting no alterations in SP-induced myogenic contractions (Figure 5B). Figure 4: Densitometric analysis and representative blots of the expression of (A) TLR-4, (B) MyD88 and (C) NF-kB in colonic tissues from HFD- or SD-fed mice treated with natural mixtures or with the single components. Each column shows the mean ± SEM (n = 6). One-way ANOVA are Tukey post hoc test results are as follows: —p < 0.05 for significant difference vs. the SD group, and a—p < 0.05 for significant difference vs. the HFD group. Abbreviations: HFD—high fat diet; MyD88—myeloid-differentiation primary response-gene 88; NF-κB—nuclear factor kB; SD—standard diet; TLR-4—toll-like receptor 4; GAPDH—Glyceraldehyde 3-phosphate dehydrogenase.* Figure 5: Effect of natural mixture on in vitro colonic contractile responses. (A) Tachykininergic contractions mediated by NK1 of colonic longitudinal smooth muscle preparations taken from HFD- and SD-fed mice treated with natural mixture, Curcuma L., Cassia M. and P. emblica. (B) Contractions elicited by exogenous SP (1 μM) in colonic preparations taken from mice treated with natural mixture, Curcuma L., Cassia M. and P. emblica. Each column shows the mean ± S.E.M. (n = 6). One-way ANOVA and Tukey post hoc test results are as follows: —p < 0.05 for significant difference vs. the SD group; a—p < 0.05 for significant difference vs. the HFD group. Abbreviations: HFD— high fat diet; SD—standard diet; SP—substance P.* ## 4. Discussion and Conclusions Obese patients often experience—alongside several associated comorbidities, including cardiovascular disease, non-alcoholic fatty liver disease, type 2 diabetes and cancer— gastrointestinal disturbances, including constipation and delayed gastric emptying [5,26,27]. In this context, gut microbiota alterations, impairments of IEB integrity and enteric inflammation have been identified as key players in the onset of obesity and gut-related dysmotility [6,7,8]. In the last few years, several lines of evidence have suggested that dietary supplementation with natural plant extracts represents a useful strategy for the management of body weight gain and systemic inflammation related to obesity. On these bases, in the present study, we evaluated the efficacy of a food supplement, containing the dry extract of Curcumin, Emblica and Cassia, in counteracting the onset of enteric inflammation and the development of motor abnormalities in a mouse model of diet-induced obesity. In particular, our experiments pointed out three major novel findings. The natural mixture supplementation [1] counteracted the increase in body weight, BMI and metabolic parameters, along with a reduction in spleen and liver weight; [2] exerts strengthening effects on the IEB integrity; and [3] reduces enteric inflammation and oxidative stress, as well as ameliorates the colonic contractile dysfunctions. To pursue these aims, we employed a murine model of HFD-induced obesity, which closely mimics a human obesity condition [10,11,17,18,28]. In our study, consistent with previous reports [10,11,17,18,28], obese mice displayed a marked increase in body weight, BMI and plasmatic MPO levels, along with significant alterations of systemic metabolic indices, such as blood total cholesterol, triglycerides and glycated hemoglobin levels (regarded as an indirect index of insulin resistance [29,30,31,32]), thus further confirming the suitability of HFD murine model. Moreover, HFD mice showed signs of enteric inflammation and neutrophil infiltration, along with an increase in spleen weight (index of chronic systemic inflammation and immune system activation [33]) and liver weight, which represent the prodromal steps leading to the development of hepatic steatosis [5,34,35]. In this setting, dietary supplementation with the natural mixture significantly counteracted the increase in body weight, BMI and metabolic parameters, along with neutrophil infiltration, as documented by a significant reduction in faecal calprotectin levels. Interestingly, the plant-based food supplement was also able to prevent the increase in spleen and liver weight. Of note, these ameliorative effects of the natural mixture may be ascribed to the ability of Curcuma L., Cassia M. and P. emblica to counteract body weight gain and oxidative stress associated with obesity, in accordance with previous studies [12,13,14]. In particular, Curcuma L. and P. emblica showed anti-obesity properties, inhibiting adipogenesis and regulating lipid metabolism, as well as preventing the increase in liver weight. In parallel, Cassia M., besides normalize metabolic parameters such as blood total cholesterol and triglycerides levels, displayed anti-oxidant properties, reducing the levels of reactive oxygen species (ROS) [12,13,14,36]. Our results corroborate interesting anti-obesity properties of such plant-based food supplements, preventing the increase in body, liver and spleen weight, as well as counteracting the metabolic modifications associated with a hypercaloric diet. It is well recognized that HFD consumption determines an impairment of the intestinal barrier structure, triggering a low-grade systemic inflammation and promoting the onset of a metabolic endotoxemia. In line with this view, we observed a reduction in the expression of occludin, one of the main tight junction proteins involved in preserving intestinal barrier integrity, along with an increase in circulating LPS binding protein (LBP) in obese mice, thus confirming changes in IEB structure and integrity following HFD intake. Of note, serum LPS is widely accepted as marker for the assessment of in vivo intestinal permeability; therefore, an increase in serum LPS levels has been associated with disorders displaying an increased intestinal permeability as common pathological feature, such as patients with inflammatory bowel diseases, irritable bowel syndrome, necrotizing enterocolitis or celiac disease [37,38,39,40]. In addition, HFD mice showed an increased expression of major inflammatory signals, such as TLR-4 and related downstream signaling molecules (MyD88 and NF-kB p65), which plays a critical role for a successful immune response [41]. Of note, the activation of TLR-4/MyD88/NF-κB pathways spur the expression of several pro-inflammatory cytokines, including IL-1β, that play pivotal roles in altering epithelial barrier integrity [24]. Interestingly, the administration of the dietary supplement significantly reinforced the IEB structure and integrity, as documented by a reduction in circulating LPS and normalization of tight junction occludin expression, as well as to counteract the increase in IL-1β levels in colonic tissues of obese mice. These ameliorative effects of such natural mixtures on intestinal barrier structure and inflammatory parameters are likely to be ascribed to the strengthening properties and anti-inflammatory abilities of Curcuma L. and Cassia M., respectively. Indeed, it has been demonstrated that the treatment with curcumin can significantly reduce the circulating LBP levels and improve IEB integrity by upregulating intestinal ZO-1, occludin and claudin-1 expression in murine models of sepsis, intestinal ischemia-reperfusion injury and type 2 diabetes mellitus [42,43,44]. In parallel, treatment with Cassia mimosoides normalized the inflammatory parameters, reducing circulating IL-1β and TNF levels in a HFD mouse model [36]. Such results highlight the strengthening effects on the IEB integrity and anti-inflammatory properties of this dietary supplement. The presence of an inflammatory condition in the gut, resulting from a weakening of the intestinal barrier, can alter digestive motility, triggering morphological and functional changes in the enteric neuromuscular compartment [45,46]. In this regard, changes in enteric tachykininergic pathways and a marked reduction in faecal output has been reported in several pre-clinical studies performed on HFD mice [10,17], corroborating the link between obesity, enteric inflammation and gut dysmotility. Of note, it is well known that an increase in colonic tachykininergic contractions, due to a marked substance P release, is associated with changes in peristaltic movements, resulting in a reduced colonic propulsive activity. In this respect, several epidemiological studies showed a high prevalence of enteric motor dysfunctions, including constipation and abdominal pain, in obese patients [47]. Consistent with this evidence, in the present study, we observed alterations of colonic excitatory neuromotility, characterized by an exalted tachykininergic pathway, in obese mice. Interestingly, dietary supplement induced a normalization of the abnormal tachykininergic contractions in HFD mice, similar to what was observed in animals fed with a standard diet, highlighting the ability of such natural mixtures to improve the bowel motor dysfunctions associated with obesity. Of note, this beneficial effect on colonic motility is likely to be ascribed to the anti-inflammatory properties of Cassia mimosoides and Curcuma longa. Indeed, it has been demonstrated that the presence of intestinal inflammation determines a reorganization of neurochemical coding on the enteric neurons, resulting in an increase in the tachykinergic contractions with consequent alteration of gut motility in obesity [10]. Therefore, the administration of natural products with anti-inflammatory properties could exert an ameliorative effect on colonic contractions due to their ability to curb the enteric inflammatory responses. In parallel, the restoration of tachykinergic contractions with natural mixtures could also be ascribed to the myorelaxant effects of Cassia M. and Curcuma L. on the mouse ileum and colon. Indeed, it has been described that treatment with Cassia and Curcumin is able to relieve the inflammatory-related intestinal dysmotility through a spasmolytic action on excitatory neurotransmitter pathways [48,49,50,51]. In conclusion, the present work provides evidence that dietary supplement, containing the dry extract of Curcumin, Emblica and Cassia, exerts interesting anti-obesity properties, preventing the increase in body, liver and spleen weight, as well as counteracting the metabolic alterations associated with a hypercaloric diet. In addition, such a natural mixture, besides exerting strengthening effects on the IEB integrity, shows anti-inflammatory properties and relieves the bowel dysmotility associated with obesity through a normalization of excitatory tachykininergic colonic contractions (Figure 6). 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--- title: The Lübeck Medication Satisfaction Questionnaire—A Novel Measurement Tool for Therapy Satisfaction authors: - Ludwig Matrisch - Yannick Rau - Hendrik Karsten - Hanna Graßhoff - Gabriela Riemekasten journal: Journal of Personalized Medicine year: 2023 pmcid: PMC10058402 doi: 10.3390/jpm13030505 license: CC BY 4.0 --- # The Lübeck Medication Satisfaction Questionnaire—A Novel Measurement Tool for Therapy Satisfaction ## Abstract Background: Therapy satisfaction is widely considered an important aspect of clinical care. Still, there are currently no freely available questionnaires for its measurement. We developed the Lübeck Medication Satisfaction Questionnaire (LMSQ) for that purpose. Here, we present its content and psychometric properties. Methods: The LMSQ was validated on 86 patients in a single center study. The Kaiser-Meyer-Olkin test, confirmatory factor analysis, covariance analysis, and a test of exact fit were performed. Reliability was tested using Cronbach’s α and McDonald’s ω. The relationship to other patient-reported outcomes was tested using Pearson’s correlation. Results: Confirmatory factors analysis yielded moderate factor loadings with $p \leq 0.001$ in all subscales. Reliability was adequate (α = 0.857 and ω = 0.872). Model fitness was excellent in all tests. The LMSQ was positively correlated with medication adherence ($r = 0.603$, $p \leq 0.001$) and most dimensions of health literacy. Conclusions: The LMSQ possesses adequate psychometric properties for its purpose. We recommend further validation in a more diverse patient collective. ## 1. Introduction We currently live in an era of increasingly personalized medical care [1]. The term refers to a philosophy of healthcare in which healthcare professionals take characteristics unique to their patients into account. This often refers to individualized therapy approaches guided by precise diagnostics on a molecular level [2]. However, personalized medical care can also take the patients’ values, goals, and their personal life situation into account [3]. This creates the basis for a trustful doctor-patient relationship. The quality of this relationship is associated with improved medication adherence and thereby improved therapy outcome [4]. Therapy satisfaction is defined as the degree to which the patients perceive that the treatment fulfills their health needs [5]. On one hand, therapy satisfaction can strengthen the trust between a patient and their healthcare providers [6], which can possibly lead to better health outcomes [7]. On the other hand, good therapy outcome can improve therapy satisfaction [8]. Therefore, improving therapy satisfaction is widely considered an important goal in healthcare [9]. Despite this importance, there is a lack of tools for the quantification of therapy satisfaction. The currently most widely used questionnaire—the Treatment Satisfaction Questionnaire for Medication (TSQM)—is a well validated tool available in several versions, but it lacks accessibility due to its licensing structure [10,11,12]. Healthcare providers or researchers in developing countries lacking sufficient funds might be unable to pay for it, hindering research as well as individualized treatment strategies. This lack of adequate diagnostic tools for therapy satisfaction reflects the minor role it has played in the concept of personalized medicine so far. In psychology, it is well known that the experiences that shape the traits, values, and personal preferences are unique to the individual [13,14,15]. Taking those experiences into consideration therefore reflects the approach and aspiration of personalized medicine. To fulfill this task, there is a need for further research in that field as well as for a cultural shift in clinical practice. ## 1.1. Measurement of Therapy Satisfaction Therapy satisfaction is a highly individual and subjective modality. Therefore, it is impossible to measure objectively [16]. Researchers as well as healthcare providers have to rely on patients’ reports. This can be performed in the form of an interview. Although interviews are an essential tool in qualitative research, they often lack the properties needed for quantitative analysis [17]. Furthermore, they rely on trained interviewers to minimize interviewer bias and thereby bind personnel capacities that often are not available in everyday clinical practice [18]. Therefore, self-reported questionnaires are often used to address these issues. Well-designed questionnaires give the opportunity to not only quickly and accurately quantify self-reported patient outcomes but to also assess multiple dimensions of said outcomes. Our goal was to develop an easily applicable questionnaire for the quantification of therapy satisfaction that could accurately differentiate between its dimensions. ## 1.2. The Lübeck Medication Satisfaction Questionnaire The Lübeck Medication Satisfaction Questionnaire (LMSQ) is a self-administered questionnaire consisting of 18 statements concerning patients’ satisfaction with their medication. The patients can state their degree of agreement on a four-point Likert scale. The questionnaire was developed after an extensive literature review on therapy satisfaction and the factors influencing it. Adequate phrasing and intelligibility were ensured through a pilot survey consisting of a series of patient interviews as well as expert interviews before the study. The questionnaire consists of six subscales reflecting the dimensions of therapy satisfaction. Each subscale is measured by three equal-weighted statements in the questionnaire. The full questionnaire is presented in Table 1. The German version of the LMSQ is presented in Supplementary Table S1. ## 1.3. Evaluation of the LMSQ Each item of the questionnaire can be assigned to a subscale. Every subscale consists of three items. The score of each subscale is calculated by adding up the scores of the three items and dividing them by three. The subscales include the following: Side effects (LMSQ_2, LMSQ_9, LMSQ_17): This subscale describes the patients’ degree of satisfaction with the side effects of their treatment. It is well known that side effects affect therapy satisfaction as well as other factors such as quality of life (QOL), medication adherence, and treatment outcome [19,20,21]. Therefore, side effects should be duly considered when deciding between therapy options. This subscale, however, does not measure the objective degree of side effects since it is a patient-reported outcome (PRO). Rather, the perceived subjective burden of side effects the patients experience is quantified. Effectivity (LMSQ_5, LMSQ_11, LMSQ_14): This subscale describes the perceived effectivity of the therapy. Treatment effectivity plays an important role in the choice of therapy and therefore is the parameter usually measured in clinical studies. However, this section also does not measure the actual effect of the therapy but rather the effect as it is perceived by the patients. Practicability (LMSQ_1, LMSQ_3, LMSQ_7): This subscale describes the practicability of the therapy. This is an important dimension of therapy satisfaction that deals with the non-biological properties of the therapy relevant to the patients. It incorporates how well the therapy resonates with the patients’ daily life schedule and their personal preferences. These factors have important implications for outcomes such as medication adherence and should be considered in therapy decisions. This is especially important from a perspective of personalized medicine. Daily life (LMSQ_10, LMSQ_12, LMSQ_16): This subscale describes the patients’ degree of satisfaction with the freedom and independence gained through the therapy. Disease burden is an important factor influencing patients’ QOL [22]. Its alleviation can create QOL improvement for patients. Therefore, it is an important dimension of therapy satisfaction. Healthcare workers (LMSQ_6, LMSQ_8, LMSQ_13): This subscale describes the patients’ degree of satisfaction with their healthcare providers. The quality of the relationship between patients and their healthcare providers has been shown to be of importance for therapy satisfaction as well as therapy outcome [23,24]. The style of communication as well as taking the patients’ values and goals into account is crucial for forming effective patient-healthcare worker relationships [25]. This should be a foremost goal in personalized therapy. General satisfaction (LMSQ_4, LMSQ_15, LMSQ_18): This subscale describes the overall therapy satisfaction of the patient. This section is especially important from a personalized medicine perspective as it reflects the balance of factors influencing therapy satisfaction individually. The total LMSQ score is calculated by adding up the scores of the individual items and dividing them by 18. ## 2.1. Patient Recruitment The LMSQ was validated in its German version within a study investigating medication adherence and its influencing factors in patients with systemic sclerosis (SSc) [26]. A total of 88 patients with SSc were enrolled in a cross-sectional study at the Department of Rheumatology and Clinical Immunology at the University of Lübeck, Germany. Two patients dropped out due to being released from the hospital before they could finish the questionnaire, resulting in a dropout rate of $2.27\%$. Patients were recruited in the weekly SSc outpatient clinic as well as in the ward. Data were collected between July 2020 and February 2021. Patients fulfilling the EULAR/ACR 2016 classification criteria currently under treatment for their SSc were included [27]. We excluded patients unable to complete the questionnaire due to physical impairment, language barrier or illiteracy, as well as patients who legally could not consent to the study. This involved two patients, one who did not understand German and one who was physically unable to hold a pen. All other patients were asked to participate and left alone for the completion of the questionnaire to eliminate possible bias due to the Hawthorne effect. Anonymization was ensured by assigning a number to the participants. Additionally to the LMSQ, patients were also asked to provide information about their age, gender, native language, their migration background, their religion, their highest educational degree, their current employment status, and the number of members in their household for demographic purposes. The Scleroderma Health Assessment Questionnaire (SHAQ), the Compliance Questionnaire of Rheumatology (CQR), and the Health Literacy Questionnaire were also applied to assess associations between these patient-reported outcomes [28,29,30]. Nine patients did not fully complete their whole questionnaires, and out of those, four did not fully complete the LMSQ section of the full questionnaire. The patient recruitment process is illustrated in Figure 1. Since the various sections of the questionnaires could be evaluated independently, it was decided to include all participating patients, irrespective of the completeness for all clinical data. ## 2.2. Translation and Cultural Adaption into English Since the questionnaire was initially created as well as used in this study in the German language, we translated it to make it more accessible to the international research and healthcare community. The translation process was led by the guidelines proposed by Beaton et al. [ 31]. In the first step, two translators were asked to independently translate the original version into English. The two translations were merged into one combined version which was translated back by a third translator into German in the second step. In the third step, the back-translated version was compared to the original version. The German version that was used in this study is accessible in the supplement of this article. ## 2.3. Statistical Analysis Statistical analysis was performed using Jamovi 1.2.27.0. Sampling adequacy was assessed using the Kaiser-Meyer-Olkin (KMO) test [32]. The cut-off value for insufficient sampling was set at 0.6. Confirmatory factor analysis was performed for the subscales of the LMSQ. Beforehand, we performed Bartlett’s test of sphericity. Reliability was analyzed using Cronbach’s α and McDonald’s ω. Pearson’s correlation was performed to elucidate the relationship between the PROs. Furthermore, we conducted an analysis of the factor covariances and performed a test of exact fit. The significance level was set at $$p \leq 0.05.$$ ## 3.1. Demographic Characteristics of the Participants Table 2 presents the demographic characteristics of the enrolled participants. All patients were treated for SSc. Miscellaneous clinical characteristics are not presented here as they are of less importance for the study of therapy satisfaction [33]. The patients are representative of SSc patients in Germany. The collective mainly consisted of women ($75.3\%$), and very young and very old patients are represented less than proportionally. Additionally, the number of retirees was higher than in the general population ($54.1\%$). Apart from these factors, the collective is representative of the general German population. ## 3.2. Descriptives of the LMSQ and Its Subscales Table 3 features the descriptive statistics of the LMSQ. Four out of the 86 participants did not fill out the questionnaire completely due to unknown reasons, resulting in a response rate of $95.35\%$. The average and the median values are similar across all the subscales as well as the total LMSQ score. ## 3.3. Kaiser-Meyer-Olkin Test Revealed Sufficient Sampling Adequacy To test the statistical requirements of the factor analysis, Bartlett’s test of sphericity and the Kaiser–Meyer–Olkin (KMO) test were performed. Bartlett’s test (χ² = 599, df = 153, $p \leq 0.001$) was significant, hinting towards a statistically significant difference between the correlation matrix and the identity matrix. The KMO test’s overall measure of sampling adequacy (MSA) was 0.811. Across all items of the LMSQ, the MSA was >0.6. Thus, we considered the MSA to be meritorious and the prerequisites to perform the factor analysis to be established. The full KMO test results are presented in Table 4. ## 3.4. LMSQ Is Characterized by Adequate Internal Validity and Reliability A confirmatory factor analysis was performed for the subscales of the LMSQ presenting the dimensions of therapy satisfaction. The results are presented in Table 5. The factor loadings of all LMSQ items are significant ($p \leq 0.001$). The factor loadings range from 0.318 (LMSQ_1 and LMSQ_18) to 0.581 (LMSQ_5). A test for exact fit showed adequate model fitness (χ² = 163, df = 120, $$p \leq 0.005$$). Additional fit measures are presented in Table 6. These additional measures of fitness further underscore the adequacy of our model. An analysis of the factor covariances is presented in Table 7. Factor variances are moderate across the subscales of the LMSQ. Significant results were seen along most of the subscales. However, the covariances between side effects and daily life (estimate = 0.257, $$p \leq 0.09$$), practicability and daily life (estimate = 0.151, $$p \leq 0.35$$) and practicability and healthcare workers (estimate = 0.179, $$p \leq 0.25$$) were not significant. To assess the scale reliability of the LMSQ, internal consistency was tested using Cronbach’s α as well as McDonald’s ω. Both proved adequate reliability of the LMSQ items (0.857 and 0.872, respectively). ## 3.5. Total LMSQ Score Correlated with Therapy Adherence and Health Literacy Assessed by CQR and HLQ Score The LMSQ score correlated with therapy adherence measured by the CQR score (Pearson’s $r = 0.566$, $p \leq 0.001$). Controlling for age, SHAQ score, and disease duration, the correlation was $r = 0.603$, $p \leq 0.001.$ Pearson’s correlation with the subscores of the HLQ controlling for age, SHAQ score, and time since the disease onset yielded the results presented in Table 8. LMSQ correlated with all subscores of the HLQ besides appraisal. ## 4.1. LMSQ Compared to Other Tools Assessing Therapy Satisfaction The LMSQ is a novel tool for the measurement of therapy satisfaction in patients with systemic sclerosis. It was developed by applying rigorous scientific evaluation and showed excellent reliability and validity in the data presented in this article. It was developed for application in long-term drug therapy in chronic diseases. However, in its current state of validation, it has only been applied on patients with SSc. The reliability and validity for the therapy of acute medical issues or non-drug interventions such as surgery has not been tested. The LMSQ is designed to distinguish between six dimensions of therapy satisfaction. This provides a more detailed and differentiated insight into patient views compared to already used questionnaires such as the TSQM or the Treatment Satisfaction with Medicines Questionnaire (SATMED-Q), which feature less dimensions [10,34]. The three questionnaires all feature a scale for the effectiveness of the treatment, for side effects, and for the general satisfaction with the treatment. The LMSQ as well as the SATMED-Q additionally feature a scale that represents the satisfaction with the medical care provided by the healthcare workers. While the TSQM and the SATMED both feature one scale to assess the convenience of the treatment, this property is split up into two scales (practicability and daily life) in the LMSQ to differentiate between the practicability of the treatment and its impact on the patients’ daily life. The LMSQ is the first questionnaire of its kind that is freely available in German. It approaches the need for methods to assess therapy satisfaction. It could thereby help to facilitate research in the field as well as daily patient care. The LMSQ positively correlates with medication adherence. This correlation has been demonstrated in other studies using other questionnaires for the measurement of therapy satisfaction [35]. It also correlates with various dimensions of health literacy. Similar observations have also been made with other questionnaires for therapy satisfaction [36]. ## 4.2. Limitations The presented data were only assessed in patients with SSc. This impedes the generalizability of the results to other patient collectives with other medical issues. Furthermore, the questionnaire was only tested in a single center. A multi-center study could provide differing results. This includes potential cultural differences. These could be addressed by performing a study in regions culturally different from Germany. Additionally, this study was conducted using the German version of the LMSQ. The English version presented in Table 1 might show different psychometric properties than the German one. Moreover, the COVID-19 pandemic and its consequences that were close to its peak during the data collection could have played a role in patient recruitment. It seems plausible that patients with a high degree of anxiety could have avoided visiting the hospital due to fear of contracting the virus of and therefore might be underrepresented in our collective [37,38]. This holds especially true considering the immunosuppressive nature of the SSc therapy regimens. Fortunately, sampling issues only play a minor role in studies such as this one since the main goal is to empirically examine the content and measurement dimensions that underpin the theoretical construct underlying the questionnaire [10]. The item-item covariance structure can be assumed to be fairly consistent, even with moderate sampling bias. Studies in larger and more diverse patient collectives would increase the external validity and should therefore be conducted. This includes two dimensions of further external validation. Firstly, studies in similar collectives to others already extensively analyzed in the field of therapy satisfaction research could help compare the LMSQ to other established questionnaires and thereby elucidate the differences in psychometric properties such as reliability and factor covariance. This would especially be useful to clarify the indications for several questionnaires in research as well as in clinical practice. Diseases with extensive research in the field of therapy satisfaction include diabetes, hypertension, and chronic obstructive pulmonary disease [39,40,41]. These diseases share high prevalence in the general population. Therefore, elucidating the role of therapy satisfaction in these disease entities is of high urgency. Secondly, further studies for the quantification of therapy satisfaction using the LMSQ could unfold the topic in less common diseases in which therapy satisfaction so far has only played a minor role. The factor loadings of the LMSQ were only moderately high with values as low as 0.318. This might impede the differentiation between the dimensions of therapy satisfaction represented in the various subscales of the LMSQ. However, all factors were considered statistically significant ($p \leq 0.001$). Moreover, the overall model of the confirmatory factor analysis displayed excellent fit. ## 4.3. The Future of Therapy Satisfaction in Medicine Currently, the assessment of therapy satisfaction is far from becoming clinical routine. Therapy satisfaction is rarely considered in therapy decisions. Even when it is considered, it is often not assessed by appropriate methods. Research data on therapy satisfaction is scarce for the majority of diseases and drugs. However, in an effort to shift the clinical practice towards a personalized medicine approach, therapy satisfaction should be tackled with high priority. Questionnaires such as the LMSQ facilitate a quick assessment of therapy satisfaction and its dimensions and thereby enable healthcare providers to shape their therapy according to the patients’ preferences. Given its quick application and non-necessity of medical personnel to complete, it does not bind many valuable human resources. Digitalization tools could make the process more efficient and further decrease the need for human resources [42]. Combining the LMSQ with other PRO-related questionnaires could help adapt therapy approaches specifically to patients. Science on the application of personalized medicine tended to concentrate on molecular analyses, neglecting the role of therapy satisfaction for the long-term adherence to individual therapy decisions, especially in chronic diseases. Therefore, it is an urgent need to add PROs assessing therapy satisfaction to conventional strategies in personalized medicine. Such a holistic approach might be the key to improve upon not only clinical outcome but also upon other outcome criteria that have so far been treated as secondary. ## 5. Conclusions The LMSQ is an easily applicable tool for the measurement of therapy satisfaction and its dimensions. Reliability and internal validity have been proven by applying multiple adequate statistical methods. External validity, however, remains unclear; therefore, a validation study in a more diverse patient collective should be conducted. The questionnaire lays the groundwork for further research in the field of therapy satisfaction. The role of therapy satisfaction in clinical practice as well as in research is currently underappreciated. It should be at the forefront of the mind of any healthcare worker when dealing with patients. ## References 1. 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--- title: Cell Adhesion Molecules in Schizophrenia Patients with Metabolic Syndrome authors: - Anastasiia S. Boiko - Irina A. Mednova - Elena G. Kornetova - Arkadiy V. Semke - Nikolay A. Bokhan - Svetlana A. Ivanova journal: Metabolites year: 2023 pmcid: PMC10058418 doi: 10.3390/metabo13030376 license: CC BY 4.0 --- # Cell Adhesion Molecules in Schizophrenia Patients with Metabolic Syndrome ## Abstract Metabolic syndrome (MetS) is a common comorbidity of schizophrenia and significantly shortens life expectancy of the patients. Intercellular (ICAM), vascular (VCAM), and neural (NCAM) cell adhesion molecules (CAMs) mediate neuroinflammatory processes, and their soluble forms (e.g., sICAM) in plasma are present in parallel with their cell-bound forms. In this study, their serum levels were examined in 211 white Siberian patients with paranoid schizophrenia (82 patients with and 129 without MetS according to the 2005 International Diabetes Federation criteria). Serum levels of CAMs were determined with Magpix and Luminex 200 (Luminex, Austin, TX, USA) using xMAP Technology. The level of sICAM-1 was significantly higher and that of sVCAM-1 significantly lower in patients with MetS compared to patients without MetS. Levels of NCAM did not differ between the groups. More pronounced Spearman’s correlations between CAMs, age, duration of schizophrenia, and body–mass index were observed among patients without MetS than among patients with MetS. Our results are consistent with MetS’s being associated with endothelial dysfunction along with other components of inflammation. Through these endothelial components of peripheral inflammatory processes, MetS might induce intracerebral neuroinflammatory changes, but further investigation is needed to confirm this. ## 1. Introduction Metabolic syndrome (MetS) and obesity are widespread among patients with schizophrenia; according to different authors, the prevalence of MetS among these pa-tients during antipsychotic treatment is in the range from $28\%$ to $46\%$ [1,2,3], and that of obesity from $16.4\%$ to $48.9\%$ [4,5]. Many factors common between mentally healthy in-dividuals and patients with schizophrenia contribute to the development of MetS, and the key ones are a sedentary lifestyle and an unbalanced diet [6]. At the same time, in patients with schizophrenia, MetS is most often considered a side effect of antipsy-chotic therapy: on haloperidol, metabolic disorders develop in $39.4\%$ of the patients; on clozapine, in $44.7\%$; on amisulpride, in $33.3\%$; on olanzapine, in $34\%$; on quetiapine, in $18.8\%$; and on risperidone, in $35\%$ of the patients [7]. MetS is a predisposing factor for cardiovascular pathologies and is regarded as a mortality risk factor in patients with mental disorders. Information on the pathogenesis of MetS can be obtained by studying hormones regulating metabolism and their genes, which in turn can also be considered potential biomarkers of the susceptibility to MetS and to lipid metabolism disorders [8,9]. Currently, aside from the generally accepted signs of MetS (central obesity, hyperglycemia, dyslipidemia, and blood pressure elevation), an important role is attributed to other and newer signs of MetS, such as microalbuminuria, cytokines, prothrombotic and fibrinolytic factors, and oxidative stress [10,11,12,13]. Molecular neurobiological research suggests that inflammation and immune activation may affect the functioning and plasticity of neurons and can switch microglial cells to a proinflammatory state associated with neurodegeneration [14,15,16]. Cell adhesion molecules (CAMs) are important for the formation and maintenance of neural structures [17], whereas disturbances of neural structures are observed in mental disorders [18,19,20]. A number of intercellular immunoglobulin-like transmembrane glycoproteins are expressed in chronic inflammatory conditions [21,22]. Intercellular adhesion molecule 1 (ICAM-1) is a transmembrane adhesion protein that participates in the migration of leukocytes to a site of inflammation [23]. Its functions are diverse and not completely clear [24], but there is evidence that ICAM-1 can play a modulating role in inflammation [25]. The expression of sICAM-1 is increased in various pathological conditions, for example, bacterial sepsis [26], type II diabetes mellitus [27], preeclampsia [28], and atherosclerosis [29]. ICAM-1 is expressed in the central nervous system (CNS) in human forebrain white and gray matter endothelial cells and astrocytes and in microglial cells [21]. Investigation of ICAM-1 in psychiatric disorders is relevant for two reasons: this protein plays a key part in the blood-brain barrier (BBB), is important for the pathogenesis of schizophrenia and other psychiatric disorders, and is a marker of inflammation. Some authors report an increase in ICAM-1 expression in schizophrenia and depressive disorders, including bipolar affective disorder [16,21]. In human obesity, overexpression of the soluble form (sICAM-1) positively correlates with the amount of abdominal fat [30]. Some studies have shown that sICAM-1 levels are also elevated in obesity and correlate with central obesity [29,30,31,32]. Vascular cell adhesion molecule 1 (VCAM-1) is a membrane-bound receptor of adhesion molecules and a member of the immunoglobulin family. The soluble form (sVCAM-1) is considered a ligand for leukocyte integrins, which mediate binding and transformation of monocytes and lymphocytes as well as strong attachment and transendothelial migration of leukocytes [33]. Endothelial cells are not only a passive barrier but also immunologically active themselves. They can produce chemokines, and endothelial sVCAM-1 is associated with age- and inflammation-induced activation of microglia, impaired neurogenesis, and cognitive deficits [34,35]. Several stimuli, including cytokines, lipoproteins, products of glycation, hypertension, and oxidants can enhance VCAM-1 expression [33]. Activated endothelial cells initially upregulate selectins (e.g., P-selectin) to slow leukocytes on the endothelial surface before firm adhesion via integrins and immunoglobulin superfamily CAMs (e.g., ICAMs and VCAMs). On leukocytes, the expression of integrin receptors, which may bind CAMs and facilitate transmigration of these cells across the BBB, has been shown to be increased in schizophrenia [16]. Neural cell adhesion molecule (NCAM) is another member of the immunoglobulin superfamily [36]. NCAM plays a crucial role in intercellular adhesion, neuronal migration, synaptic plasticity, and brain development and is involved in learning and memory formation processes [37,38,39]. NCAM is primarily expressed in neurons and not only participates in intercellular homotypic adhesion but also functions as a signaling receptor. NCAM enables endothelial cell adhesion and communication with other cells, such as pericytes and astrocytes. NCAM expression has been detected both in neurons and in myocytes in the zone of neuromuscular contact, on lymphocytes, and in organs of the vascular and other systems. These CAMs may be shed from the cell surface by different mechanisms, and their soluble form is released into the circulation. Soluble forms of NCAM are modulators of NCAM-mediated cell behavior. Given that NCAM plays an important part in the development of the nervous system, some authors have tested the hypothesis of dysfunction of nervous-system development in schizophrenia; their reports suggest that an altered NCAM level may be one of biomarkers of cognitive impairment [35]. Literature data also indicate that low concentration of NCAM in serum is associated with a smaller hippocampus volume in first-episode schizophrenia patients [40]. Thus, NCAM, ICAM, and VCAM are CAMs that affect the structure of the nervous system and cause synaptic alterations in the adult brain [41]. They are important for neuroinflammatory signal transduction across the BBB and therefore may have a role in neuroinflammatory processes in schizophrenia [16]. These proteins also take part in cell migration, axon growth, peripheral axon regeneration, and synaptic plasticity [42,43]. Despite a large number studies on CAMs and their soluble forms in schizophrenia, there have been few research articles about MetS in patients with schizophrenia. The aim of the study was investigation of CAMs in blood serum of schizophrenia patients with MetS. ## 2.1. The Study Population and Sample Collection The study complied with the Declaration of Helsinki (1975, revised in Fortaleza, Brazil, 2013). The Bioethical Committee of the Mental Health Research Institute of Tomsk National Research Medical Center (the Russian Academy of Sciences) approved the study protocol (decision No. 187, approval on 24 April 2018). All patients had an opportunity to familiarize themselves with the purpose and objectives of the study and received answers to their questions. Then, all participants provided written informed consent. After obtaining informed consent, we recruited 211 patients with schizophrenia being treated at various clinics in Siberia (Russian Federation): the Mental Health Research Institute of Tomsk National Research Medical Center, Tomsk Clinical Psychiatric Hospital, Kemerovo Regional Clinical Psychiatric Hospital, and N.N. Solodnikova Clinical Psychiatric Hospital of Omsk. The main inclusion criteria were (i) the paranoid type of schizophrenia diagnosed—consistently with ICD-10 (International Classification of Diseases, 10th revision)—according to a structured clinical interview (Structured Clinical Interview for the DSM), (ii) age 18–65 years, (iii) the patient’s informed consent, and (iv) confirmed absence of pronounced organic pathology or unstable somatic disorders. The Positive and Negative Syndrome Scale (PANSS) for schizophrenia was used to assess symptom severity [44]. This questionnaire includes three subscales that allow to separately evaluate positive, negative, and general psychopathological symptoms and to calculate the total score. Baseline antipsychotic treatment and concomitant therapies (drugs, doses administered, and duration of current medication use) were assessed, as were previous antipsychotic and concomitant somatic therapies during the preceding 6 months. We employed the chlorpromazine equivalent (CPZeq) daily dose to standardize the dose, efficacy, and adverse effects of antipsychotics [45]. The diagnosis of MetS was made according to the criteria of the International Diabetes Federation (IDF, 2005) [46]; they included a definition of abdominal obesity (waist circumference greater than 94 cm in males or greater than 80 cm in females) and the presence of any two of the following four signs: The level of triglycerides above 1.7 mmol/L or an ongoing lipid-lowering therapy. The level of high-density lipoprotein cholesterol of less than 1.03 mmol/L in males or less than 1.29 mmol/L in females. Blood pressure higher than or equal to $\frac{130}{85}$ mm Hg or the use of antihypertensive medication. The level of glucose in blood serum higher than or equal to 5.6 mmol/L or previously diagnosed type 2 diabetes mellitus. Blood samples were collected after a 12-h overnight fast in the first days of admission to a hospital before antipsychotic-drug ingestion and were centrifuged for 30 min at 2000× g and 4 °C to isolate serum. The serum samples were stored at −80 °C until analysis. ## 2.2. Laboratory Metrics Parameters characterizing MetS, including concentrations of glucose, triglycerides, and high-density lipoprotein cholesterol, were determined in serum using Cormay kits (Lomianki, Poland) on a biochemical analyzer. Concentrations of sCAMs (sICAM-1, sNCAM, and sVCAM-1) were measured by means of Magpix and Luminex 200 multiplex analyzers (Luminex, Austin, TX, USA) and xMAP Technology at the Medical Genomics core facility of Tomsk National Research Medical Center. Panel HNDG3MAG-36K by MILLIPLEX® MAP (Merck, Darmstadt, Germany) was used to quantify the CAMs. The data were processed in the Luminex xPONENT software, with subsequent export of the results to the MILLIPLEX® Analyst 5.1 software. ## 2.3. Statistical Analysis Data analysis was carried out using the SPSS Statistics software (version 23) for Windows. Data were checked for normality of distribution by the Shapiro–Wilk test. The significance of differences was determined by the Mann–Whitney U test for independent samples with a non-normal distribution along with the calculation of the median and quartiles (Me [Q1; Q3]). For normally distributed data, the results are presented as the mean and standard deviation (SD) together with significance of differences according to Student’s t test. The Chi-square test was applied to categorical variables. Bonferroni’s correction was used for multiple comparisons. Spearman’s correlation analysis was carried out to assess associations among the investigated parameters. Multiple regression analysis was performed to estimate the joint effect of different variables on a CAM’s level. Data were assumed to be statistically significant at p-values less than 0.05. ## 3.1. Sociodemographic and Clinical Characteristics of the Subjects The main sociodemographic and clinical characteristics of the enrolled patients are shown in Table 1. Patients with schizophrenia were subdivided into two groups depending on the presence of MetS: a group with MetS (82 patients, $38.86\%$) and a control group (without MetS; 129 patients or $61.14\%$). Patients with MetS had statistically significantly older age, longer duration of schizophrenia, older onset age of schizophrenia, a higher BMI, and greater waist circumference. Most patients (over $90\%$) in the MetS group were obese or overweight, while patients in the control group had either normal weight or overweight (~$50\%$ each). The sex distribution was almost the same between the two groups. The PANSS score and CPZeq did not differ significantly between the two groups. ## 3.2. Cell Adhesion Molecules Patients with MetS showed a significantly higher serum concentration of sICAM-1 as compared with patients without MetS (Table 2). Additionally, the level of sVCAM-1 was significantly lower in the MetS group than in patients without MetS. The concentration of NCAM in the serum did not differ significantly between the two groups. Next, the concentrations of CAMs were collated with the patients’ weight (considered normal at BMI < 25, overweight or obesity at BMI ≥ 25; Table 3). The serum level of sICAM-1 was found to be significantly higher in obese and overweight patients than in patients with a normal BMI. Spearman’s correlation analysis was carried out to assess relations between the studied quantitative parameters in the control group (Table 4) and in the MetS group (Table 5). Plots of correlation between CAMs, age, duration of schizophrenia, and BMI among patients with or without MetS are presented in the Supplementary File (Figures S1 and S2). sNCAM manifested a weak negative correlation with age, whereas sICAM-1 weakly positively correlated with the BMI in the group of patients without MetS. CAMs correlated with one another (a positive correlation on average). The correlation analysis revealed that associations were weaker in the group of patients with MetS. For instance, there were no significant associations of CAMs with age, duration of illness, or BMI among patients with MetS. A significant correlation between sNCAM and sICAM-1 levels, which was found in patients with schizophrenia without MetS, was absent in the MetS main group, and correlations between other CAMs were weaker. We then performed a multiple regression analysis, considering CAMs dependent variables while regarding age, duration of schizophrenia, and BMI as independent variables. We found no significant associations among these parameters (Table S1). When the BMI was replaced by MetS, only sVCAM-1 maintained an independent negative correlation with MetS ($$p \leq 0.034$$; Table 6). ## 4. Discussion CAMs are responsible for leukocyte trafficking and may serve as a link between peripheral inflammation and CNS neuroinflammation in patients with schizophrenia by mediating signaling across the BBB and by promoting immune responses. CAMs are among the most common proteins in the nervous system and take part in synaptic plasticity and functioning [43,47,48]. We hypothesized that CAMs are dysregulated in MetS in schizophrenia patients and for this purpose measured serum levels of vascular, intracellular, and neural CAMs in schizophrenia patients with MetS as compared to those without. First, we noticed a higher concentration of sICAM-1 in the serum of schizophrenia patients with MetS in comparison to those without MetS. An increased level of sICAM-1 was also found in obese and overweight patients with schizophrenia. In the CNS, ICAM-1 is expressed in microglial cells and astrocytes and in endothelial cells of white and gray matter of the human forebrain [21]. A number of studies indicate elevated levels of sICAM-1 in schizophrenia [16,49,50] and bipolar disorders [51,52], whereas some old articles show lower levels in schizophrenia [53,54]. We have demonstrated in some of our previous papers that MetS in schizophrenia is associated with upregulation of inflammatory factors (apolipoproteins and cytokines) [13,55]. This finding can be interpreted as the presence of an inflammatory component in the mechanism of MetS onset in individuals with schizophrenia. ICAM may play a specific role in the extension of peripheral inflammatory responses to the CNS by promoting leukocyte penetration through the BBB [56]. Cytokines such as tumor necrosis factor (TNF) regulate the permeability of the BBB to leukocytes—among other phenomena—by promoting the expression of ICAM in the endothelial cells that constitute the BBB [56,57]. It can be supposed that ICAM-1 levels are associated with hyperpermeability or hypopermeability of the BBB and thus affect the connection between glial cells and the peripheral immune system. These aberrations may not only follow the onset of MetS but also precede it, for example, when neuroinflammation occurs in behavior-modulating neuronal structures such as the dorsal diencephalic conduction system [58,59]. Intervention studies on experimental animals are needed to explore this topic further, as done previously, for example, for mRNA expression of NCAM, ICAM, and VCAM in the hippocampus of mice with streptozotocin/nicotinamide-induced diabetes [41]. There are also data on widespread expression of sICAM-1 in vessels [60] and on its participation in atherosclerosis and metabolic diseases [61,62], in which elevated levels are observed, meaning a cardiometabolic risk. Literature data suggest that insulin resistance and MetS were associated with sICAM-1 levels in Taiwanese [63]. Second, we found a statistically significant decrease in the level of sVCAM-1 in the serum of patients with schizophrenia with metabolic syndrome compared with patients without MetS in our study of Siberian White patients with schizophrenia. sVCAM-1 appears to be associated with obesity in Pima Native Americans with type 2 diabetes [64], while no such association was found in other studies in mentally healthy White individuals with diabetes [65,66]. The possible contribution of ethnicity, schizophrenia, and its treatment to the results should be explored in future studies. According to correlation and multiple regression analysis, we found a negative relationship between the presence of MetC and the level of sVCAM-1. No significant relationships were found between age, disease duration, BMI, and CAMs. Probably, the lack of influence of age, disease duration, and BMI on CAM is due to the fact that the mechanisms of CAMs alterations in MetS are more related to other factors, such as antipsychotic therapy, which patients with schizophrenia are forced to take for a long time. Serum NCAM levels did not differ between patients with and without metabolic syndrome. According to the literature data, the level of sNCAM is reduced in patients with schizophrenia and in patients with cognitive deficits [36,40]. NCAM’s role in the development of metabolic disorders has not previously been studied, except for the study of its expression in experimental mouse models of type 2 diabetes and the association of genetic variants at NCAM locus with lipid metabolism disorders [38,67]. This is the first study known to us of the influence of MetS on peripheral CAM levels in an adequately sized population of people with schizophrenia of homogeneous ethnicity. Our pilot study does not allow us to clarify the mechanisms of changes in CAMs in metabolic syndrome in patients with schizophrenia due to several limitations. A limitation is the trans-sectional nature of our investigation and the existence of a variety of differences between groups. Moreover, the clinical syndrome of schizophrenia has a heterogeneous biological character, and the patients were treated with a variety of antipsychotics over a long period of time. For this, medication history cannot be standardized, and it is usually not known. This increases the need for intervention studies. However, the obtained preliminary results demonstrate a violation of leukocyte/vascular interactions, which manifests itself in an increase in sICAM-1 and a decrease in sVCAM-1, which can be identified as a novel pattern of dysregulation in the combination of metabolic syndrome and schizophrenia. ## 5. Conclusions Our findings are consistent with reported high levels of CAMs and of some cytokines in patients with MetS [8], suggesting that MetS is associated with endothelial dysfunction along with other components of inflammation. We can hypothesize that through these endothelial components of peripheral inflammatory processes, MetS induces intracerebral neuroinflammatory changes that may participate in the pathophysiology of MetS itself and of schizophrenia, but further investigation is needed to test this theory. ## References 1. Sugawara N., Yasui-Furukori N., Sato Y., Umeda T., Kishida I., Yamashita H., Saito M., Furukori H., Nakagami T., Hatakeyama M.. 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--- title: Impact of Caloric Restriction and Exercise on Trimethylamine N-Oxide Metabolism in Women with Obesity authors: - Daniel J. Battillo - Steven K. Malin journal: Nutrients year: 2023 pmcid: PMC10058428 doi: 10.3390/nu15061455 license: CC BY 4.0 --- # Impact of Caloric Restriction and Exercise on Trimethylamine N-Oxide Metabolism in Women with Obesity ## Abstract Trimethylamine N-oxide (TMAO) is linked to cardiovascular disease (CVD) through partly altered central hemodynamics. We sought to examine if a low-calorie diet plus interval exercise (LCD+INT) intervention reduces TMAO more than a low-calorie diet (LCD) program alone in relation to hemodynamics, prior to clinically meaningful weight loss. Women with obesity were randomized to 2 weeks of LCD ($$n = 12$$, ~1200 kcal/d) or LCD+INT ($$n = 11$$; 60 min/d, 3 min at $90\%$ and $50\%$ HRpeak, respectively). A 180 min 75 g OGTT was performed to assess fasting TMAO and precursors (carnitine, choline, betaine, and trimethylamine (TMA)) as well as insulin sensitivity. Pulse wave analysis (applanation tonometry) including augmentation index (AIx75), pulse pressure amplification (PPA), forward (Pf) and backward pressure (Pb) waveforms, and reflection magnitude (RM) at 0, 60, 120, and 180 min was also analyzed. LCD and LCD+INT comparably reduced weight ($p \leq 0.01$), fasting glucose ($$p \leq 0.05$$), insulin tAUC180min ($p \leq 0.01$), choline ($p \leq 0.01$), and Pf ($$p \leq 0.04$$). Only LCD+INT increased VO2peak ($$p \leq 0.03$$). Despite no overall treatment effect, a high baseline TMAO was associated with decreased TMAO (r = −0.45, $$p \leq 0.03$$). Reduced TMAO was related to increased fasting PPA (r = −0.48, $$p \leq 0.03$$). Lowered TMA and carnitine correlated with higher fasting RM (r = −0.64 and r = −0.59, both $p \leq 0.01$) and reduced 120 min Pf (both, $r = 0.68$, $p \leq 0.01$). Overall, treatments did not lower TMAO. Yet, people with high TMAO pre-treatment reduced TMAO after LCD, with and without INT, in relation to aortic waveforms. ## 1. Introduction Cardiovascular disease (CVD) is a leading cause of death worldwide [1]. The gut microbiome has recently been implicated as an important mediator of atherosclerosis and vascular dysfunction. One CVD risk mediator that has garnered particular attention is trimethylamine N-oxide (TMAO). TMAO is a gut-derived metabolite produced largely from dietary sources such as meat, fish, and eggs that are rich in choline, carnitine, and betaine. These later metabolites are metabolized by gut bacteria to form trimethylamine (TMA) via TMA lyase [2]. In turn, TMA is oxidized in the liver by hepatic flavin monooxygenases, particularly FMO3, to form TMAO [3]. High TMAO levels are clinically concerning because it is linked to foam cell production, inflammation, and endothelial dysfunction, all of which promote arterial stiffness [3,4,5]. Indeed, TMAO has been associated with obesity, type 2 diabetes, and cardiovascular disease as well as hypertension [6,7,8]. However, identification of optimal therapeutic means to counteract TMAO levels and CVD risk remains unclear. Lifestyle modification consisting of diet and exercise are first line therapies for reducing CVD risk. Dietary intake has been a primary interest in reducing TMAO production and concentration, given the association between carnitine and choline consumption with TMA metabolism by bacteria in the gut. In particular, diets low in red meat reduce plasma TMAO, and individuals adhering to vegetarian diets demonstrate lower TMA [9,10]. Not surprisingly, hypocaloric diets have also been proposed to reduce TMAO, through both lower animal product consumption and overall caloric restriction [11]. Alternatively, aerobic exercise may reduce CVD risk through improvements to gut health and microbiota [12,13]. Some exercise studies, including [14], but not all [15] report reduced plasma TMAO levels. The discrepancy between exercise studies on TMAO is unclear but increased moderate to vigorous physical activity is associated with lower TMAO levels in older individuals [16]. These later findings suggest exercise may act to lower TMAO through a distinct fitness-related mechanism, compared with diet. Interestingly, Erikson et al. [ 14] showed that a hypocaloric diet plus exercise for 12 weeks lowered TMAO more effectively than exercise alone in older men and women. However, weight loss was significantly greater following diet plus exercise, thereby confounding whether the diet per se or additional weight loss promoted TMAO reduction. Further, both men and women were studied, and recent work highlights the potential of sex differences in the gut microbiome [17]. We recently reported that a low-calorie diet (LCD) was similarly effective at reducing aortic waveforms when compared with an LCD plus interval exercise (LCD+INT) treatment matched on energy availability, in middle-aged women [18]. Whether TMAO metabolism improves comparably following LCD or LCD+INT, in relation to vascular function in middle-aged women, is unknown. Therefore, we tested the hypothesis that LCD+INT would reduce plasma TMAO comparably to LCD, and this change in TMAO metabolism would relate to improved central hemodynamics. ## 2. Methods Participants. Twenty-three sedentary women with obesity (48.4 ± 2.4 yr; 37.9 ± 1.4 kg/m2; Table 1) were recruited from the local community via advertisements. Individuals were excluded if physically active (>60 min/wk), pregnant or nursing, on medications known to affect glucose metabolism (e.g., biguanides, insulin, TZDs, etc.) and/or blood pressure (e.g., ACE-inhibitors, beta-blockers, etc.), participated in smoking with the previous 2 years, or had an unstable weight over the prior six months (>2 kg variation). Menses status was documented (LCD: 5 post-menopausal, 2 irregular menses; LCD+INT: 7 post-menopausal, 1 irregular menses) but not controlled for, provided no women took hormone replacement therapy. Further, all participants underwent fasted blood work and a routine physical to confirm no indication of chronic disease (e.g., renal, hepatic, and cardiovascular) and participation safety. Individuals provided written and verbal informed consent before participation as approved by the University of Virginia Institutional Review Board (IRB # 18316). Body Composition and Aerobic Fitness. Fat mass and fat-free mass (FFM) were determined using air displacement plethysmography (BodPod, Concord, CA, USA), and waist circumference (WC) was measured 2 cm above the umbilicus using a soft tape measure. Peak oxygen consumption (VO2peak) and heart rate (HRpeak) were determined using a continuous incremental cycle ergometer test and indirect calorimetry (Carefusion, Vmax CART, Yorba Linda, CA, USA). VO2peak criteria included a cadence < 60 rpm, RER > 1.1 and volitional fatigue. Oral Glucose Tolerance Test. Participants reported to the Clinical Research Unit (CRU) after an approximate 10 hr overnight fast. Individuals were instructed to refrain from strenuous exercise, medications, caffeine, and alcohol consumption for 24 h. An intravenous catheter was placed in the right antecubital fossa for blood draws to determine glucose and hormonal responses during a 75 g oral glucose load. Fasting blood was collected to measure levels of TMAO, TMA, carnitine, betaine, and choline. Blood draws were subsequently collected at 30, 60, 90, 120, and 180 min to measure glucose tolerance and insulin sensitivity as estimated by total area under the curve (tAUC) calculations using the trapezoidal model. Aortic waveforms were measured at 0, 60, 120, and 180 min (see details below). Post-intervention assessments were obtained about 24 h after the last training session. Pulse Waveform Analysis. The SphygmoCor XCEL system (AtCor Medical, Itasca, IL, USA) was used to characterize hemodynamic and aortic waveform responses as previously described [18]. This characterization included brachial systolic (bSBP), diastolic (bDBP), and pulse pressure (bPP), central systolic (cSBP), diastolic (cDBP), and pulse pressure (cPP), heart rate (HR), augmentation pressure (AP), and index (AIx) as well as wave convolution aspects of forward (Pf) and backward (Pb) pressure and reflection magnitude (RM). Pulse pressure amplification (PPA) was calculated as the ratio of bPP to cPP. Augmentation index was corrected to a standard HR of 75 bpm using the manufacturer’s software. All measurements were obtained while individuals were laying quietly in the semi-supine position in a temperature-controlled room. Low-Calorie Diet. Participants were instructed to record their ad-libitum dietary intake for 3 days prior to pre-intervention testing. Subjects underwent 13-day LCD (1000–1200 kcal/d) based on pre-operative diets recommended to obese adults undergoing bariatric surgery. Meal replacement shakes were given to participants at breakfast and lunch (Ensure® Abbott Laboratories, USA, 8 fl. Oz; providing 160 kcal, 16 g protein, 2 g fat, 19 g CHO). Menus detailing options for low-kcal snacks and dinners not exceeding 600 kcal (e.g., lean protein with vegetables) were provided. To assess compliance and caloric intake, 13-day food records were assessed and averaged from the course of the intervention. Empty shake containers were also collected to verify consumption. Additionally, food logs were recorded in the 3 days preceding clinical testing before and after the intervention. Food intake was assessed using ESHA (Version 11.1, Salem, OR, USA), and pre- and post-intervention changes are reported. Exercise Training. Participants randomized to LCD+INT completed 12 supervised INT sessions over 13 days. Exercise duration was progressively ramped up, such that participants completed 30 and 45 min of INT on day 1 and 2, respectively, and 60 min of exercise per session thereafter, with one rest day over the 13 days. Exercise sessions consisted of subjects cycling for 3 min at $50\%$ heart rate peak (HRpeak) to warm up, followed by alternating 3 min periods of cycling at $90\%$ and $50\%$ of HRpeak for the 60 min session as previously described [18]. Participants completed a light 5 min cooldown on the cycle to facilitate HR recovery. The study team completed daily check-ins with participants to ensure they were not experiencing excessive soreness or overuse injuries. A mixed-meal shake (Ensure® Abbott Laboratories, USA, 8 fl. Oz; providing 350 kcal, 13 g protein, 11 g fat, 50 g CHO) was provided after each exercise in efforts to equate energy availability between treatments. Biochemical Analysis. Plasma glucose was measured immediately following collection using the glucose oxidase method (YSI Instruments 2300, Yellow Spring, OH, USA). Fasting blood samples were collected in EDTA tubes and centrifuged at 4 °C for 10 min at 3000 RPM. All bloods were frozen at −80 °C until further analysis. Plasma betaine, choline, carnitine, TMA, and TMAO were determined by liquid chromatography tandem mass spectrometry as described by Koeth et al. [ 19] and Kirsh et al. [ 20]. Data acquisition of TMAO metabolism was carried out using selective ion monitoring, and the concentration of each analyte was calculated against an 8-point standard curve for that analyte. Statistical Analysis. Data were analyzed using GraphPad Prism version 9 (GraphPad Software, San Diego, CA, USA). Normality was assessed using the Shapiro–Wilk test, and non-normally distributed data were log-transformed for analysis. Baseline differences between groups were analyzed using Student’s unpaired t test. Repeated measures analysis of variance (ANOVA) was used to determine group x time differences. Change in TMAO pre-intervention to post-intervention was calculated, and participants were categorized as either responders (decreased plasma TMAO) or non-responders (increased plasma TMAO) following their respective interventions. There were no baseline or post-intervention differences in variables of interest between the responder and non-responder groups. Pearson or Spearman rank correlations were used to assess normally and non-normally distributed outcomes, respectively. Statistical significance was accepted as p ≤ 0.05 and data are presented as mean ± SEM. ## 3. Results Participant Characteristics and Diet. LCD and LCD+INT comparably reduced weight and body fat (all $p \leq 0.01$; Table 1). There were no significant changes in FFM following either treatment ($$p \leq 0.78$$; Table 1). Additionally, only LCD+INT increased VO2peak, compared to a slight decrease in LCD ($$p \leq 0.03$$; Table 1). LCD and LCD+INT reduced both fasting glucose and fasting insulin comparably ($$p \leq 0.05$$ and $$p \leq 0.03$$, respectively; Table 1), and each treatment reduced insulin tAUC180min ($p \leq 0.01$; Table 1). While both groups decreased fasting LDL cholesterol ($p \leq 0.01$), only LCD+INT increased HDL cholesterol, compared to a reduction in LCD ($p \leq 0.01$). Both treatments reduced caloric intake similarly ($p \leq 0.01$), that was explained by reductions in carbohydrates ($$p \leq 0.05$$), fat ($p \leq 0.01$), and protein ($$p \leq 0.03$$, Table 2). Hemodynamics. Fasting Pf was lowered after both LCD and LCD+INT ($$p \leq 0.04$$; Table 3), independent of changes in RM ($$p \leq 0.45$$) and AIx75 ($$p \leq 0.28$$). There were no changes in fasting cSBP and cDBP ($$p \leq 0.48$$ and $$p \leq 0.30$$, respectively; Table 3) or bSBP and bDBP ($$p \leq 0.47$$ and $$p \leq 0.39$$, respectively; Table 3), although there was a trending reduction in AIx75 tAUC ($$p \leq 0.08$$)180min following each intervention. Further, there was no difference in fasting PPA ($$p \leq 0.90$$), but a trending reduction in fasting HR ($$p \leq 0.08$$; Table 3), following each intervention. TMAO Metabolism. There were no differences in TMAO ($$p \leq 0.74$$), TMA ($$p \leq 0.62$$), betaine ($$p \leq 0.54$$), or carnitine ($$p \leq 0.89$$) following either intervention, whereas choline was reduced after LCD and LCD+INT ($p \leq 0.01$; Table 4). Interestingly, a higher baseline TMAO was associated with greater reductions in TMAO following both LCD and LCD+INT (r = −0.45, $$p \leq 0.03$$; Figure 1). Furthermore, decreased TMAO was associated with increased fasting PPA (r = −0.48, $$p \leq 0.03$$). Reductions in fasting carnitine correlated with increased fasting RM (r = −0.59, $p \leq 0.01$) as well as lowered 120 min Pf ($r = 0.68$, $p \leq 0.01$). Similarly, lowered fasting TMA was also linked to reduced 120 min Pf ($r = 0.68$, $p \leq 0.01$) and greater fasting RM (r = −0.64, $p \leq 0.01$; Figure 2). Additionally, older age was associated with higher fasting TMAO before ($r = 0.58$, $p \leq 0.01$) but not after the intervention (r = −0.26, $$p \leq 0.23$$). ## 4. Discussion The primary finding from this present study is that neither LCD nor LCD+INT was effective overall at reducing plasma TMAO in women with obesity, despite lowering plasma choline. However, we did observe that both treatments were effective at reducing TMAO in women with higher baseline levels. This is consistent with prior work demonstrating that participants with a median plasma TMAO level below 4.72 μM were free of CVD [21,22]. Thus, it is not entirely surprising that our lifestyle treatment had less robust changes across participants, given the average levels were 3.46 ± 0.4 μM and 4.16 ± 0.7 μM in LCD and LCD+INT, respectively. These discrepancies are interesting since other work has demonstrated that both caloric restriction and specific macronutrient-targeted diets are effective at reducing circulating TMAO [11,14,23]. However, this previous dietary work was mainly focused on vegan or low-fat diets, which potentially reduced animal product consumption and subsequent choline and carnitine intake more than the present study. While both groups in the present study saw reductions in all macronutrients, it is difficult to discern the extent of our observed dietary alterations, compared to these other studies [23,24]. Nonetheless, we did detect statistical reductions in circulating choline concentrations, which suggests that caloric restriction contributes to reduced TMAO precursor metabolites that influence TMAO. Indeed, our data are consistent with caloric restriction reducing choline levels in individuals with overweight and obesity [25]. This highlights that other precursors or factors may drive TMAO or have compensated to maintain TMAO levels. Regardless, in the present study, we had posited that exercise would augment the effect of an LCD to reduce TMAO, given some [16] studies demonstrated that exercise had a beneficial effect on plasma TMAO levels. Despite women cycling for 60 min a day over about 2 weeks in the present study, we did not detect statistical changes in TMAO. While longer-term exercise interventions may be required to elicit reductions in TMAO, it is worth noting that Erikson et al. [ 14] also did not detect changes in TMAO following 12 weeks of aerobic exercise training in older adults. Further, recent cross-sectional work in aerobically fit versus unfit individuals did not report TMAO differences [15]. It is difficult to reconcile why exercise studies are mixed on reducing TMAO, but our work points towards pre-treatment circulating TMAO concentrations as an important factor. Indeed, the reduction in TMAO was associated with increased fasting PPA. This association is clinically relevant as higher PPA suggests reduced central pulse pressure, compared with brachial pulse pressure, thereby reducing workload of the heart to propel blood into systemic circulation [26]. TMAO precursors are relevant to disease development, as choline, TMA, and carnitine levels have been associated with increased CVD risk [19,27,28]. Interestingly, LCD and LCD+INT similarly reduced plasma choline in the present study. The relevance of this reduction, though, is unknown, given lower choline levels did not associate with changes in aortic waveforms or blood pressure. It is worth noting that the relationship between dietary choline and plasma choline can differ among individuals, given the wide diversity of gut microbiota [29]. Therefore, it is possible that our LCD may have impacted how dietary choline was metabolized or that choline alone was not of sufficient concentration to influence vascular outcomes. In either case, reductions in TMA and carnitine were related to lower fasting RM after both treatments. RM is a ratio of the backward reflected wave (Pb) to the forward reflected wave (Pf). A higher RM suggests reduced effort of the heart to pump blood to the periphery [30]. In the present study, we observed a significant reduction in fasting Pf in both groups but no change in Pb. Collectively, with no change in Pb, these outcomes suggest that lower TMAO precursors may relate to a decreased left ventricular ejection fraction to support cardiac muscle function [31]. Conversely, it is important to recognize that the effect of carnitine is somewhat equivocal, compared to TMA, since it has been purported to reduce oxidative stress [32,33] and lower systolic and mean arterial pressures [34]. In fact, carnitine supplementation can increase left ventricular ejection fraction in patients with cardiomyopathy [35,36]. In our study, these later observations would be consistent with lower carnitine being related to lower RM and 120 min Pf as well as AIx75 tAUC180min. Since there were not equivalent reductions in brachial blood pressure after either treatment, our work highlights that the changes we see are likely at the level of the heart, rather than the peripheral vasculature. Somewhat surprisingly, post-prandial heart rate and bDBP tAUC180min tended to rise after LCD+INT, compared to reductions following LCD. While exercise may have unique influences on central hemodynamics, compared with LCD, to maintain blood pressure during the fed state [37], these collective data highlight that reductions in TMA, choline, and carnitine appear important for aortic waveforms after lifestyle treatment in women. This observation is clinically relevant to targeting TMAO and its precursors in CVD etiology, as it conveys that TMAO has both central and peripheral effects on heart function and hemodynamics in women. This study has limitations that may influence our interpretations. The present investigation only included women, so the results may not be generalizable to men. In fact, studies with similarly aged male and female cohorts have demonstrated lower TMAO levels in females than men [38] and may help explain the lower TMAO levels on average. Additionally, our sample size is modest, despite other lifestyle investigations on plasma TMAO that used similar sized cohorts and reported that lifestyle reduced TMAO [11,14]. Aging is also a consideration of plasma TMAO levels, as TMAO has been demonstrated to increase with age, independent of other CVD risk factors (e.g., systolic blood pressure and carotid–femoral PWV) [2,39]. As such, menopausal status should be considered in future work. In line with TMAO correlating with age at baseline ($r = 0.58$, $p \leq 0.01$), post-menopausal women would be anticipated to have more TMAO than premenopausal women. While this difference in menopausal status could influence ability to identify treatment effects, there was no association with age and the change in TMAO after the intervention. This suggests both LCD and LCD+INT potentially mitigate age-related CVD risk, regardless of menopausal status. Further, we were not able to quantify dietary intake of precursors such as choline, carnitine, and betaine in the study dietary logs due to technical difficulties with the software. Nevertheless, a strength of the study is that we were able to characterize TMAO-related precursors that have not been previously reported. Another consideration is that we only measured TMAO and its precursors in the fasted state of a 75 g OGTT. However, 5 days of a high-fat diet did not influence fasting or post-prandial TMAO levels in either sedentary- or endurance-trained individuals [15]. This suggests that TMAO is unlikely acutely affected by diet, particularly when TMAO precursors are not consumed. Additionally, TMAO is cleared by the kidney and metabolized in the liver [40]. Although we did not examine kidney or liver function with regard to TMAO, per se, our clinical labs indicate that people had relatively normal kidney and liver function. Further, FMO3 action in the liver mediates the oxidation of TMA to TMAO and is influenced at least in part by liver insulin sensitivity [41]. While we did not measure FMO3 to discern TMA metabolism in the gut and TMAO oxidation in the liver prior to systemic circulation, neither TMA nor TMAO were altered in this study, despite reductions in fasting glucose and insulin. Given the liver is the primary organ regulating fasting glucose homeostasis [42], our work suggests TMAO metabolism is unaltered independent of lower hepatic insulin resistance. In conclusion, overall, neither LCD nor LCD+INT for 2 weeks was effective at reducing plasma TMAO in women with obesity. However, in women with higher circulating baseline TMAO levels, both treatments lowered plasma TMAO. This is consistent with our observation that LCD, with or without INT treatment, is effective at lowering choline, a key precursor to TMAO. 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--- title: A Novel Based Synthesis of Silver/Silver Chloride Nanoparticles from Stachys emodi Efficiently Controls Erwinia carotovora, the Causal Agent of Blackleg and Soft Rot of Potato authors: - Shazia Dilbar - Hassan Sher - Dalal Nasser Binjawhar - Ahmad Ali - Iftikhar Ali journal: Molecules year: 2023 pmcid: PMC10058436 doi: 10.3390/molecules28062500 license: CC BY 4.0 --- # A Novel Based Synthesis of Silver/Silver Chloride Nanoparticles from Stachys emodi Efficiently Controls Erwinia carotovora, the Causal Agent of Blackleg and Soft Rot of Potato ## Abstract In recent years, the biological synthesis of silver nanoparticles has captured researchers’ attention due to their unique chemical, physical and biological properties. In this study, we report an efficient, nonhazardous, and eco-friendly method for the production of antibacterial silver/silver chloride nanoparticles utilizing the leaf extract of Stachys emodi. The synthesis of se-Ag/AgClNPs was confirmed using UV-visible spectroscopy, DPPH free radical scavenging activity, Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and X-ray diffraction (XRD). An intense peak absorbance was observed at 437 nm from the UV-visible analysis. The Stachys emodi extract showed the highest DPPH scavenging activity ($89.4\%$). FTIR analysis detected various bands that indicated the presence of important functional groups. The SEM morphological study revealed spherical-shaped nanoparticles having a size ranging from 20 to 70 nm. The XRD pattern showed the formation of a spherical crystal of NPs. The antibacterial activity performed against Erwinia carotovora showed the maximum inhibition by centrifuged silver nanoparticles alone (se-Ag/AgClNPs) and in combination with leaf extract (se-Ag/AgClNPs + LE) and leaf extract (LE) of $98\%$, $93\%$, and $62\%$ respectively. These findings suggested that biosynthesized NPs can be used to control plant pathogens effectively. ## 1. Introduction Plant growth and development are affected by various biotic and abiotic factors affecting its yield and quality [1]. It is estimated that the world population is going to increase up to 10 billion by 2050 which will pressurize farmers for nutritious and safe food production in near future. The present food production systems are mainly threatened by diseases, pests, microorganisms, drought, and sudden climate changes [2]. Among these, phytopathogens are causing serious diseases in agricultural crops, resulting in global food insecurity [3]. The increased demand for vegetables and fruits such as potatoes, tomatoes, and eggplants has employed about 800 million individuals and contributes more than $33\%$ of the world’s agricultural production [4]. The agricultural productivity of vegetables and fruits decreases due to the diseases caused by phytopathogens, which in turn increase the market price of such products [5]. Potato (Solanum tuberosum L.) is considered to be an attractive crop in the agricultural sector due to its high nutritional value as it is a good source of vitamins, proteins, energy, minerals, and carbohydrates [6]. Globally, potato is one of the most consumed foods, occupying fourth position after corn, rice, and wheat [7]. Potato is an important crop; it is not only utilized as a source of food, but as a feedstock for other industrial products. Potato crop yield is not only affected by abiotic stress such as high radiation, heat and cold stress, air pollutants (nitrogen dioxide and ozone), and drought stress, but also by biotic stress such as viral, fungal and bacterial diseases [8]. Potato crop is badly affected by various pathogenic diseases which lead to low production. The most prominent biotic factor which could affect the quantity and quality of potato are the bacterial diseases blackleg and soft rot caused by Erwinia carotovora. Erwinia carotovora is a Gram-negative bacterium with rod-shaped cells which decay most of the vegetables and fruits in the field and during shipment or its storage. These edibles are contaminated by the E. carotovora after rainfall and irrigation [9]. E. carotovora is one of the plant pathogens known to cause blackleg and soft rot diseases in potato crop [10]. A spreading maceration of the tuber tissue, frequently with a creamy consistency that darkens when exposed to air, is a sign of soft rot [11]. The disease is known as either potato blackleg disease or aerial stem rot when it affects the plant’s aerial components; its symptoms often start as a dark discoloration at the base of stem, at soil line and progress to the stems from infected tubers [12]. E. carotovora gain entry into the plant through some injuries and degrade its cell wall, followed by tissue maceration through pectolytic enzymes which lead to the soft rotting of the stems and fruits [13]. Globally, potato yield is affected annually by pests, weeds, and insects as well as diseases caused by different viruses, bacteria and fungi [14]. Viral, bacterial, fungal, and other plant diseases result in an annual loss of USD 1 billion worldwide [15]. Conventional methods are not useful enough to control these pathogens, while the frequent use of synthetic pesticides to manage plant diseases results in environmental pollution [16]. Several strategies are in use against phytopathogens for the control of various crop diseases for better crop production. The application of commercial pesticides has benefited farmers in one way by minimizing the effect of different crops’ ailments, but on the other hand, their frequent use leads to major upsets to human health as well as some plant-friendly, soil-borne microorganisms [17]. Nanotechnology deals with the manipulation and study of nanosized particles which can be used across various fields of science and technology [18]. Nanotechnology is of special concern in almost all fields of science and technology mainly because of the distinct chemical, biological, and physical characteristics of nanoparticles [19]. As a result of recent scientific advancements, metal nanoparticles are practical for producing drugs which can be used in various medical and industrial areas. Nanotechnology and nanoparticles have dominated the current generation which has attracted applications in daily life and technology to medicine, cosmetics, and space technology [20]. Nanobiotechnology is a modern field in which bulk materials are processed and converted into small particles having a size of 1–100 nm [21]. Nanobiotechnology has broad applications in the agricultural sector, e.g., to combat diseases and enhance crop productivity [22]. Recently, the use of nanobiotechnology in the management of plant diseases has gained substantial attention [23] due to the important role of nanomaterials in the control of plant pathogenic microorganisms and, thus, an improvement in crop productivity [24,25]. Nanobiotechnology possesses huge potential for the production of novel products which are advantageous to the environment as well as human health [26]. The green synthesis of nanoparticles by using medicinal plants has preference over physical and chemical methods as this method is eco-friendly, economic, and more effective [27]. Nanoparticles can be synthesized by using metals or nonmetals; however, metallic nanoparticles can be fabricated by using copper, cobalt, gold, silver, nickel etc. Metallic nanoparticles have received more attention because of their specific electrical, catalytic, and optical properties. Silver NPs are one of the main crucial and fabulous nanoparticles among several metallic nanoparticles which are involved in biomedical uses. Ag/AgClNPs play a noticeable role in nanoscience and nanotechnology, specifically in nanomedicine [28]. Among all nanoparticles, AgNPs hold a superior position due to their unique characters. Consequently, these nanoparticles have various applications including nanodevice fabrication, food technology, mechanics, biosensing, medicine, agricultural textiles, drug delivery, catalysis, electronics, and optics [29]. Because of the antiviral, antibacterial, and antifungal properties of nanoparticles, their use is increasing day by day in the agricultural field. In the past, the ancient Greeks used silver for wound healing, to treat ulcers, and as a preservative for food and water. Silver nanoparticles are used in different fields such as bone healing, bone cement, dental applications, and wound healing due to their antibacterial, antiviral, anticancer, and antifungal properties. Silver nanoparticles are applied as insecticides, pesticides, and growth promoters and against abiotic stresses [30]. The genus Stachys is considered to be a rich source of important plant secondary chemicals having therapeutic and commercial uses. The biological activities of Stachys are associated with the presence of different phytochemicals in various parts of the plant. In general, more than 200 compounds from the Stachys genus have been identified, and they fall into the following significant chemical groups: terpenes (e.g., diterpenes, iridoids, and triterpenes), essential oils, polyphenols (e.g., phenylethanoid glycosides, flavone derivatives, and lignans), and phenolic acids [31,32]. Stachys belongs to the third-largest genus of the Lamiaceae family with approximately 300 species, which are mostly perennial herbs and small shrubs mostly confined to the temperate regions in the Mediterranean, Asia, Southern Africa, and America. Many Stachys spp. have been used as traditional medicines for thousands of years. Most of the Stachys species are consumed to cure asthma, gastrointestinal diseases, the common cold, skin diseases, inflammation, and anxiety [33,34]. The Stachys species has been used by the traditional people of Europe, Japan, Iran, and in Chinese folk medicine as a tonic and for the treatment of other diseases [32,35,36]. Stachys emodi, commonly known as silky woundwort, belongs to the largest Stachys genus of the family Labiatae. The plant is a perennial herb with an erect stem reaching 60 cm tall, having 3–6 × 2–3 cm leaves, with multiflowered verticillasters in the axils of the leaves. The plant is distributed from Afghanistan and Pakistan (Kashmir) to Bhutan and NW India [37]. This study was designed to synthesize se-Ag/AgClNPs and evaluate them for various antibacterial activities against E. carotovora, the causal agent of blackleg and soft rot diseases in potato. ## 2.1. DPPH Assay The widely used method for determining free radical scavenging uses DPPH, a free radical with great stability. The S. emodi plant extracts showed strong antioxidant activity when they were assayed through DPPH free radical scavenging activity. The results showed that the S. emodi plant extract exhibited the highest DPPH scavenging activity (89.4) for the 1000 µg/mL concentration. Similarly, the obtained results of the plant sample concentration were compared with those of standard ascorbic acid (Figure 1). ## 2.2. Characterization of Silver/Silver Chloride Nanoparticles The color of the solution started turning brown immediately after placing the solution in sunlight and turned completely dark brown after 20 min. This was due to the reduction of silver ion to silver/silver chloride nanoparticles in the reaction mixture [38]. The silver nanomaterial synthesis was achieved by using varying volumetric ratios (1:9, 2:8, 3:7, 4:6, 5:5, 6:4, 7:3, 8:2, and 9:1 v/v) of the S. emodi extract and silver nitrate solution. The UV-visible spectrum of the reaction mixture was recorded after 24 h. Nine various peaks were obtained for different ratios. The maximum absorbance was observed at 437 nm (Figure 2) and pH 11 for the 6:4 (v/v) ratio, where its pointed peak indicated the formation of spherical-shape (se-Ag/AgClNPs) silver/silver chloride nanoparticles [39]. The FTIR pattern was used to study the various functional groups which might be involved in se-Ag/AgClNP synthesis and could play an important role as a stabilizing agent. The FTIR spectral analysis showed various peaks for different functional groups. A small broad peak at 2035 cm−1 was observed due to C=C=N stretching, which could be a ketenimine-like compound. A small peak at 1975 cm−1 was observed due to C-H bending of the possible aromatic compound. A broad peak was observed at 1576 cm−1 for the N-H bending of the amine compound (Figure 3). Scanning electron microscopic analysis was used to verify the morphology and size of the synthesized silver/silver chloride nanoparticles. The obtained SEM results showed that the produced nanoparticles had random morphology with spherical-shaped structures detected in the micrograph. The obtained results showed the size of the synthesized nanoparticles was in the range of 20 to 70 nm (Figure 4). The crystalline nature of the sliver/silver chloride nanoparticles was confirmed by using XRD analysis at a 2θ angle ranging from 10° to 80°. The XRD diffraction peaks situated at 38.10°, 44.1°, 64.41°, and 77.35° are indexed to the [111], [200], [220], and [311] crystalline planes of pure Ag nanoparticles with a face-centered cubic structure according to the reference database in the Joint Committee on Powder Diffraction Standards (JCPDS) library (JCPDS, file No. 04-0783). The other dominant and clear five peaks at 27.71°, 32.14°, 46.11°, 54.73°, and 57.40° are attributed to planes [210], [122], [231], [142], and [241] of the cubic phase of silver chloride (AgCl) crystal (JCPDS No. 31-1238). The XRD results show that the biosynthesized Ag/AgClNPs were in the shape of spherical crystals (Figure 5). The Debye–Scherrer equation measured the average crystallite size as 38 nm for the bio-fabricated se-Ag/AgClNPs which validates SEM results. ## 2.3. Antibacterial Activity The antibacterial activity against E. carotovora resulted in significant inhibition by various concentrations (500 µg mL−1, 250 µg mL−1, 100 µg mL−1, 80 µg mL−1, 50 µg mL−1, 20 µg mL−1, and 10 µg mL−1). The centrifuged nanoparticles in combination with the leaf extract (se-Ag/AgClNPs + LE) at a concentration of 500 µg mL−1 showed a maximum inhibition of $98\%$. The centrifuged nanoparticles alone (se-Ag/AgClNPs) inhibited the growth of the bacteria by $93\%$, while the leaf extract alone (LE) showed an optimal inhibition of $62\%$. The control treatment showed no inhibition of the cell growth of E. carotovora. The inhibition patterns of the various concentrations of se-Ag/AgClNPs + PE, se-Ag/AgClNPs, and PE are shown in Figure 6. ## 3. Discussion Plants produce different types of secondary metabolites which are potentially active against various insects and phytopathogens. As compared to commercial fungicides and pesticides, medicinal plants have more antifungal and antibacterial properties due to the presence of secondary metabolites which are more active in controlling plant diseases and are eco-friendly with fewer side effects [40]. As compared to commercial fungicides and pesticides, medicinal plants have more antifungal and antibacterial properties due to the presence of secondary metabolites which are more active in controlling plant diseases and are eco-friendly with fewer side effects [41]. The spectrophotometer peak is dependent on the size of the nanoparticles. A smaller particle size represents peaks at a shorter wavelength while a larger particle size indicates a longer wavelength peak [42]. Our findings regarding UV-visible analysis were in compliance with those of previously described studies [43] in which silver/silver chloride nanoparticle peaks were observed at around 420 nm. Similar results were also reported by Patra et al. [ 44] using Pisum sativum plant extract and Kup et al. [ 45] using a plant extract of Aesculus hippocastanum. They used various techniques to characterize their synthesized nanomaterials. According to the UV-visible analysis, the formation of Ag-NPs was observed at a wavelength above 420 nm. The color change in the mixture from violet blue to yellow proved the reduction of DPPH radical by the antioxidant compounds in plants [46]. This is due to the potential of methanolic extract in S. emodi plants as antioxidants. The highest DPPH free radical scavenging activity was shown by the plant extract at a concentration of 1000 µg/mL, which was $89.4\%$. Similar results were shown by the previous studies by Tatarczak et al. [ 47] where the DPPH radical was reduced by the phytochemicals in plants, proving its strong antioxidant activity. Khan et al. [ 48] synthesized Au/MgO nanomaterial by using Tagetes minuta which exhibit excellent antioxidant activity with $82\%$ scavenging capability. FT-IR revealed that stretching in the band from 3000 to 2000 cm−1 revealed good bonding between the functional groups and the Ag. The observed FTIR spectrum of the synthesized nanoparticles was in complete agreement with previous studies [49]. The FTIR pattern showed the presence of biological groups in the S. emodi extracts which could be involved in reducing and capping the biosynthesized nanoparticles (se-Ag/AgClNPs). The agents which could be responsible for the bioreduction and stabilization of silver ions into silver NPs present in S. emodi extract were confirmed by the FTIR pattern. The obtained bands of FTIR could be attributed mainly to the phenols, terpenoids, and flavonoids present in S. emodi plant extracts. The present study agreed with the study by Mohamed et al. [ 50] which also suggested that flavonoids, phenols, and proteins could be the reducing and stabilizing agents of silver/silver chloride nanoparticles. Our SEM observation of the synthesized nanoparticles was in complete accordance with that previously observed by Khan et al. [ 51], who prepared silver nanoparticles by using Mentha spicata. Their SEM results at different magnifications showed spherical-shaped particles with size ranges from 21 to 82 nm. According to Yousaf et al. [ 52], silver nanoparticles were synthesized from the extracts of Achillea millefolium L. Their SEM results had an average diameter of 14.27, 18.49, and 20.77 nm with spherical, cubical, and rectangular morphology which positively correlates with the present study. This study suggested that the obtained se-Ag/AgClNPs were capped by biomolecules present in the S.emodi plant extracts and these metabolites may be manipulated by metallic silver to biogenically synthesize silver/silver chloride nanoparticles. The S. emodi NPs’ size could also be detected from the sharpness and broadness of the XRD peaks. The Figure 5 peaks show that se-Ag/AgClNPs were in the nanosize range. Our XRD results were generally in accordance with those XRD patterns previously described by Hashemi et al. [ 53] which had the same peaks. Our results are in positive agreement with Sing et al. [ 54]; their XRD peaks were very strong and revealed that the synthesized Ag/AgClNPs were in the nanosize range and had a crystalline nature. Plants belonging to the Stachys genus are very medicinal and have been used since early eras as traditional medicine to cure many problems such as gout, cough, fever, asthma, earaches, genital tumor, abdominal cramps, menstrual disorder, and dizziness. Advanced research shows that Stachys genus plant extracts have strong antifungal, antibacterial, antinephritic, antioxidant, and anti-inflammatory activities [31]. Previously, Shakeri et al. [ 55] reported the strong antibacterial efficacy of Stachys against Staphylococcus aureus, Bacillus cereus, Staphylococcus epidermidis, Escherichia coli, Salmonella typhi, and Pseudomonas aeruginosa. Jan et al. [ 56] also observed the antibacterial effects of Stachys against various bacteria. They showed that ethyl acetate, aqueous, n-hexane, and ethanolic extracts of the Stachys parviflora plant showed strong antimicrobial activity against six bacteria (Bacillus atrophaeus, Staphylococcus aureus, Pseudomonas aeruginosa, Salmonella typhi, Escherichia coli, and Bacillus subtilis) and one fungi (Candida albicans). The antibacterial activity of the study showed similar results to those previously reported studies that suggested that biosynthesized Ag/AgClNPs (by using grape pomace aqueous extract) have potential in controlling the growth of E. carotovora [57]. E. carotovora is a Gram-negative bacterium which affects most vegetables and fruits in the field and during shipment or in storage [58]. E. carotovora infect the host plant through some injuries and degrade its cell wall, followed by tissue maceration leading to the soft rotting of stems and fruits [9,59]. In the current study, the antibacterial effect of the S. emodi leaf extracts (500 µg/mL–10 µg/mL) was tested against E. carotovora. High concentrations (500 µg/mL and 250 µg/mL) showed promising results against the bacteria while the lowest activity was observed for the lowest (10 µg/mL) concentration of the leaf extract. Similarly, high concentrations (500 µg /mL, 250 µg/mL, and 100 µg/mL) of plant-coated silver/silver chloride nanoparticles (se-Ag/AgClNPs + PE) had high antibacterial activity as compared to the lowest concentrations (80 µg/mL to 10 µg/mL). The activity of the centrifuged nanoparticles (se-Ag/AgClNPs) was high for the 500 µg/mL and 250 µg/mL concentrations. Overall, the activity of the plant-coated nanoparticles was superior to the centrifuged nanoparticles and plant extracts alone. This might be due to the synergism of secondary metabolites with silver ions which makes its activity more efficient. The antibacterial activities of the present study agreed with those of Arif et al. ’s study [38], in which silver nanoparticles synthesized from Euphorbia wallichii were tested against phytopathogens. Our study is in positive correlation with the previously reported study by Balachandar et al. [ 60] who studied the activities of biologically synthesized nanoparticles against various phytopathogens, and noticed a strong growth inhibition of the plant pathogens. NPs synthesized by using Eucalyptus camaldulensis were tested against various bacteria and were found to significantly reduce the Gram-negative bacteria growth. The antibacterial character of Ag/AgClNPs prepared from E. camaldulensis could be ascribed to the small particle size and high surface-to-volume ratio, which let the nanoparticles interact with bacterial membranes [61]. According to a proposed mechanism which describes how silver particles act, due to their small size and spherical shape, they can penetrate bacterial cell walls and can increase their permeability by bringing some structural changes; these changes include the generation of pores in the bacterial cell wall through reactive oxygen species production. Silver ions can also damage important cell enzymes, proteins, and nucleic acids of the bacteria, resulting in bacterial cell death [62]. ## 4.1. Preparation of Leaf Extract Healthy plant specimens were collected, washed thoroughly, and dried up at room temperature. The dried specimens were ground into a fine powder and used for the synthesis of silver/silver chloride nanoparticles. For the preparation of leaf extract, 1 g of the ground powder was mixed in 100 mL of distilled water and the solution was heated at 40–50 °C for 15 min on a hot plate. The solution was left to cool down and then it was filtered with the help of Whatman No. 1 filter paper (pore size of 11 µm) and was stored in a refrigerator at 4 °C for further use. ## 4.2. Antioxidant Activity The DPPH free radical scavenging capacity of the sample plant was determined according to the protocol of Govindappa et al. [ 63] with a minor modification. The plant solution was prepared by taking 10 mg of the powdered plant in 10 mL of methanol. Through the two-fold dilution of the plant stock solution, 5 different concentrations (1000 µg/mL, 500 µg/mL, 250 µg/mL, 125 µg/mL, and 62.5 µg/mL) were formed. The DPPH solution was already prepared and stored at room temperature in the dark. A total of 1 mL of the DPPH solution was added to 2 mL of these diluted samples of the plant extract and kept for incubation in the dark for 30 min. The absorbance of all concentrations was measured with a Multiskan TM Sky Microplate Spectrophotometer (MAN0018930, Santa Clara, CA, USA) at 517 nm while ascorbic acid was used as standard. The percent activity was calculated with the given formula. % antioxidant activity = (OD of the control − OD of the sample × 100)/control OD[1] ## 4.3. Biosynthesis of Silver/Silver Chloride Nanoparticles Following the procedures of Arif et al. [ 63] and Ul Haq et al. [ 64] with certain modifications, the green synthesis of nanoparticles was accomplished. The diluted leaf extract (2.5 mg/mL) solution was mixed appropriately with silver nitrate (4 mM) solution at equal volume (1:1) and was kept under sunlight for 20 min. The mixture was adjusted at different pHs ranging from 6 to 12. For the separation of the synthesized Ag/AgClNPs, the solution was centrifuged (Centrifuge 5425, Eppendorf, Hamburg, Germany) at 15,000 rpm for 15 min. The residual settled material was collected in a distinct tube and was then dissolved in deionized water followed by centrifugation again at 12,000 rpm for 10 min. This was repeated multiple times and the obtained pure nanoparticles were subjected to various characterizations. ## 4.4. Characterization of Synthesized Particles The biosynthesis of se-Ag/AgClNPs was confirmed through various characterization techniques, which were as follows: Fourier transform infrared spectrophotometric analysis was carried out using an FTIR (Spectrum two-103385; Waltham, MA, USA) spectrophotometer equipped with ATR. The FTIR spectroscopic analysis was performed between the ranges of 4000 and 400 cm−1. The various functional groups were identified by comparing the observed peaks with an IR spectrum table. Scanning electron microscopy (JSM-5910, JEOL, Tokyo, Japan) was used to find out the morphology and distribution of the nanoparticles. The X-ray diffraction (XRD) analysis of the silver/silver chloride nanoparticles was carried out using an X-ray diffractometer (Model: X-3532, JEOL, Tokyo, Japan). The XRD patterns were evaluated to find out the peak intensity, position, and width. The mean crystallite size was measured using Debye–Scherrer’s formula. ## 4.5. Antibacterial Activity The antibacterial activity of the green synthesized se-Ag/AgClNPs against E. carotovora was accomplished using the methods of Ahmad et al. [ 65] with certain modifications. The freshly grown culture of E. carotovora was acquired from (FCBP-PB-421) First Fungal Culture Bank of Pakistan (FCBP), Institute of Agricultural Sciences (IAGS) University of Punjab, Lahore, Pakistan and inoculated in nutrient broth and placed overnight at 28 °C in an incubator (FTC-90E Velp Scientifica, Lombardia, Italy). The activity was implemented with a microtiter plate (96-well) assay with various concentrations (500 µg mL−1, 250 µg mL−1, 100 µg mL−1, 80 µg mL−1, 50 µg mL−1, 20 µg mL−1, and 10 µg mL−1) of centrifuged silver nanoparticles alone (se-Ag/AgClNPs) and in combination with leaf extract (se-Ag/AgClNPs + LE) and leaf extract (LE) alone. 150 µL concentration of each treatment and 150 µL of E. carotovora suspension were poured into each well of the microtiter plate. The control well was adjusted with bacterial suspension. The optical density (OD) at 600 nm was recorded immediately and placed in a shaking incubator for 24 h. After 24 h, the OD was again read at 600 nm and the bacterial growth inhibition was calculated using the given formula:Bacterial growth inhibition = Control − Treatment/Control × 100[2] ## 5. Conclusions In the present study, we showed the efficient biosynthesis of silver/silver chloride nanoparticles and their antibacterial screening against E. carotovora using S. emodi. The characterizations of the prepared nanoparticles showed a significant biosynthesis of stable silver/silver chloride nanoparticles. Our study showed that the size of the nanoparticles ranged from 20 to 70 nm with an average diameter of 38 nm. Moreover, the antibacterial activity resulted in the significant growth inhibition of E. carotovora by the biogenically synthesized silver/silver chloride nanoparticles. The study concluded that biosynthesized Ag/AgClNPs have the potential to control the growth of E. carotovora through in vitro activities. It is recommended to evaluate the potential of se-Ag/AgClNPs through in planta means. However, further studies should confirm the effectiveness of these nanoparticles against other plant pathogens to protect important crops. ## References 1. Ali M., Kim B., Belfield K.D., Norman D., Brennan M., Ali G.S.. Inhibition of. Phytopathology (2015) 105 1183-1190. PMID: 25871856 2. Rafique K., Rauf C.A., Gul A., Bux H., Memon R.A., Ali A., Farrakh S.. 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--- title: 'Adipose-Derived Stem Cells in Reinforced Collagen Gel: A Comparison between Two Approaches to Differentiation towards Smooth Muscle Cells' authors: - Elena Filova - Monika Supova - Adam Eckhardt - Marek Vrbacky - Andreu Blanquer - Martina Travnickova - Jarmila Knitlova - Tomas Suchy - Sarka Ryglova - Martin Braun - Zuzana Burdikova - Martin Schätz - Vera Jencova - Maxim Lisnenko - Lubos Behalek - Renata Prochazkova - Radek Sedlacek - Kristyna Kubasova - Lucie Bacakova journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10058441 doi: 10.3390/ijms24065692 license: CC BY 4.0 --- # Adipose-Derived Stem Cells in Reinforced Collagen Gel: A Comparison between Two Approaches to Differentiation towards Smooth Muscle Cells ## Abstract Scaffolds made of degradable polymers, such as collagen, polyesters or polysaccharides, are promising matrices for fabrication of bioartificial vascular grafts or patches. In this study, collagen isolated from porcine skin was processed into a gel, reinforced with collagen particles and with incorporated adipose tissue-derived stem cells (ASCs). The cell-material constructs were then incubated in a DMEM medium with $2\%$ of FS (DMEM_part), with added polyvinylalcohol nanofibers (PVA_part sample), and for ASCs differentiation towards smooth muscle cells (SMCs), the medium was supplemented either with human platelet lysate released from PVA nanofibers (PVA_PL_part) or with TGF-β1 + BMP-4 (TGF + BMP_part). The constructs were further endothelialised with human umbilical vein endothelial cells (ECs). The immunofluorescence staining of alpha-actin and calponin, and von Willebrand factor, was performed. The proteins involved in cell differentiation, the extracellular matrix (ECM) proteins, and ECM remodelling proteins were evaluated by mass spectrometry on day 12 of culture. Mechanical properties of the gels with ASCs were measured via an unconfined compression test on day 5. Gels evinced limited planar shrinkage, but it was higher in endothelialised TGF + BMP_part gel. Both PVA_PL_part samples and TGF + BMP_part samples supported ASC growth and differentiation towards SMCs, but only PVA_PL_part supported homogeneous endothelialisation. Young modulus of elasticity increased in all samples compared to day 0, and PVA_PL_part gel evinced a slightly higher ratio of elastic energy. The results suggest that PVA_PL_part collagen construct has the highest potential to remodel into a functional vascular wall. ## 1. Introduction According to the World Health Organisation, cardiovascular diseases cause the deaths of 17.9 million people each year, which is $31\%$ of all deaths worldwide [1]. The need for vascular prostheses and cardiovascular patches therefore increases every year. Autologous vascular grafts are used preferentially for the creation of small caliber prostheses, but they have limited availability [2]. For pulmonary artery reconstruction, the following materials have been used so far: branch patch homograft, bovine pericardium, autologous pericardium, and porcine intestinal submucosal patch [3]. Due to the increasing need for vascular grafts, scientists have been developing various tissue-engineered vascular prostheses from a wide range of polymers—either natural (e.g., collagen, gelatin, elastin, chitosan, cellulose, pullulan, decellularised tissues) or synthetic, such as poly(lactic acid) (PLA), poly(glycolic acid) (PGA), poly(caprolactone) (PCL), poly(vinyl alcohol) (PVA), dextran, chitosan, and their blends [4,5,6,7,8,9]. Collagen as a natural extracellular matrix polymer offers both mechanical support and binding sites for cell adhesion receptors. In addition, it can be prepared in the form of hydrogels, decellularised tissues, sponges, meshes, films, nano/micro-fibers, micro-particles, and sheets, or it can serve as a drug-delivery system [10,11,12,13,14]. For colonisation of these scaffolds, aortic smooth muscle cells (SMCs), endothelial cells (ECs), NIH3T3 fibroblasts, autologous endothelial progenitor cell (EPC)-derived ECs, and mesenchymal stem cells (MSCs) derived from the bone marrow or from the adipose tissue have been used [14,15,16]. Pure collagen hydrogels with entrapped cells have fast degradation, high contraction and weak mechanical properties. This unfavourable behavior of collagen gels could be overcome by preparing composites with other polymers, such as polydopamin, chitosan, hyaluronic acid, silk fibroin, or by reinforcement with, e.g., polycaprolactone fibers, coral collagen fibers or bioactive glass particles [17,18,19,20,21]. In addition, mechanical properties and stability of the collagen-based materials can be improved by crosslinking with various agents, e.g., epoxidised chitosan quaternary ammonium salt, using in situ photochemical crosslinking, genipin, 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride (EDC)/N-hydroxysuccinimide (NHS) or transglutaminase [22,23,24,25,26]. However, the crosslinkers can be toxic and can be released from the material for a long time. Apart from biomechanical properties, it is important to improve bioactivity and bioconductivity of collagen gels. In various studies, the incorporation of vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF), angiopoietin-1 or conditioned medium, obtained from dermal fibroblast, into the collagen scaffold supported cell ingrowth, migration, differentiation, and the healing process [27,28,29,30,31]. Autologous stem cells, such as bone marrow- or adipose tissue-derived MSCs, are relatively easily available for the colonisation of collagen gels/composites intended as vascular patches, and these cells are able to differentiate into SMCs, as shown in our previous studies and studies by other authors (for a review, see Bacakova et al. 2018) [32]. For stem cell differentiation, specific growth factors and other bioactive molecules can be added in defined doses into the cell culture medium [33,34,35], or these additives can be replaced by a platelet lysate that contains a variety of bioactive compounds, which are physiologically released from platelets during wound healing [36,37]. Moreover, the platelet lysate does not have to be only directly added to the culture medium, but it can also be incorporated into an external controlled drug delivery system, ensuring gradual and long-term release of the bioactive compounds and their prolonged influence on cells. The novelty of this study therefore lies in preparation of a fully biodegradable nature-derived collagen-based composite, i.e., collagen hydrogel reinforced with collagen particles, incorporated with human adipose tissue-derived stem cells (ASCs) with the aim to differentiate these cells towards SMCs phenotype and to reconstruct the tunica media of the physiological vascular wall. For inducing this differentiation pathway, we developed an external drug delivery system, represented by nanofibrous PVA meshes releasing human platelet lysate into the culture medium, or we supplemented the culture medium with a combination of transforming growth factor-β1 (TGF-β1) and bone morphogenetic protein-4 (BMP-4), which has been proven as highly efficient for differentiation of ASCs towards SMCs [34,38]. The cell-material constructs were then evaluated with respect to ASCs proliferation, differentiation, extracellular matrix (ECM) production and remodelling, and mechanical properties of the patches. Finally, the constructs were endothelialised with human umbilical vein ECs in order to reconstruct the tunica intima, to mimic a physiological blood vessel wall, and to render the constructs applicable for creating vascular patches and blood vessel replacements. For these purposes, the construct incubated with the platelet lysate-loaded PVA meshes seemed to be the most promising, as indicated by a relatively high degree of ASCs differentiation towards SMCs, a relatively high mechanical stability, low shrinkage of the construct, and its homogeneous and confluent endothelialisation. ## 2.1. Properties of Isolated Porcine Collagen Composition of isolated COL is shown in Table 1. COL lyophilizate contains protein, lipids, glycosaminoglycans and water. Total protein content, represented by amino acids (AAs), is 58.5 wt$.\%$. AAs distribution is defined as a number of specific AA residues in 1000 AA units. The Hyp content is reflected in the degree of hydroxylation ($40\%$), which is defined as the ratio of Hyp/(Hyp + Pro). GAGs and lipids were determined close to 4 and 25.5 wt$.\%$, respectively. High scatter of data determined in lipids content can be connected with local inhomogeneity. The amount of interstitial water slightly exceeded 7 wt$.\%$. Figure 1 shows the electrophoretic profiles of porcine collagen. Protein patterns, comprising α1 and α2 chains with an average molecular weight of 130–110 kDa, their dimer (β chain) with molecular weight ∼250 kDa and trimer (γ chain) with molecular weight ∼300 kDa, are apparent. The band intensity ratio of the α1 and α2 chains is approximately 2:1, proving that isolated COL comprise type I existing in two other configurations: α1(I)α2(I)α3(I) and [α1(I)]2α2(I) [39]. The similarity in electrophoretic mobility of the α1 chain and α3 chain did not allow for separating them under the electrophoretic conditions [40]. In addition, the profile also comprises a lower molecular weight peptides (LMPs) component visible at 50 kDa. These peptides can be the product of collagen degradation, indicating that, during acidic extraction, some part of collagen (e.g., fragment from the telopeptide regions) may be more susceptible to hydrolysis. LMPs may also include peptide parts of non-collagenous protein residues that may be present in the collagen isolate. The FTIR spectrum of isolated COL can be seen in Figure 2. The spectrum contains five amidic bands, typical for protein, such as amide A at ∼3300 cm−1 representing N–H stretching and amide B at ∼3100 cm−1 representing stretching vibration of the N–H bonds in secondary amides. The amide I band (∼1650 cm−1) originates from C=O stretching vibrations coupled with N–H bending vibration, while the amide II band (∼1550 cm−1) arises from N–H bending vibrations coupled with C–N stretching vibrations [41]. Another piece of evidence for the existence of a triple helical structure is the presence of a quartet of bands at ∼1338 cm−1 and a triple band at ∼1205, 1240, and 1280 cm−1 (amide III) [42]. The amide I region (∼1650 cm−1) was deconvoluted into six distinct bands with maxima at ∼1695, 1675, 1660, 1650, 1635, and 1620 cm−1. The most dominant components are bands ∼1660 cm−1 assigned to the triple helix with contribution from α-helix, and the band at ∼1650 cm−1, which corresponds to random coils of α and β chains. Band 1635 cm−1 represents a denaturated state. Bands at 1675 cm−1 (β-turn), at 1695 cm−1 (β-sheet) [43] and band at 1620 cm−1 (imide residues) representing other structural states can be associated with the existence of LMP proved by SDS-PAGE. The ATR-FTIR spectrum also contains bands of impurities such as lipids (bands in spectral region 2800–2900 cm−1 belong to C-H aliphatic bonds and band at 1745 cm−1 assigned to C=O bonds in esters), and low intensity bands in spectral region 900–1100 cm−1 relating to GAGs. These residual impurities remain in the collagen after the isolation procedure [42]. Analysis of COL lyophilisates proved that the isolated material is based on collagen with the presence of GAGs, lipids and low molecular weight peptides. These peptides with a lower molecular weight and a shorter chain length than collagen molecules, and with much more hydrophilic and charged amid and carboxyl groups, can stabilize water in a protein gel matrix, as it can be proved by Abdollahi et al. [ 2018] [44]. ## 2.2. Morphology of Collagen Fibers and Particles Figure 3 shows selected images representative of the entire electrospun fibers (mag. 50,000×) and particles prepared via homogenisation of collagen electrospun layers (mag. 500×). Collagen fibers evinced an average diameter of 268 ± 75 nm ($$n = 100$$). The average length of particles was 363 ± 160 µm ($$n = 100$$). These measurements confirmed that the collagen fibers were of submicrometer dimensions, but the collagen particles contained both amorphous and fibrous structures. ## 2.3. Properties of PVA and PVA_PL Meshes The produced nanofibrous materials from PVA with incorporated proteins (from platelet lysate, PL) have a fiber diameter 455 ± 159 nm with a wide range fiber diameter distribution (Figure 4A,B). The protein content was 19.7 mg per gram of material. The analysis of protein release shows that up to $90\%$ of the protein is released within the first 24 h; the release then slows down and lasts for at least one week (Figure 4C) [45]. Crystallinity analysis did not confirm the influence of incorporated proteins and no significant difference in crystallinity was observed for the materials measured by DSC (Figure 5) and XRD (Figure S1) methods. This means that solubility of PVA was not affected by the incorporation of PL. ## 2.4. Cell Colonisation of Collagen Gels Reinforced with Collagen Particles We developed novel composite scaffolds based on a collagen gel reinforced with embedded collagen particles and compared them with collagen gels without reinforcement. During the first 6 days, the ASCs in collagen without particles were proliferating and reached the highest densities in TGF + BMP and PVA_PL samples (Figures S2 and S3). The TGF + BMP gel evinced increased shrinkage compared to the samples. On day 14, the gels without collagen particles seemed to be degraded and almost disappeared, and further analyses were not performed. In the experiments with collagen gels with collagen particles, we observed proliferation and differentiation of ASCs incorporated into these scaffolds and cultivated in the presence of platelet lysate-loaded nanomats (PVA_PL_part samples). Cultivation of cells in gels in standard DMEM media and in media with PVA mats without PL served as negative controls (DMEM_part and PVA_part samples). Conversely, the addition of TGF-β1 and BMP-4 to the media represented a positive control for the cell differentiation towards SMCs (TGF + BMP_part). The process of gel preparation with ASCs previously stained with CellTrackerTM Green CMFDA dye was relatively fast, and thus this prevented cells sedimentation and allowed for initial homogeneous cell distribution in the collagen gel. Collagen particles had a weak autofluorescence, and therefore they were partially visible on confocal images. The prepared samples showed a similar morphology and population density of ASCs on day 1 (Figure 6A–D,A`–D`). On day 7, the population density of ASCs was highest in TGF + BMP_part sample and lowest in the PVA_part sample (Figure 6A,E–H,E`–H`). The cells grew both in the gel and on the surface of the particles. The ASCs further increased their population densities on day 14; the highest value was observed in the TGF + BMP_part sample (Figure 6I–L,I`–L` and Figure 7A). Seeding ECs on the top of the ASC-incorporated gels enhanced the proliferation of both ASCs and ECs. Surprisingly, the highest cell population density on day 14 was observed in DMEM_part sample, which was used as a negative control (Figure 7A). Collagen particles hindered the measurement of the gel depth via microscopic evaluation. Thus, in order to evaluate the gel shrinkage, the gel area was measured inside cell culture dishes. There was no shrinkage of gels on day 7 (Figure 7B). On day 14, the shrinkage of ASCs-seeded gel was apparent only in the TGF + BMP_part sample. All the samples seeded with both ASCs and ECs shrank until day 14; a slightly higher extent of shrinkage was in the TGF + BMP gel. The shrinkage was probably caused by a higher proliferation rate of both ASCs and ECs in EGM-2 medium from day 8. The presence of PVA_PL system seemed to prevent the gel shrinkage, although the cell density was quite high. ASCs differentiation towards SMCs, which are an essential cellular component of vascular wall, was evaluated by immunofluorescence staining of alpha-actin and calponin, an early marker and a mid-term marker of differentiation into smooth muscle cells. On day 6, the DMEM gel without particles contained cells positive for alpha-actin, but the cells were negative for calponin (Figure S4). The PVA samples contained both alpha-actin positive cells and a small portion of calponin-positive cells. On the other hand, both PVA_PL and TGF + BMP samples contained alpha-actin-positive cells and a high portion of calponin-positive cells. On day 7, staining of reinforced gels showed the ASCs positive for alpha-actin, but only a small portion of the cells were positive for calponin (Figure 8). On day 14, the highest ratio of calponin-positive cells was in both PVA_PL_part and TGF + BMP_part gels on day 14 (Figure 8C). In the latter sample, all ASCs were positively stained for calponin. The collagen gels with particles seeded with ASCs were also evaluated for ECM proteins fibronectin and type I collagen by immunofluorescence staining and SHG microscopy (Figure 9). Fibronectin (green) was observed as filamentous only in the TGF + BMP_part samples. In the other samples, the signal was present mainly inside cells or in their vicinity, and was diffuse or granular. Type I collagen was detected by immunofluorescence staining (red), which visualizes total collagen, and also by the SHG technique (purple), which visualizes mature collagen organised into fibrils. In PVA_PL_part samples, the immunofluorescence of collagen was localised predominantly around the cells, which suggest de novo formation of collagen by these cells. SHG staining was also brightest in PVA_PL_part samples, but fibrous arrangement of collagen was most prominent in TGF + BMP_part samples. At the same time, however, the TGF + BMP_part samples contained a relatively low amount of collagen, especially around the cells, which suggested collagen remodelling, particularly its reorganisation and breakdown. However, the quantitative analyses of immunofluorescence signal of both fibronectin and type I collagen did not reveal any differences among the tested samples. Endothelialisation of the collagen gels reinforced with particles and incorporated with ASCs was performed with ECs from day 8 to day 14 of the culture. The DMEM_part, PVA_part, and PVA_PL_part samples were homogeneously endothelialised with almost confluent EC layer, as it was proved by staining of the von Willebrand factor (Figure 10A–C). In contrast, the TGF + BMP_part sample was not covered with ECs homogeneously, i.e., these cells tended to form separate dense islands, and the staining of von Willebrand factor seemed to be weaker (Figure 10D). However, the quantification of fluorescence signal of area occupied with von Willebrand factor and the intensity of staining of von Willebrand factor normalised to cell nuclei did not show any significant differences among the tested samples. In all samples, the ECs were localised on the gel surface, but sometimes they were found inside the collagen gel as well. ASCs were found freely distributed in collagen gel or adhering on collagen particles. The ability of collagen particles to be colonised with ASCs illuminates a slower collagen degradation and sample shrinkage, which were enormous in gels without reinforcement. The submicro-/nano-structure and crosslinking of the particles might contribute to their anti-shrinkage effect inside the collagen gel, which further increased with the presence of PVA_PL nanomeshes in cell culture medium. ## 2.5. Proteomics of the Cell-Material Constructs A total of five groups, namely collagen gels with ASCs immediately after preparation (D0), and collagen samples after 12 days (D12) in culture, i.e., DMEM_part, PVA_part, PVA_PL_part, and TGF + BMP_part containing ASCs and ECs, were analysed by mass spectrometry according to their protein concentration. There was a high number of significant changes detected between the control group (D0) and the samples after a 12-day cultivation, i.e., DMEM_part/D0 = 731 significantly upregulated proteins (s.u.p.) for a 12-day cultivation group; PVA_part/D0 = 718 s.u.p.; PVA_PL_part/D0 = 756 s.u.p.; TGF + BMP_part/D0 = 895 s.u.p.). Because the number of significantly altered proteins was too high, we selected three protein groups, i.e., proteins involved in cell differentiation (Table 2), ECM (Table 3) and proteins associated with ECM remodelling (Table 4) for better comprehensibility. ## 2.5.1. Proteins Involved in Cell Differentiation Table 2 displays 25 significantly upregulated proteins between day 12 and day 0 (D12/D0 cultivations) involved in cell differentiation. They comprise proteins related to SMCs differentiation (i.e., calponin and caldesmon, alpha-parvin, myosin phosphatase Rho-interacting protein), to muscles and vessels (cofilin-2, tropomyosines, plectin, transgelin, tropomodulin-3, nexilin, utrophin, filamin-A, filamin-C, alpha-adducin, fascin, myosin light polypeptide 6, myosin phosphatase Rho-interacting protein), proteins related to endothelial cells (i.e., platelet endothelial cell adhesion molecule, von Willebrand factor, endothelial monocyte-activating polypeptide 2, endothelial differentiation-related factor 1), proteins present in epithelial cell types (i.e., LIM and SH3 domain protein 1, alpha-actinin-4, F-actin-capping protein subunit alpha-1) and proteins that influence the differentiation of various other cell types (vinculin, fascin). The increased concentration of caldesmon was in both PVA_PL_part and TGF + BMP_part samples compared to PVA_part sample. The TGF + BMP_part samples contained significantly increased concentrations of myosin phosphatase Rho-interacting protein, transgelin, and tropomyosin alpha-1 chain. On the contrary, higher concentrations of both nexilin and fascin were found in the PVA_part compared to TGF + BMP_part samples. ## 2.5.2. ECM Proteins There were detected 19 significantly upregulated proteins between day 12 and control D0 sample in the ECM group (Table 3). The ECM group involves laminins (subunit alpha-2, alpha-4, beta-1, and gamma-1); collagens (type VII and triple helix repeat-containing protein 1, collagen alpha-1(V) chain, and collagen alpha-1(XII) chain), fibronectin, basement membrane-specific heparan sulfate proteoglycan core protein, decorin, tenascin, thrombospondin-4, lumican, fibulin-1, fibrilin, extracellular matrix protein 1, nidogen, and galectin-3-binding protein. Among the samples, the cells in TGF + BMP_part sample produced the significantly highest amounts of both type VII collagen and tenascin. In both PVA-part and PVA_PL_part, the cells expressed more extracellular matrix protein 1, galectin-3-binding protein, laminin subunit alpha-4, nidogen-1 and thrombospondin-4 compared to the TGF + BMP_part. ## 2.5.3. Remodelling Proteins Among ECM remodelling proteins, there were detected 13 significantly upregulated proteins (D12/D0 cultivations) in DMEM_part, PVA_part, PVA_PL_part and TGF + BMP_part between day 12 and control D0 group (Table 4). This remodelling group consists of five matrix metaloproteinases (MMP1, MMP2, MMP14, disintegrin and metalloproteinase with thrombospondin motifs 1), three enzymes required for collagen crosslinking or its regulation (lysyl oxidase homolog 2, procollagen-lysine 2-oxoglutarate 5-dioxygenase 1 and 2, and periostin), two transforming growth factor beta-related proteins (TGF-1-induced transcript 1 protein and TGF-beta-induced protein ig-h3) and metaloproteinase inhibitors (TIMP1 and procollagen C-endopeptidase enhancer 1). In TGF + BMP_part, higher amounts of periostin, matrix-remodelling-associated protein 7 (MXRA7) and transforming growth factor beta-1-induced transcript 1 protein (TGFB1I1) were measured compared to all other groups (for periostin), compared to PVA_part (for MXRA7) or compared to PVA_PL_part (for TGFB1I1). The expression of interstitial collagenase MMP1 was higher in both PVA_part and PVA_PL_part samples in comparison with the TGF + BMP_part. ## 2.6. Biomechanical Properties The mechanical properties of the composite material were characterised by the initial Young modulus of elasticity, total deformation energy and the ratio of elastic energy, i.e., the ratio between the elastic deformation energy and the total deformation energy. Young modulus (Eini) was higher in all collagen samples after 5 days in culture compared to the DMEM sample immediately after preparation (signed DMEM_D0; see Figure 11). The statistically significant differences (Student’s t-test, 0.05) were observed for DMEM, PVA and PVA_PL samples. The stiffness of the samples increased by more than $39\%$ after 5 days of cultivation. This result suggests remodelling of the gel by ASCs. Other biomechanical parameters, i.e., total deformation energy (Uc) and ratio of elastic energy (Uel/Uc), were similar for all samples (see Figures S5 and S6 in the Supplementary File). No statistically significant differences were observed. ## 3. Discussion Cardiovascular patches and prostheses based on collagen can be prepared using various methods, such as collagen gel casting, gel compression, 3D printing, decellularisation of tissues, etc. [ 46]. These implants can be used as acellular or can be cellularised either by conventional in vitro seeding cells on the prepared materials or by direct admixing the cells into the matrices during their preparation. Both of these approaches were used in the present study, i.e., the collagen gels were directly incorporated with ASCs and after the pre-differentiation of these cells towards SMCs, the constructs were seeded with ECs. ## 3.1. Collagen Gel Preparation, Gel Reinforcement Collagen gels with entrapped cells can be easily prepared using a wide range of collagen concentrations. The main disadvantage of a collagen gel incorporated with cells is contraction of this gel, which is more intense in gels with a lower initial collagen concentration. Collagen contraction/shrinkage stimulated the cell apoptosis and reduced the synthesis of ECM proteins [47]. In our experiment with collagen reinforced with collagen submicrometer particles, we used a final collagen concentration of 3.79 mg/mL, but this collagen contained about $25\%$ of GAGs and lipids. We observed only a limited gel contraction after its incorporation with ASCs, and this contraction was observed predominantly in gels incubated in medium with TGF-β1 + BMP-4 and in endothelialised gels. Another disadvantage of a collagen gel is weak mechanical resistance of the gel. To overcome it, the gel can be reinforced with fibers, particles or by preparation of various composites with other materials. For example, Nashchekina and colleagues [48] prepared polylactide scaffolds filled with a collagen gel of collagen density in the range from 1 to 3.5 mg/mL, colonised with mesenchymal stem cells (MSCs). The collagen density influenced the cell morphology, which was more spindle-shaped in gels with a density of 2 mg/mL or higher. This composite stimulated the production of laminin and fibronectin, especially from day 10 [48]. Similarly, fibronectin, laminin, and a number of other ECM proteins were produced by a co-culture of ASCs and ECs in our collagen gels until day 12. Collagen gel reinforced with fibrin-coated nanofibrous membrane and cellularised with fibroblasts immigrating from the membrane into the gel was developed as a skin construct [49]. This system was also advantageous in preventing the undesired gel shrinkage because the cells gradually colonizing the gel from the underlying membrane caused a significantly lower contraction of the gel than the cells admixed directly into the material [49]. Collagen gel was also reinforced by polymerisation with polyethylene glycol (MW = 8000) [50] or by crosslinking with transglutaminase [51]. ## 3.2. Cellular Component of the Gel, Cell Differentiation For cardiovascular tissue engineering, the collagen gel should contain suitable cell components. ASCs are able to differentiate into smooth muscle phenotypes in cell culture media supplemented with various growth factors, such as TFG-β1 with ascorbic acid [35,52], using various combinations of vascular endothelial growth factor (VEGF), fibroblast growth factor (FGF), platelet-derived growth factor (PDGF), TGF-β and B27 minus insulin supplement for inducing either synthetic or contractile phenotypes of SMCs differentiating from human induced-pluripotent stem cells [33]. Other factors inducing SMC differentiation include TGF-β3, sphingosylphosphorylcholine [53], and BMP-4, especially in combination with TGF-β1 ([34]. In a study by Elçin and colleagues [38], the combination of TGF-β1 with BMP-4 was selected as the most efficient among the media supplemented with TGF-β1 alone, with BMP-4 alone, with angiotensin II (Ang II), Ang II + TGF-β1 and with Ang II + BMP-4, and thus this medium was also used in our present study as a positive control for ASC differentiation towards SMCs. The biochemical signal inducing the SMC differentiation, provided by various culture media supplements, can be further enhanced by a mechanical stimulation. For example, a combination of PDGF-AB and TGF-β1 with cyclic stretching considerably enhanced the differentiation of ASCs towards SMCs [35]. In our study, the ASCs were cultured in DMEM medium with $2\%$ of FS and ascorbic acid, further supplemented either with direct addition of TGF-β1 + BMP-4 or of an external drug delivery system, based on PVA nanofibers releasing platelet lysate (PVA_PL). Moreover, for co-culture of ASCs inside the material with ECs on its surface, the cell culture medium contained growth factors, such as VEGF, FGF-2, insulin-like growth factor-1 (IGF-1), epidermal growth factor (EGF) and heparin, from which VEGF with heparin were observed to stimulate the differentiation of ASCs towards SMCs in our earlier study [28]. In our collagen gels, we proved the presence of alpha-actin and calponin, i.e., markers of SMC differentiation, in ASCs cultured with TGF-β1 + BMP-4 supplement and with the external PVA_PL drug delivery system. In addition, ASCs have the capacity to mediate wound healing through mitochondrial transfer and the paracrine secretion of various growth, antiapoptotic, angiogenic, antioxidant, anti-inflammatory and immunomodulatory factors, contained in exosomes and extracellular vesicles (for a review, see [32]). Furthermore, exosomes from ASCs can be internalised by other cell types, e.g., fibroblasts to stimulate the cell migration, proliferation and collagen synthesis in a dose-dependent manner, and to significantly accelerate cutaneous wound healing [54]). ASCs co-cultured with monocytes enhanced ECM deposition in comparison with the ASCs in monoculture, which had been differentiated towards SMCs using supplementation with both TGF-β1 and retinoic acid. We co-cultured ASCs in the collagen gel with endothelial cells that are naturally present in blood vessels. In our co-culture experiment, the TGF + BMP_part sample supported the differentiation of ASCs towards SMCs well but did not support homogeneous endothelialisation of the gels with ASCs. It could be explained by a dual effect of TGF-β1 and BMP-4, which can either stimulate or inhibit the migration and proliferation of ECs. TGF-β1 has multiple functions: it controls embryonic development, cell proliferation, migration and differentiation, ECM production and new blood vessels formation. TGF-β1 can stimulate the proliferation of various cell types, such as mesenchymal stem cells, fibroblasts, chondrocytes, osteoblasts and endothelial cells, but it can also inhibit the cell proliferation, including the proliferation of endothelial cells, epithelial cells and keratinocytes. This is due to the fact that TGF-β1 can activate two distinct type I receptor/Smad signalling pathways with opposite effects: the TGF-beta/ALK1 pathway induces endothelial cell migration and proliferation, necessary for the blood vessel formation, while TGF-beta/ALK5 pathway leads to inhibition of cell migration and proliferation and contributes to the blood vessel maturation [55,56]. TGF-β1 together with VEGF is also involved in the angiogenic response to hypoxia, and their response is connected with NOX4-mediated reactive oxygen species production [57]. BMP-4 also has a dual (controversial) effect on the migration and proliferation of ECs. In a study by [58], the addition of BMP-4 into the culture medium significantly increased migration and proliferation of mouse embryonic stem cell-derived ECs and human microvascular ECs via activation of VEGF and angiopoetin signalling pathways. However, in a recent study by [59], the addition of BMP-4 into cell culture medium inhibited the migration of human umbilical vein ECs, which was attributed to the accumulation of reactive oxygen species (ROS), induced by BMP-4. In samples exposed to the external drug delivery system consisting of PVA meshes slowly releasing platelet lysate, we achieved not only the differentiation of ASCs towards SMCs, but also a homogeneous and almost confluent endothelialisation. Platelet α-granules contain a wide variety of bioactive molecules that are released upon activation via physical or physiological stimuli and participate during wound healing, such as coagulation factors (e.g., factor V), adhesion molecules (e.g., von Willebrand factor, fibrinogen, thrombospondin), platelet factor 4 (PF-4), protease inhibitors (α2-macroglobulin, α2-antiplasmin), plasma proteins (IgG, albumin), proteoglycans, EGF, heparin-binding EGF-like growth factor, IGF-1, transforming growth factors (TGF-α, TGF-β), platelet-derived growth factors (PDGF-AA, PDGF-AB, PDGF-BB), soluble CD40L, immunoglobulins such as vascular cell adhesion molecule-1 (VCAM-1), intercellular adhesion molecule-1 (ICAM-1), chemokine (C-C) ligand 5 and chemokine (C-X-C) ligand $\frac{1}{2}$/3 [36]. The growth factors released from platelets act in the inflammatory phase of wound healing by stimulating the chemotaxis of monocytes to the site of injury and their differentiation into macrophages [37]. EGF has been observed to stimulate proliferation of fibroblasts, keratinocytes, and vascular ECs, and the production of fibronectin [60]. PDGF-BB is a potent stimulant for vascular SMC proliferation, migration, phenotypic modulation, and for pericyte recruitment; it prevents aberrant angiogenesis, reduces circumferential enlargement of vessels and supports vascular splitting into functional capillary network even with high VEGF concentrations [61,62]. In our earlier study, the PVA_PL nanofibers were able to release PL for more than for 7 days in sufficient concentration to stimulate growth of ECs, HaCaT keratinocytes and dermal fibroblasts [63]. Similarly, in this study, the slow and long-term release of PL from PVA meshes had a clearly positive effect on cell performance, manifested by the differentiation of ASCs towards SMCs, and particularly by the formation of a continuous EC layer. Similarly, in studies by other authors, ASCs cultured in a medium supplemented with $5\%$ of platelet lysate and without FS created more homogeneous phenotype, had a high proliferative capacity, secreted various proteins, such as basic fibroblast growth factor (bFGF), interferon-γ (IFN-γ), and IGF-1, and had immunomodulatory effects [64]. ASCs cultured in LaCell StromaQualTM medium supplemented with $1\%$ human platelet lysate enhanced proliferative capacity by about $70\%$ compared to supplementation with $10\%$ of FS. The ability to form colonies (evaluated by a colony-forming unit-fibroblast assay, CFU-F) was, however, reduced with human PL [65]. In our experiments, the external PVA_PL delivery system stimulated preferential production of ECM matrix proteins laminin, thrombospondin-4, galectin-3-binding protein, extracellular matrix protein 1 and interstitial collagenase (MMP1), while the TGF-β1 + BMP-4 supplement supported synthesis of matrix-remodelling-associated protein 7, periostin, TGF-β1-induced transcript 1 protein, tenascin, and type V and VII collagens. On the other hand, many other proteins, e.g., fibronectin, decorin, vinculin, and lumican, were produced equally in both types of samples. ## 3.3. Mechanical Properties of the Constructs Mechanical properties of cardiovascular patches are important for further clinical use. Biomechanical evaluation of our samples was performed on day 5 of static culture, as the construct had a proper volume for testing via an unconfined compression test. Despite this short time interval, there was an increase in the initial Young modulus of elasticity in all samples compared to the D0 time interval, although there were no differences among the groups. Our gels contained 0.5 × 106 ASCs cells/mL of the gel. Camasão and colleagues [66] have observed that higher initial SMCs densities during collagen gel preparation, i.e., 1.5–4.5 × 106 cells/mL, increased the initial collagen gel compaction/shrinkage, but did not negatively influence the long-term collagen gel compaction. In the samples with high cell densities, the cells produced a higher amount of collagen than the samples seeded with a lower cell density (0.5 × 106 cells/mL). The initial (E0) and equilibrium elastic modulus (EE) for the construct with 4.5 × 106 cells/mL were 220 ± 18 kPa and 58 ± 4 kPa, respectively, and these values were about two- and threefold higher compared to the gel with the lowest cell seeding density. At the same time, on day 7, the EE/E0 ratio, which expresses an elastic component, was greater in the high cell seeding density sample [66]. For comparison, the initial Young modulus of elasticity of our samples was in the range from 121 ± 24 kPa to 148 ± 24 kPa for TGF + BMP_part and DMEM_part samples after 5 days of culture, and the increase was in the range from 29 to $57\%$, respectively. The ratio of elastic energy was slightly higher for the PVA_PL_part sample. In the PVA_PL_part sample, upregulated protein interstitial collagenase (MMP1) was detected, thus collagens were probably more cleaved and loosen up there. The PVA_PL_part sample also evinced upregulated protein thrombospondin, which is a modulator of elastic fiber organisation [67]. TGF + BMP_part had a slightly higher total deformation energy than the PVA_PL_part, which was probably due to a significantly higher concentration of several types of collagens (V, VII, XII) detected by proteomic analysis. In addition, significantly upregulated protein periostin in the TGF + BMP_part sample could play a positive role in the contractility of the ECM scaffold. Periostin knockout −/− fibroblasts showed a significantly reduced ability to contract a collagen gel [68]. TGF + BMP_part also contained a significantly higher concentration of protein tropomyosin alpha-1 chain, which is involved in the actin contractile system, and protein transgelin, which is a shape-change sensitive actin crosslinking protein [69]. The elastic modulus of collagen hydrogel reinforced with silk fibroin, measured by a compression method, increased from 1.6 kPa for pure collagen to 2.6 kPa or 2.3 kPa for $50\%$ and $100\%$ silk content, respectively [70]. The gels containing $50\%$ and $100\%$ of silk fibroin reinforcement allowed for the growth of bone marrow MSCs. Improving the mechanical properties of collagen gel allows for its further processing by 3D printing for cardiovascular patches development. In another study [71], the addition of PVA/liposome nanofibers into the hyaluronate/type I collagen/fibrin composite gel increased gel stiffness and Young modulus. In addition, these nanofibers served as a carrier of bFGF and insulin for osteochondral regeneration. In another study, a texture reinforcement prepared from collagen fibers, which had been isolated from a coral, improved mechanical properties of crosslinked alginate gel dramatically [21]. The tubular construct evinced radial compliance values as follows: 9.97 ± 3.80, 4.88 ± 0.99, and 3.38 ± $0.64\%$/100 mmHg for the pressure ranges of 50–90, 80–120, and 110–150 mmHg. These values are similar to those of young and old coronary arteries. Another ureteral tubular collagenous scaffold was reinforced with Vicryl mesh [72], loaded with heparin, FGF-2 and VEGF, and then implanted successfully into pigs. In a study of Syedain and Tranquillo [73], TGF-β1 stimulated collagen production by neonatal human dermal fibriblasts during the first two weeks of cyclic stretching of fibrin-based tubular structures. At 5 and 7 weeks, however, both ultimate tensile strength and collagen concentration were lower, and elastin concentration was higher in the samples cultured with TGF-β1 [73]. Static culture of pure collagen gel with embedded SMC without any reinforcement did not improve mechanical properties of collagen gel. However, the samples evinced the improved initial modulus and relaxed modulus after 5 days of $10\%$ cyclic strain loading at 0.5 Hz. In addition, mechanical loading caused gel contraction [74]. ## 4.1. Isolation of Collagen The type I collagen (COL), used for preparing the hydrogel matrix, was isolated from porcine skin (Czech Improved White pig, 6 months old, the skin was obtained from the slaughterhouse) using the following protocol: incubation in $70\%$ ethanol (v/v) solution (1 g skin/10 mL, 30 min), washed 3× by water and subsequently exposed to an acetic acid solution in ratio 1:1000 (v/v), 1 g of COL/20 mL for 48 hrs). COL in collected supernatant was precipitated using 0.1 M NaOH solution in ratio 6:1 (v/v) up to slightly neutral pH 6–7. The obtained pellets were then dissolved again in acetic acid solution 1:1000 (v/v), frozen to −30 °C and lyophilised. All isolates were stored in a freezer at −20 °C. ## 4.2. Preparation of Collagen Submicrometer Fibers and Particles Collagen fibers were used as a reinforcement for optimisation of mechanical properties of the collagen hydrogels. Fibers based on collagen (type I, VUP Medical, Brno, Czech Republic) were prepared via the electrospinning (4SPIN, Contipro, Dolní Dobrouč, Czech Republic) of an 8 wt% collagen PBS/ethanol solution modified by 8 wt% (to collagen) polyethylene oxide (PEO; Mr. 900,000, Sigma-Aldrich, St. Louis, MO, USA). The stability of all the collagen layers was enhanced by means of crosslinking with a $95\%$ ethanol solution containing N-ethyl-N′-(3-(dimethylaminopropyl)carbodiimide (EDC) and N-hydroxysuccinimide (NHS) at a weight ratio of 4:1 (both Sigma-Aldrich, St. Louis, Missouri, USA), for 24 h at 37 °C. Cross-linked layers were further washed in 0.1 M Na2HPO4 (2 × 45 min), and by rinsed using deionised water (30 min). In this step, PEO was fully leached out [75]. The materials were then frozen at −30 °C for 5 h and lyophilised. Collagen fibers were then swelled in ethanol ($100\%$), and their homogenisation, resulting in particle formation, was achieved using a disintegrator (10,000 rpm, 10 min), followed by rinsing with deionised water (30 min), freezing at −30 °C and lyophilising. ## 4.3. Analyses of Porcine Collagen Composition Composition of isolated COL lyophilisates was studied by various analytical methods. The determination of interstitial water (directly bound to the triple-helix) was performed according to the standard ISO 6496:1983 (Animal feeding stuffs—Determination of moisture content), i.e., by drying to 160 ± 2 °C for 4 h. Amino acid analysis was performed using an Ingos AAA 400 analyser (INGOS s.r.o., Prague, Czech Republic). The hydroxyproline (Hyp) content was determined according to the ISO 3496:1994(E) standard (Meat and Meat products—the determination of hydroxyproline content). Content of lipids was assessed by the Schmidt-Bondzyński–Ratzlaff method, according to Czech technical standard EN ISO 1735:2004. Total content of glycosaminoglycans (GAGs), i.e., long unbranched polysaccharides, was quantified by high-performance liquid chromatography (HPLC) method based on hexosamines; i.e., glucosamine and galaktosamine, due to the formation of fluorescent N-acetylated hexosamine derivatives by reaction with a specific derivatisation agents—o-phthaldialdehyde [76]. Sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) was performed using the Mini-Protean Tetra Cell electrophoretic system from BIO-RAD on a gradient TGX Miniprotean Precast Gel, 4–$15\%$ (BIO-RAD, Hercules, CA, USA). The secondary structure of the isolated COL was evaluated by means of infrared spectrometry (FTIR) using iS50 infrared spectrometer (Nicolet Instrument, Madison, WI, USA) by attenuated total reflection (ATR) mode (GladiATR, PIKE Technologies, Madison, WI, USA) with a diamond crystal. Obtained spectra were processed by OMNIC version 9 software (Thermo Fisher Scientific, Waltham, MA, USA). Detailed information relating the used analytical methods can be found in a study by Stepanovska et al. [ 77]. ## 4.4. Morphology of Collagen Submicrometer Fibers and Particles The morphology of electrospun submicrometer-scale fibers and particles were characterised using scanning electron microscopy (SEM) (QUANTA 450, FEI). Randomly selected images representative of the entire electrospun fibers (mag. 50,000×) and homogenised particles (mag. 100×) were used to measure the diameters of 100 individual fibers and/or particles using the ImageJ software (US National Institutes of Health, Bethesda, MD, USA, http://imagej.nih.gov/ij/ (accessed on 30 August 2022). ## 4.5. Platelet Lysate Preparation Platelet lysate (PL) was prepared from platelet-rich solution, which was obtained from healthy blood donors (from Regional Hospital Liberec, Czech Republic), and all blood donors signed the informed consent. Concentration of platelets was 843 × 106 per mL. Fresh platelet-rich solution was frozen at −80 °C at least for 24 h, and then thawed over night at 4 °C (causing gentle cell lysis). Then, the cell lysate was centrifuged (1000× g, 30 min), and the supernatant after centrifugation (PL) was stored at 4 °C until use (not longer than 24 h) [45]. ## 4.6. PVA_PL Nanofibrous Mat Preparation Nanofibrous mats were prepared from $10\%$ solution of PVA (molecular weight 125,000, degree of hydrolysis 98–$98.9\%$, Mowiol 20–98, Merck Spol. S.R.O., Prague, Czech Republic) in water: ethanol (9:1) solvent system. In case of protein loaded mats, the 10 g of platelet lysate was added into 90 g pre-PVA solution 30 min before electrospinning and gently mixed at room temperature until use (for details, see [45]). Materials were then electrospun using Nanospider™ 1WS500U machine (Elmarco, Liberec, Czech Republic) at 22 °C, $25\%$ humidity, −10/+60 kV, EMW speed 320 mm/s, rewinding speed 10 mm/min, distance of string and collector 160 mm. Prepared mats were stored at −80 °C until use. ## 4.7. Protein Content/Release Analysis of PVA_PL The protein release was analysed by sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) after incubation of PVA mats containing proteins in phosphate-buffered saline (PBS, pH 7.4). Cumulative analysis was performed placing 10 mg of materials into 1 mL of PBS; subsequently, 200 µL of solution was taken for analysis at certain time intervals, and 200 µL of fresh PBS was added to keep the volume of 1 mL. Proteins were analysed after incubation at 37 °C for 1, 2, 4, 6, 8, 24, 72, and 168 h. Solutions after protein release (sample preparation described in [45] were analysed by $10\%$ SDS-PAGE (1.5 h/90 V); proteins were visualised using the Coomassie Brilliant blue gel staining method. ## 4.8. PVA Crystallinity Analysis The crystallinity of PVA was evaluated from thermal analysis, i.e., differential scanning calorimetry (DSC), of the prepared nanofibrous mats. Ten milligrams of samples was analysed using a differential scanning calorimeter DSC$\frac{1}{700}$ (Mettler Toledo, LLC, Columbus, OH, USA). Aluminium pots with samples were cooled to 0 °C and then heated to 300 °C at a rate of 10 °C/min. Heating was performed under inert conditions (nitrogen), and crystallinity was calculated from the recorded DSC curves. In addition, the crystallinity of the nanofibrous PVA materials was measured by X-ray diffraction (XRD) on a Bruker D8 Advance diffractometer equipped with a LynxeyePSD detector (Bruker, Billerica, MA, USA) and Cu Kα1.2 radiation (40 kV and 40 mA), 0.02 mm Ni Kβ absorber, 5–50° 2θ range and a 0.02° step scan with a sample rotation speed of 30 RPM. The relative proportion of crystalline regions in the samples was calculated using the following formula:α %=IcIc+Ia·100 where α is the degree of crystallinity, Ic is the sum of the intensities below the crystalline peaks, and Ia is the sum of the intensities below the amorphous sections of the spectra. ## 4.9. Cell Isolation, Cultivation and Characterisation Lipoaspirates were harvested by liposuction from subcutaneous fat of tight regions of human female donors using a negative pressure of −700 mmHg. The procedure was accomplished in compliance with the tenets of the Declaration of Helsinki and under ethical approval issued by the Ethics Committee of the Bulovka Hospital in Prague (28 August 2014; 11 June 2019) and under Informed Consent of the patients. Adipose tissue-derived stem cells (ASCs) were isolated using the enzymatic digestion method first described by Estes and colleagues [78] and further modified by our group [79]. Briefly, after washing the lipoaspirate with PBS (Sigma-Aldrich, St. Louis, MO, USA) several times, an enzymatic digestion followed using PBS containing $1\%$ (wt/vol) of bovine serum albumin (BSA; Sigma-Aldrich, St. Louis, MO, USA) and type I collagenase $0.1\%$ (wt/vol) (Worthington, Lakewood, NJ, USA) for 1 h at 37 °C. After the centrifugation, the stromal vascular fraction (SVF) was obtained at the bottom of the test tubes. The SVF was washed, filtered through membranes with pores of 100 μm in diameter (Cell Strainer, BD Falcon, Corning, New York, NY, USA), and seeded into culture flasks (75 cm2, TPP, Trasadingen, Switzerland) in a density of 0.16 mL of original lipoaspirate/cm2. The ASCs were cultured in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with $10\%$ (vol/vol) of fetal bovine serum (FS, Cat. No. 10270-106 GIBCO, Waltham, MA, USA), gentamicin (40 µg/mL, Lek Pharmaceuticals d.d., Ljubljana, Slovenia) and human recombinant basic fibroblast growth factor (FGF2; 10 ng/mL; GenScript, Rijswijk, The Netherlands). The cells were passaged, when they reached 70–$80\%$ subconfluence. Flow cytometry analysis (Accuri C6 Flow Cytometer, BD Biosciences, San José, CA, USA) revealed that the ASCs were positive for cell surface antigens CD73 (ecto-50-nucleotidase, CD90 (immunoglobulin Thy-1), CD105 (endoglin) and CD29 (fibronectin receptor), all >$95\%$, while they were almost negative for CD31 (platelet-endothelial cell adhesion molecule-1), CD34 (antigen of hematopoietic progenitor cells), CD45 (protein tyrosine phosphatase receptor type C), and CD146 (melanoma cell adhesion molecule or receptor for laminin, which is also considered to be a marker of pericytes, all <$5\%$). For experiments, the ASCs were seeded at the passages 4–5. Human umbilical vein endothelial cells (ECs) were purchased from LONZA (Basel, Switzerland) and were seeded at the passages 3–4. ## 4.10. Preparation of Collagen Hydrogels with Cells, Cell Cultivation The lyophilised COL I was dissolved in 0.02 M acetic acid in the concentrations of 6 mg/mL and was stored at 4 °C for 5 days. The COL suspension was homogenised by means of a disintegrator (10,000 rpm, 10 min). Before collagen gel preparation, 32 mg of collagen particles per 1 mL of the gel were added into each well of a 24-well glass bottom plate (Cellvis, City, CA, USA, P24-1.5H-N). The hydrogel was prepared by mixing the COL suspension with the ASCs suspension in DMEM (Cat. No. 52100-021, Gibco Waltham, MA, USA), supplemented with $2\%$ of FS (Cat. No. 10270-106 GIBCO), gentamicin (40 µg/mL, Lek Pharmaceuticals d.d., Ljubljana, Slovenia), 2-phospho-L-ascorbic acid trisodium salt (50 µg/mL, Cat. No. 49752, Sigma-Aldrich, St. Louis, MO, USA) and with sodium bicarbonate (7.5 wt$.\%$). The ratio of COL, cell suspension and sodium bicarbonate solution was 1.766:1:0.0294 (v/v/v), respectively. Collagen suspension with the medium with cells was left to polymerise for at least 10–15 min at 37 °C, in a humidified atmosphere with $5\%$ CO2, to reach pH around 7.4, and then 1.5 mL of cell culture medium was added above the gel. The change in pH from acidic to neutral and 37 °C caused the COL to polymerise into a hydrogel. Final COL concentration in gels was 3.3 mg/mL, and the final ASCs density was 500,000 cells/mL. The ASCs incorporated in the COL hydrogel without COL particles and in COL hydrogel reinforced with COL particles (part) were then cultured by the following manners: [1] In DMEM medium supplemented with $2\%$ of FS, 40 µg/mL of gentamicin and 50 µg/mL of ascorbic acid (Cat. No. 49752, Sigma-Aldrich, St. Louis, MO, USA), mentioned above (samples labelled as DMEM_part); [2] In the same medium with the addition of pure PVA nanomats (2 × 1 cm2; samples labelled as PVA_part); [3] In the same medium with addition of PVA nanomats loaded with PL (2 × 1 cm2) representing an external drug delivery system (samples labelled as PVA_PL_part), and [4] In the same medium supplemented with transforming growth factor β1 (TGF-β1, Cat. No. ab50036, Abcam, Cambridge, UK) and bone morphogenetic protein 4 (BMP-4, Cat. No. SRP6156-10UG, Sigma-Aldrich, St. Louis, MO, USA) at the concentration of 2.5 ng/mL, representing a culture medium proven for cell differentiation towards SMCs (samples labelled as TGF + BMP_part). In all four groups of samples, the medium was replaced twice per week during a 14-day culture. For endothelialisation of the gels reinforced with particles, ECs were seeded on the top of all four groups of samples at the density of 100,000 cells/well on day 8 after ASC incorporation, and cultured either in a pure EGM-2 medium (Promocell, Heidelberg, Germany) or in an EGM-2 medium with PVA nanomats, with PVA_PL namomats or with TGF + BMP until day 12 (for mass spectrometry) or until day 14 (for immunocytochemical staining). For measurement of biomechanical properties, the prepared gels with collagen particles were as thick as 1 cm, and the samples with ASCs cells were cultured for 5 days or were analysed immediately after preparation (day 0). The samples were incubated in a humidified atmosphere with $5\%$ of CO2 at 37 °C. The scheme of the whole study is in Figure 12. ## 4.11. Visualisation of Living Cells The ASCs cells cultured in TPP flasks were incubated with CellTrackerTM Red CMTPX dye or with CellTrackerTM Green CMFDA (both 25 µM, Thermo Fisher Scientific, Waltham, MA, USA) in DMEM with $10\%$ of FS for 45 min. After washing with PBS, the cells were kept in a standard cell culture medium until the stained cells’ suspension was used for collagen gel preparation. The gels with embedded cells were vizualised using Andor Dragonfly 503—a spinning disk confocal microscope on day 14 of culture. The 3D and 2D projections were created, and cell densities were calculated via IMARIS software. ## 4.12. Immunofluorescence Staining of Cell Differentiation Markers and ECM Components The samples were fixed with $4\%$ paraformaldehyde in PBS for 15 min at room temperature (RT), washed twice with PBS, and permeabilised with $1\%$ BSA in PBS containing $0.1\%$ Triton X-100 for 20 min. The samples were then washed with PBS, treated with $1\%$ Tween for 20 min at RT and washed again with PBS. The samples were incubated with a rabbit anti-calponin antibody (Abcam, Cat. No. ab46794 (EP798Y), dilution 1:200) at 4 °C overnight; then, they were washed twice with PBS and incubated with a mouse anti-alpha smooth muscle actin antibody (Sigma-Aldrich, St. Louis, MO, USA, clone 1A4, Cat No. A2547, dilution 1:200) at RT for 3.5 h. Then, the samples were washed twice with PBS and were incubated in a goat anti-rabbit secondary antibody conjugated with Alexa Fluor 488 (Thermo Fisher Scientific A11070, 1:400) for 90 min, washed with PBS and incubated in a goat anti-mouse secondary antibody conjugated with Alexa Fluor 546 (Thermo Fisher Scientific, A11003, 1:400) for 90 min. Finally, the samples were washed twice with PBS. For immunocytochemical staining of the co-culture of ASCs and ECs, mouse anti-alpha smooth muscle actin antibody (Sigma-Aldrich, St. Louis, MO, USA, clone 1A4, Cat No. A2547, dilution 1:200) was applied at 4 °C overnight, washed twice with PBS, and then rabbit anti-von Willebrand factor antibody (Sigma-Aldrich, St. Louis, MO, USA, F3520, dilution 1:200) for 3 h were applied. After washing twice with PBS, the anti-mouse and anti-rabbit secondary antibodies, mentioned above, were then applied sequentially at RT for 120 min each. The cell nuclei dye DAPI was added into the last secondary antibody solution (1 µg/mL). Similarly, immunofluorescence staining of fibronectin and type I collagen in reinforced collagen gels with ASCs on day 14 was performed using the primary antibodies as follows: the mouse monoclonal anti-human fibronectin antibody, clone IST-3 (Sigma-Aldrich, St. Louis, MO, USA, F079, 1:200), applied at RT for 3 h, and the rabbit polyclonal anti-type I collagen antibody (COSMO BIO CO., LTD, LSL-LB-1197, 1:200), applied at RT for 90 min. The secondary antibodies were F(ab’)2-goat anti-mouse IgG (H + L) cross-adsorbed secondary antibody, Alexa FluorTM 488 (Thermo Fisher Scientific, Waltham, MA, USA, A-11017, 1:400), which was applied at RT for 90 min and a mixture of AlexaFluor546 goat anti-rabbit IgG, cross-adsorbed secondary antibody (Thermo Fisher Scientific, Waltham, MA, USA, A11010, 1:400) and DAPI (1 µg/mL), applied at RT for 90 min. Quantification of the fluorescence signal of von Willebrand factor, fibronectin and type I collagen was performed by ImageJ software, and the data were normalised to the cell nuclei signal. ## 4.13. Confocal Microscopy Images were obtained by the Dragonfly 503 spinning disk confocal microscope using software Fusion version 2.1.0.80 (Andor, Oxford Instruments, Tubney Woods, Abingdon, UK), equipped with objectives HC PL APO 10×/0.40 DRY and camera Zyla 4.2 PLUS sCMOS—2048 × 2048 pixels. Images were acquired with a voxel edge size of 6.5 µm and a z-step of 5 µm using a 25 μm pinhole size. Cells stained by CellTracker Red CMTPX or CellTracker Green CMFDA (Thermo Fisher Scientific, Waltham, MA, USA, 25 µM) were excited by a 561 nm laser; emissions were collected in a range of 575–625 nm for the red tracker, excited by a 488 nm laser, and collected in a range of 500–550 nm for the green tracker. ## 4.14. Lightsheet Microscopy Lightsheet microscopy 3D images were acquired with a Zeiss Z.1 lightsheet microscope using the 10×/0.2 NA excitation and 20×/1.0 water immersion detection objective lenses, 488 nm and 561 nm excitation and the respective green (505–545 nm) and red (575–615 nm) emission. Image processing and visualisation were performed in ZEN (Zeiss, GmbH, Aalen, Germany) and Arivis Vision 4D (Zeiss, GmbH, Aalen, Germany) software, respectively. ## 4.15. Nonlinear Imaging—Second Harmonic Generation Second Harmonic Generation (SHG), able to visualize mature collagen fibers [28], was performed on a Zeiss LSM 780 microscope system (Zeiss, GmbH, Aalen, Germany), comprised of an Axio Observer inverted microscope stand, LSM 780 laser scanner head and Coherent Chameleon tunable femtosecond laser. For SHG, 860 nm excitation was used, together with $\frac{430}{15}$ detection using the internal LSM 780 spectral detector. The sample was kept at 10 °C with the help of a cooler (Okolab, S.r.l., Pozzuoli, Italy). ## 4.16. Bruker Microscopy Samples were measured using multiphoton microscope Bruker Ultima (Bruker Corporation, Billerica, MA, USA) using the CFI75 Apo 25XC W 1300 objective (1.1 NA). Images of samples were captured as 12-bit images of different z-planes 2 µm apart at 1024 × 1024 pixel resolution with 525.45 × 525.45 µm using Prairie View (Bruker Corporation, Billerica, MA, USA). The excitation was carried out with two different wavelengths, 940 nm and 1100 nm (or 760 nm). The emission signal was filtered through bandpass filters ET$\frac{525}{70}$m-2P and ET$\frac{595}{50}$m-2P (or $\frac{450}{50}$m-2P) (Chroma Technology Corp., Bellows Falls, VT, USA) and detected with GaAsP photosensors sensitive in the visible light region (Hamamatsu, Hamamatsu, Japan). Three-dimensional projections were created using ImageJ and IMARIS software (Oxford Instruments, Tubney Woods, Abingdon, UK). The two-channel lightsheet data were processed in Arivis Vision 4D version 3.1.3. After stitching, data were denoised with a 2D median filter, and background correction was applied. Objects were segmented using the global intensity threshold, and their morphological and intensity features were exported for further statistical analysis. ## 4.17. Evaluation of Biomechanical Properties Biomechanical testing of the collagen hydrogel was performed using an unconfined compression test. The MTS Mini Bionix 858.02 testing system (MTS, Eden Prairie, MN, USA) equipped with 10 N force sensor (sensitivity 0.001 N) was used for the compression tests in quasi-static mode at a constant cross head loading speed of 2.0 mm/min. A total of 5 cycles were realised, i.e., 5 times loaded to 1 N and 5 times unloaded to 0.05 N. The hydrogel disks for this test were placed between two stainless steel cylinders at room temperature (24 °C). The force and the deformation data were recalculated into the stress–stain curves. The mechanical properties of the composite material were characterised by the initial Young modulus of elasticity, total deformation energy and the ratio of elastic energy, i.e., the ratio between the elastic deformation energy and the total deformation energy. The data were acquired by the MTS Mini Bionix testing system and were analysed in Matlab 2020b (MathWorks, Natick, MA, USA). The environmental conditions were recorded by a COMET (Comet System, S.R.O., Roznov pod Radhostem, Czech Republic) digital thermometer hygrometer. ## 4.18. Mass Spectrometry—Label Free Quantification (MS LFQ) Biological samples ($$n = 4$$ in each group) were harvested, and MS LFQ analysis was performed. Briefly, each sample was lyophilisated and 10 mg of dry weight was taken for analyses. Samples were homogenised in liquid nitrogen, and 0.3 mL of 0.1 M ammonium bicarbonate (pH = 7.8) was added. After 30 min of sonication and centrifugation (10,000× g; 5 min), the supernatant was extracted and used for subsequent analysis (both pellet and supernatant were stored at −25 °C). Supernatant samples were heated at 105 °C for 5 min., digested with trypsin and desalted on Empore C18 columns, dried in Speedvac (Thermo Fisher Scientific, Waltham, MA, USA). Samples were dissolved in $0.1\%$ TFA + $2\%$ acetonitrile. About 0.5 µg of peptide digests were separated on 50 cm C18 column using 2.5 h elution gradient and analysed in a DDA mode on Orbitrap Exploris 480 mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). The resulting raw files were processed in MaxQuant (v. 1.6.17.0) with label-free quantification (LFQ) algorithm MaxLFQ. The search was performed at 0.01 false discovery rate (FDR) levels using FASTA files from UniProt (release 2021_01). Downstream analysis and visualisation were performed in Perseus (v. 1.6.15.0.). The p-value returned was corrected by FDR based on a frequency histogram. An FDR adjusted p-value threshold was less than 0.01. ## 4.19. Statistical Analysis For cell experiments, an all pairwise multiple comparison procedure (ANOVA, Student–Newman–Keuls Method) was used. Biomechanical data were analysed using a Student’s t-test, and statistical significance was considered for p value ≤ 0.05. The statistical analysis of mass spectrometry is described in the previous subsection. ## 5. Conclusions Collagen gels reinforced with collagen particles, incorporated with ASCs and endothelialised with HUVECs were prepared and cultured either in a medium with TGF-β1 and BMP-4 (TGF + BMP_part sample), or in a medium with a newly developed external drug delivery system, represented by a nanofibrous PVA mesh releasing platelet lysate (PVA_PL_part sample). Cell-material constructs incubated only in a standard cell culture medium (DMEM_part) or in this medium with pure PVA nanomats (PVA_part) served as negative controls. Gel reinforcement with collagen particles prevented the planar shrinkage of all gels until day 7. On day 14, significant gel shrinkage was observed with TGF + BMP_part gels either with or without endothelial cells. On the contrary, the minimum shrinkage was observed with PVA_PL_part gel regardless of its endothelialisation. Endothelial cells formed a confluent layer on all gels; however, TGF + BMP_part gels evinced less homogeneous coverage with endothelial cells. The differentiation of ASCs towards SMCs, assessed by the intensity of calponin immunofluorescence staining as well as proteomic analysis, was strongest in TGF + BMP_part samples, moderate in PVA_PL_part and PVA_part samples, and the lowest in DMEM_part samples. The highest concentrations of proteins involved in ECM synthesis and remodelling were found in TGF + BMP_part samples, lower in PVA_PL_part and PVA_part samples, and the lowest in DMEM_part samples. In all samples, we observed improved mechanical properties on day 5 after seeding compared to day 0. The PVA_PL samples seem to have a slightly higher ratio of elastic energy, and TGF + BMP_part a slightly higher total deformation energy value. PVA_PL_part samples with an external drug delivery system, releasing platelet bioactive components into the culture medium, represent a more natural way of stimulating ASCs proliferation, differentiation, ECM production and remodelling than the direct addition of TGF-β1 and BMP-4 into the medium. The slower effect of the external PVA_PL system, probably limited by the amount of released PL components, was balanced with homogeneous endothelialisation and minimum gel shrinkage. ## References 1. Cardiovascular Diseases (CVDs) 2. 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--- title: 'Diapause-Linked Gene Expression Pattern and Related Candidate Duplicated Genes of the Mountain Butterfly Parnassius glacialis (Lepidoptera: Papilionidae) Revealed by Comprehensive Transcriptome Profiling' authors: - Chengyong Su - Chen Ding - Youjie Zhao - Bo He - Ruie Nie - Jiasheng Hao journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10058462 doi: 10.3390/ijms24065577 license: CC BY 4.0 --- # Diapause-Linked Gene Expression Pattern and Related Candidate Duplicated Genes of the Mountain Butterfly Parnassius glacialis (Lepidoptera: Papilionidae) Revealed by Comprehensive Transcriptome Profiling ## Abstract The mountain butterfly Parnassius glacialis is a representative species of the genus Parnassius, which probably originated in the high-altitude Qinhai–Tibet Plateau in the Miocene and later dispersed eastward into relatively low-altitude regions of central to eastern China. However, little is known about the molecular mechanisms underlying the long-term evolutionary adaptation to heterogeneous environmental conditions of this butterfly species. In this study, we obtained the high-throughput RNA-Seq data from twenty-four adult individuals in eight localities, covering nearly all known distributional areas in China, and firstly identified the diapause-linked gene expression pattern that is likely to correlate with local adaptation in adult P. glacialis populations. Secondly, we found a series of pathways responsible for hormone biosynthesis, energy metabolism and immune defense that also exhibited unique enrichment patterns in each group that are probably related to habitat-specific adaptability. Furthermore, we also identified a suite of duplicated genes (including two transposable elements) that are mostly co-expressed to promote the plastic responses to different environmental conditions. Together, these findings can help us to better understand this species’ successful colonization to distinct geographic areas from the western to eastern areas of China, and also provide us with some insights into the evolution of diapause in mountain Parnassius butterfly species. ## 1. Introduction In the context of global climatic changes throughout Earth’s history, insects in the field are usually exposed to repeated bouts of stress (e.g., cold/heat, dry/moist and solar radiation) and unpredictable factors (e.g., predators, pathogenic microorganisms, food supply and population density), under the varied intensity or amplitudes of fluctuating conditions [1,2]. Correspondently, determining the drivers and the resultant patterns of gene expression is more complicated in the fluctuating environments where insects typically live than in controlled laboratory conditions. For example, previous studies showed that both the mean and fluctuation of temperature could contribute to thermal acclimation and affect the transcriptional pattern in Drosophila melanogaster [3]; repeated and single cold factors could induce divergent transcriptomic responses [1]; photoperiodism might mediate insect phenological responses to temperature [4], and the synergistic effects of multiple stressors could induce novel candidate genes responsible for the variation found in thermal tolerance and survival [5,6,7]. However, insects have evolved to overcome unfavorable environmental conditions in a hormonally regulated state of diapause, during which their activity is suppressed and their development is decelerated, but their tolerance of environmental stress is bolstered (e.g., increased stress resistance, improved immune defense and somatic maintenance) [8,9,10,11], reflecting their shared transcriptional strategies for regulating the hallmark diapause-linked physiological phenotypes, especially at the functional pathway level [11]. Nevertheless, our knowledge of butterflies’ (including those of new colonizers or nonnative invaders) responses to the changes of natural conditions for survival in the field remains limited. The genus Parnassius is a typical mountain-adapted butterfly group, mainly distributed across the Holarctic, with its highest diversity on the Qinghai–Tibet Plateau (QTP) and adjacent mountainous regions (including Xinjiang and Gansu, China), with a broad elevational range of 3000–5000 m (Figure 1). Previous studies have indicated that the diversification of Parnassius initiated during the Middle Miocene, correlated with their host plant’s spatiotemporal distributions, and geological and paleoenvironmental changes in the QTP region [12,13], as well as the fact that both the ancient gene introgression and climate cooling after the Middle Miocene Climate Optimum (MMCO) might have contributed to the spread of Parnassius species to different altitudes, accompanied by the dispersal from West China to Northeast China and other areas of East Asia [14]. Among them, the Glacial Apollo butterfly, Parnassius glacialis, is the only species that has dispersed into the southeastern areas of the Yangtze River, and mainly inhabits low-altitude mountains (~200 to 1800 m), suggesting their extraordinary flexibility to local seasonal environmental challenges. Previous studies have demonstrated that P. glacialis diverged firstly into two clades during the Pleistocene period, then dispersed independently into distinct geographic areas from the western to eastern China, most likely driven by the Pleistocene’s glacial–interglacial cycles [15]. Currently, most P. glacialis populations are restricted to ecologically and topographically fragmented habitats, especially in relatively lower-altitude mountains in the northeast and southeast of China, with remarkable morphological adaptations, such as body size enlargement and wing color lightening, implying that they have adapted locally to disparate ecological zones. Thus, these populations could offer an excellent butterfly model to examine the intraspecific transcriptional variation in the field, and how this would influence climate change-driven phenotypes. In the present study, we sampled a total of 24 P. glacialis individuals from eight localities, and determined large scale transcriptomic data to identify the common genome-wide transcriptomic expression pattern, as well as their intraspecific transcriptional variations. Meanwhile, we attempted to reveal the distinctive transcriptomic signatures of duplicated genes and transposable elements (TEs), based on the newly sequenced high-quality genome of P. glacialis from our laboratory, in order to deepen our understanding of the “out of QTP” dispersal and adaptation to different environmental conditions of P. glacialis. ## 2.1. Statistics of Differentially Expressed Genes (DEGs) and Functional Enrichment Analysis In order to dissect the molecular mechanisms underlying P. glacialis’ adaptation to different natural habitats, a total of 24 samples in four groups were used for RNA-seq analysis (Figure 1), and 6.4–10.3 Gb of clean data for each sample were obtained (Table S1). The boxplots show the normalized gene expression profiles and principal component analysis (PCA) scatter plots show differences among samples dwelling in different habitats (Figure S1). When compared to the WG samples, the quantitative aspect of the transcriptional changes, roughly judged by comparing the DEGs numbers, gradually decreased from the NG samples to the CG and SG samples, i.e., for NG vs. WG, $6.8\%$ [1,135] of the genes from a total 16,659 sequences were DEGs; for CG vs. WG—$3.3\%$ [544], and for SG vs. WG—$1.8\%$ [296], probably suggesting that the differences in gene expression were not significantly correlated with geographical distances between WG and other groups. When compared to the CG samples, the decreased DEG numbers were also found for the NG samples ($1.2\%$, 195 for NG vs. CG) and the SG samples ($1.0\%$, 162 for SG vs. CG), but both of these had markedly fewer DEGs than were found in CG vs. WG ($3.3\%$, 544). Moreover, the qualitative aspect of transcriptional changes also tends to evolve gradually, as indicated by the gradual decrease in overlap of DEGs between comparisons, i.e., for NG and WG vs. CG and WG, $23.0\%$ [313] of 1,366 DEGs overlap, whereas for SG and WG vs. CG and WG, only $13.1\%$ [97] of 743 DEGs overlap. Further, for CG and WG vs. NG and CG, $0.8\%$ [6] of 733 DEGs overlap, whereas for CG and WG vs. SG and CG, no DEGs overlap (Figure 2a). KEGG enrichment analyses showed consistent trends with those above in both the quantitative and qualitative aspects of transcriptional changes, i.e., gradually decreased number (64, 21 and 10) of enriched signaling pathways for DEGs in the comparisons of NG vs. WG, CG vs. WG, and SG vs. WG, respectively, as well as relatively lower overlap of enriched pathways between comparisons, i.e., for NG and WG vs. CG and WG, $21.4\%$ [15] of 70 pathways overlap, whereas for SG and WG vs. CG and WG, only $10.7\%$ [3] of 28 pathways overlap. There were no overlapped pathways among the comparisons of CG vs. WG, NG vs. CG, and SG vs. CG (Figure S2). When compared to WG samples, the KEGG enrichment analyses showed that NG samples harbored sixty-three significantly enriched pathways for the up-regulated DEGs, while they harbored only one (ribosome) for the down-regulated DEGs (adjusted p value < 0.05; Figure 2b, Tables S3 and S4). The pathways enriched for up-regulated DEGs mainly included proteoglycans, calcium signaling, phototransduction, olfactory transduction, cytoskeleton and immune-related pathways. In addition, components of the pathways related to the endocrine system (e.g., GnRH, insulin, relaxin and other hormone-related signaling pathways) and the central nervous system (CNS, including cholinergic, dopaminergic, synaptic vesicle cycle and long-term potentiation) were also enriched (Table S3) [16,17,18]. These KEGG pathways were mainly involved in cell proliferation, motility, immune regulation, hormone biosynthesis, neural plasticity and responses to environmental stimuli, which are necessary for insect survival, growth and longevity regulation [8,16,19,20,21,22,23,24,25]. In the CG samples, twenty-one KEGG pathways were enriched for up-regulated DEGs, including cytoskeleton, proteoglycans and immune-related pathways, in response to pathogenic infection (Figure 2c and Table S3), fifteen of which were shared with those in the NG samples. No KEGG pathways were significantly enriched for down-regulated DEGs of CG samples (Table S4). For the SG samples, eight and two KEGG pathways were significantly enriched for up- and down-regulated DEGs, respectively (adjusted p value < 0.05; Figure 2d, Tables S3 and S4). As regards the up-regulated DEGs, the enriched pathways mainly included PPAR (peroxisome proliferator-activated receptor), fatty acid degradation, cytoskeleton proteins, amino acid metabolism and immune response pathways related to bacterial infection, whereas they were related to lipid metabolism and steroid hormone biosynthesis for down-regulated DEGs. Taken together, these results indicate, that compared to WG samples, the NG, CG and SG samples commonly harbored enriched cytoskeleton and immune-related pathways, with each group also exhibiting separate habitat-specific expression patterns. ## 2.2. General Statistics of Enriched KEGG Pathways Based on GSEAs In order to better extract biological insights from the genome-wide expression patterns, multiple GSEAs at both the KEGG pathway and KEGG orthology (KO) levels were conducted, using the normalized and non-normalized datasets. The quantitative aspect of the enriched KEGG pathways can be judged by comparing the sizes of the pie charts (the bigger the pie, the larger the proportion of enriched pathways). The colors of sectors, representing the higher-level functional categories defined according to the KEGG database (https://www.genome.jp/kegg/ (accessed on 16 September 2022)) and the previous study [26], can help to visually identify the changes in gene functional categories and allow a rough comparison of the qualitative aspects of the transcriptional change (Figure 3 and Table S5). In the present study, both the normalized and non-normalized datasets yielded very similar results (Tables S5 and S6). Nonetheless, non-normalized datasets generally resulted in more enriched pathways than normalized ones, especially for the pairwise comparisons of NG vs. WG and NG vs. CG (Table S6), probably due to batch effects (Figure S1), suggesting that the data normalization procedure is necessary. Overall, our GSEA results corroborate the magnitude and complexity of the transcriptional changes revealed by DEGs and the functional enrichment analyses above. The gradually reduced sizes of pie charts, reflecting the decreasing number of enriched pathways (Figure 3a,b; for NG vs. WG, 102; CG vs. WG, 93; and SG vs. WG, 46), suggest the lack significant correlation between differences in gene expression and geographical distance among compared groups, as shown in the DEG and functional enrichment analyses. Interestingly, the presence of reduced overlap in enriched pathways between comparisons (i.e., for NG and WG vs. CG and WG, $57.3\%$ [71] of 124 pathways overlap, whereas for SG and WG vs. CG and WG, only $12.2\%$ [15] of 123 pathways overlap) possibly indicates that transcriptional changes in SG samples qualitatively differed from those in CG and NG samples, as these groups dispersed eastwards from western area of China [15]. The overall statistics of DEGs, KEGG enrichment analyses and multiple GSEAs consistently suggest that the genome-wide expression pattern of the CG samples was more similar to that of NG samples than to that of the SG samples. In addition, more genes and signaling pathways were probably involved in local environmental adaptation when P. glacialis initially dispersed from the western (WG) to central (CG) areas of China, followed by less recruitment of potentially new gene sets for the successive colonization of northeastern (NG) and southeastern (SG) areas, respectively (Figure 3a). ## 2.3. Featured Gene Sets Based on GSEAs In pairwise comparisons to WG samples, the GSEA results based on genome-wide expressed genes reveal that the pathways enriched for mostly up-regulated genes in NG, CG and SG samples are mainly involved in cell signaling, immune system and metabolism, while those enriched for down-regulated genes are markedly related to genetic information processing, cell cycle and aging, regardless of datasets used (Figure 3a and Table S5). Specifically, enhanced pathways, including cytoskeleton proteins, focal adhesion, tight junction, proteoglycans, calcium signaling, tryptophan metabolism, tyrosine metabolism, ECM–receptor interaction, PI3K-Akt, Rap1, Ras, phagosome and pathogens infection-related, were shared in at least two groups out of NG, CG and SG (Figure 4 and Table S5). Among these, cytoskeleton-related proteins can help to maintain cell shape [24]; the focal adhesion-, tight junction-, proteoglycans- and glycosaminoglycans-related pathways are of critical importance in intercellular communication and cellular homeostasis in organisms, and play significant roles in forming the complex biomolecular structures that are necessary for insect survival, growth and development [19,20]; calcium signaling can mediate the environmental sensitivity of the diapause timer, and could be a key integrator of environmental condition (e.g., cold temperature) with downstream hormonal control of diapause [25]; both the tryptophan and tyrosine metabolism may contribute to color pattern in butterflies, and participate in resisting insecticides and defending against a wide range of pathogens, respectively [27,28]; other pathways, such as ECM–receptor interaction, PI3K-Akt, Rap1, Ras and phagosome, can functionally interact with each other to collectively make up an immune defense network [21,29]. These enhanced pathways imply strengthened cellular interactions and somatic maintenance, and improved structural defense and cellular immune response, which may strengthen the constitutive and inducible defenses against pathogen infection, as well as increase the stress resistance [30,31]. In contrast, ribosome, spliceosome, longevity and genetic information processing (e.g., DNA replication and repair, transcription, translation, etc.) pathways were commonly inhibited in at least two groups out of NG, CG and SG (Figure 4 and Table S5), suggesting the repression of cell replication and differentiation as the mechanism underlying the adults’ decelerated or arrested development status. To decipher the shared signaling pathways among different insect groups, we further compared our enriched pathways with previously published genome-wide transcription studies of diapausing D. melanogaster [8]. The results show that almost $48\%$ (23 out of 48) of the enriched pathways in that genome-wide transcription study were shared in our analysis. More importantly, the vast majority of these shared pathways in D. melanogaster were commonly enhanced (e.g., cytochrome P450, ECM–receptor interactions and metabolic-related pathways) or inhibited (e.g., genetic information processing, protein processing and circadian rhythm pathways), as shown in this study. We also compared our data to those of the cabbage butterfly Pieris melete, which is involved in summer and winter diapauses [32]. The results show that a series of signaling pathways related to diapause, such as calcium signaling, insulin signaling, forkhead transcription factor (FOXO), target of rapamycin (mTOR), mitogen-activated protein kinase (MAPK) and hormone-related signaling pathways, were shared between these two butterfly species (Table S5) (reviewed in [32]). The same or similar cases were also identified in other diapausing insect species, including the Megachile rotundata [33], Locusta migratoria [34], Delia antiqua [24], Hyphantria cunea [35] and Drosophila suzukii [36]. Overall, the overlap in enriched functional pathways was commonly enhanced or inhibited among P. glacialis populations and other diapausing insect groups, suggesting that the diapause-linked transcriptional regulation strategy of P. glacialis, accompanied by the success of colonization eastwards, enhance resistance to hostile conditions. Interestingly, nutrient-sensing-related pathways, such as insulin (IS), mTOR and FOXO signaling pathways [37,38,39], were commonly inhibited, especially in NG and CG samples. The insulin signaling pathway can directly or indirectly interact with mTOR and FOXO signaling pathways to form an integrated nutrient-sensing network involved in the regulation of carbohydrate metabolism and energy restore [40,41]. The silencing of nutrient-sensing pathways may be causally related to reduced food intake, as well as to the arrested growth/development, enhanced stress response, increased lifespan, and other phenotypic changes characteristic of insect diapause [8,11,39,42]. In addition, cell cycle-, necroptosis- and apoptosis-related pathways were also systematically suppressed, implying a delayed life cycle, which results are similar to those for Heterorhabditis nematodes and Drosophilia flies [21,43]. Moreover, thirteen gene clusters were found to be enriched in multiple GSEAs based on pairwise comparisons to WG samples (Figure 5 and Table 1). Most of the up-regulated genes in each gene cluster were found to be enriched in NG and CG samples, which are directly or indirectly related to longevity regulation, immune defense and stress responses, whereas those down-regulated were mostly enriched in SG samples, mainly involved in fatty acids and hormone biosynthesis (Figure 5 and Table 1). Among these up-regulated genes, previous studies showed that LIP (lipase) can play a crucial role in fat catabolism responsible for oocyte maturation, sex pheromone biosynthesis and antiviral infection [44,45]; EBPIII (ejaculatory bulb-specific protein 3-like) in the chemosensory protein (CSP) gene family can function as receptors of environmental stimuli and in resistance to insecticides [46,47]; SCARB1 (scavenger receptor class B member 1), an important regulator for cholesterol efflux and steroid hormone production, can also mediate phagocytosis and the antimicrobial peptide pathway in the endoparasitic wasps, involved in central nervous system (CNS)-mediated immune response [48,49]. Both BXA (bombyxin) and ALS (insulin-like growth factor-binding protein complex acid labile subunit) are involved in the insulin signaling pathway, and play important roles in the precise regulation of metabolism, growth, longevity and stress responses through functional interaction with each other [50,51]. Other genes, including MTH (G protein-coupled receptor Mth), CRYAB (crystalline alpha B), SERPINB (serpin B) and CHT (chitinase), have also been found to be mainly associated with longevity regulation, immune defense and stress responses in insects [30,52,53,54]. In addition, the enriched gene clusters with genes mostly down-regulated, including ELOVL (elongation of very long chain fatty acids protein) and FDPS (farnesyl diphosphate synthase), may participate in the unsaturated fatty acids biosynthesis of lipid metabolism, and in the formation of the juvenile hormone (JH) III in insect groups, respectively [55,56]. Furthermore, duplicated genes (e.g., tandem duplications) were commonly found in the enriched gene clusters above, regardless of whether they were up- or down-regulated (Figure 6). Previous studies indicated that duplicated genes can be fixed by positive selection [57], and lead to novel expression patterns, as a mechanism of the genomic adaptation to a changing environment [58]. Notably, two transposon-derived gene clusters (transposable elements, TEs), SETMAR (Histone-lysine N-methyltransferase SETMAR) and NAIF1 (nuclear apoptosis-inducing factor 1), were identified to be significantly enriched, with the former being mostly up-regulated in CG samples, while the latter were down-regulated in SG samples. SETMAR, a fusion gene previously found only in anthropoid primates comprising an N-terminal SET domain and C-terminal Hsmar1-derived (MAR) transposase [59], has been shown to function in DNA repair and enhance resistance to ionizing radiation, and would have contributed to the regulation of a vast gene expression network and epigenetic modification [60,61]. NAIF1, a domesticated transposase that originated from the ancestral Harbinger transposon, can induce apoptosis when overexpressed [60,62]. TEs are likely to be associated with gene expression variation and adaptive signatures in Drosophila [63], and also seem to be involved in the regulation of diapause in different insect groups [64,65]. ## 2.4. Featured Modules Based on WGCNA To obtain further insight into the habitat-specific adaptation mechanisms of P. glacialis populations resulting from diverged colonizing events [15], WGCNA was performed to investigate the co-expressional networks of all expressed genes. Two different subsets (WCN and WCS), reflecting transcription along two different dispersal routes, with each consisting of the normalized TPM values of WG and CG samples combined with those of either NG or SG samples, were used for analyses, respectively. The analysis of the WCN dataset showed that these genes were clustered into 16 major modules (labeled with different colors; the gray module contains the remaining uncorrelated genes) (Figure 7a,b). Six modules (turquoise, blue, purple, magenta, tan and black) were significantly correlated with sampling localities, with high correlation coefficients (Figure 7b). Among them, the turquoise module contained 1819 genes and was highly positively correlated with the western area (correlation coefficient = 0.82, p-value = 3.4 × 10−5), while it was strongly negatively correlated with the northeastern area (correlation coefficient = −0.55, p-value = 0.02). In contrast, the blue module with 783 genes was highly positively correlated with the northeastern area (correlation coefficient = 0.61, p-value = 0.0068), but highly negatively correlated with the western area (correlation coefficient = −0.82, p-value = 3.4 × 10−5). Considering that these two modules contain the top two highest numbers of genes, both of which were also moderately correlated with the central area (\|correlation coefficient\| < 0.3, p-value > 0.05), they have been selected for further enrichment analysis. For the WCN dataset, the KEGG enrichment analysis shows that genes in the turquoise module were primarily related to genetic information processing, protein processing, cell cycle and apoptosis regulation (Figure 7c and Table S7), which are strongly correlated with the cell replication, differentiation and aging processes underlying the developmental status. Most of the genes in this module were down-regulated in samples from the northeastern area (negative correlation) compared to those of the western area (Figure 7b), supporting the developmental arrest status of NG adult samples due to the general silencing of cell division and protein synthesis. In the blue module, the genes were significantly enriched for cell signaling and community, cytoskeleton regulation and immune defense against infections (Figure 7d and Table S7), suggesting that genes in this module were mainly responsible for somatic maintenance and defense system regulation to combat the pathogen infection and to increase the stress resistance. Most of the genes in this module were up-regulated in samples of the northeastern area (positive correlation) compared to those of the western area (Figure 7b), indicating the increased stress resistance and improved immune defense potential of NG samples. Meanwhile, 10 out of 16 modules were found to be moderately correlated with the central area, and the correlation coefficients between modules and sampling localities from the western to northeastern areas of China mostly changed with gradients (Figure 7b). This co-expression pattern probably implies that the transcriptional changes were more quantitative than qualitative between CG and NG samples, consistent with the overall statistics regarding DEGs, KEGG enrichment analyses and multiple GSEAs. In contrast, the analysis of the WCS dataset shows that these genes were clustered into 25 modules with relatively complex correlations between modules and sampling localities (Figure 8a,b), suggesting that the transcriptional changes are both quantitative and qualitative between CG and SG samples. Specifically, a total of 16 modules were significantly correlated with sampling localities (p-value < 0.05, Figure 8b). Among these, six modules (yellow, dark green, dark turquoise, light cyan, royal blue and blue) were positively correlated with the western area. Of these six modules, both the yellow and blue modules were also strongly negatively correlated with the central area, with the vast majority of genes primarily involved in the regulation of growth and development (e.g., pathways in genetic information processing, mTOR and FOXO), cell cycle and apoptosis (Figure 8c,d and Table S8). When compared to samples from the western area, most of the genes in these two modules were down-regulated in samples of the central area, suggesting adult developmental arrest in CG samples. Moreover, out of the two modules (magenta and green) most highly positively correlated with the central area, the green module also strongly negatively correlated with the western area, with most of the genes in this module highly expressed in CG samples (Figure 8e and Table S8). These genes are primarily related to cell signaling, cytoskeleton regulation and immune defense against infections, providing enhanced stress resistance and immune defense. Interestingly, among the other six modules (green-yellow, midnight blue, light green, light yellow, brown and tan) highly positively correlated with the southeastern area, the brown and tan modules contained 580 and 99 genes, respectively, and most of these genes were highly expressed in SG samples and enriched in the pathways of energy metabolism (e.g., oxidative phosphorylation, thermogenesis and fatty acid degradation), carbohydrate metabolism (e.g., glycolysis/gluconeogenesis, pyruvate metabolism and citrate cycle, etc.) and immune response (e.g., MAPK and cGMP-PKG signaling pathways) (Figure 8f,g and Table S8), thus contributing to rapid growth/development, as shown in the GSEA and the resulting earlier emergence time of SG samples compared to other samples. ## 2.5. RNA-Seq Validation Using RT-qPCR In order to validate the RNA-seq, a total of ten genes (juvenile hormone acid O-methyltransferase, JHAMT; hydroxysteroid dehydrogenase-like protein 1, HSDL1; phosphoenolpyruvate carboxykinase, PEPCK; hamartin, TSC1; tuberin, TSC2; GTP-binding protein Rheb, RHEB; calcium/calmodulin-dependent phosphodiesterase 1C, PDE1C; actin-related protein 2, ARP2; integrin beta, ITBX and ITB2L) reported to be involved in diapause regulation in previous studies [8,11,24,35] were selected for testing using RT-qPCR. The results for six representative samples in four localities (XLS1, HDT1, KYS1, KYS2, TMS1 and TMS2) covering the most well-known marginal range of distribution in western, northeastern and southeastern China confirm the consistency of the gene expression pattern with overall high correlation ($R = 0.88$, p-value = 2.7 × 10−17) (Figure S4). The correlations between RNA-seq and qPCR data were extremely strong for eight genes (R > 0.80), while the correlations were less strong for the other two genes (with a range of R values from 0.20 to 0.60) (Figure 9). We speculate that these discrepancies could be related to the methodological difference between RNA-seq and qPCR, which seemed to be common in the transcript-level analyses. Nonetheless, the variation tendencies in the RNA-seq data curve and the qPCR histogram are mostly similar, suggesting our RNA-seq and qPCR data analyses are reliable. ## 3. Discussion As global warming is increasingly exacerbating, rapid climate changes may lead to shifts in species’ ranges, population declines, and even extinctions [66]. In response, diapause can occur at different ontogenetic stages (e.g., in egg, embryonic, larval, pupal or adult stage) in different insect species under various environmental contexts, but usually in a single specific stage for each species [11,32,35,43,64]. In addition, diapause could evolve very rapidly and polyphyletically in different insect lineages (reviewed in [11]). Hence, previous studies have identified different transcriptional patterns of diapause at the gene level among different insect lineages. However, the genetic toolkit of diapause is likely to be observable in the activation/inhibition of the common functional pathways regulating the hallmark diapause-linked phenotypes [11,32]. Therefore, in the present study, we focused mainly on the enriched functional pathways/gene sets to compare the transcriptional patterns observed in P. glacialis populations with analogous patterns published in other insects. Several strategies for large-scale transcriptomic interpretation, such as DEG enrichment analysis, GSEA and WGCNA, were used to investigate the featured pathways/gene set to minimize the disadvantages of individual methods, and to characterize the genome-wide expression patterns for different P. glacialis populations. Substantial functional pathways underpinning the diapause-linked phenotype characteristics, which could contribute to the success of P. glacialis’ colonization out of the QTP from western to eastern China, were herein identified for the first time [15]. A few key functional pathways, including the evolutionarily conserved hormone (endocrine system), insulin-IGF (IIS) and mTOR-related signaling pathways, have been shown to be implicated as key regulators of insect diapause that promote local adaptation [8,11,67]. Among these, hormone-related pathways such as ecdysone (a steroid hormone) and juvenile hormone (JH) have been implicated in reproduction, stress responses and longevity regulation, and play key roles in insect diapause [8,35,67,68]. In the present study, a series of enriched pathways (e.g., cholesterol metabolism and cytochrome p450, etc.) and one gene cluster (SCARB1) involved in steroid hormone production were found to be uniquely enhanced in NG samples. Among them, both cholesterol metabolism and cytochrome p450 can participate in 20-hydroxyecdysone (20-HE, the active form of ecdysone) biosynthesis [43]. In contrast, both the enriched pathway related to steroid hormone biosynthesis and the gene cluster FDPS responsible for the formation of the JH III were shown to be significantly inhibited in SG samples (Figure 2d and Figure 5). This result suggests that the hormonally regulated state of diapause was likely to be different among the adult P. glacialis populations. Given the fact that the specific hormones and their levels are individual-, species- and diapause stage-dependent [8,24,43,69,70], the hormone-inducing diapause regulation patterns among P. glacialis populations deserve detailed attention in future functional studies. The silencing of the IIS and mTOR signaling pathways is related to the suppression of growth/development, enhanced stress response and extend lifespan in several diapausing insect groups and nematode Caenorhabditis elegans [8,11,39]. In the current study, functional pathways linked to IIS and mTOR were generally suppressed, especially in NG and CG samples. The gene expression levels of several core molecular components in these two pathways (e.g., PEPCK, TSC1, TSC2 and RHEB) were validated via qPCR (Figure 9). The increased expression of PEPCK, a potential marker for distinguishing between diapause and direct development [71], can enhance gluconeogenesis, as was also found in SG samples herein and other diapausing insects [8]. It is worth noting that several other IIS-related pathways (e.g., insulin secretion, FOXO and relaxin signaling pathway) and two gene clusters (e.g., duplicated genes BXA and ALS) were concurrently enhanced or inhibited (Figure 5 and Table S5), and this probably indicates the concomitant up-regulation of some positive and negative components of IIS-related pathways for precise regulation during the phase of diapause. A similar regulation pattern was also described in the diapausing flies [8,11]. Under the hormonal control and regulation of the key signaling pathways above, a series of other pathways related to diapause regulation have been well presented in our enrichment analyses, such as those involved in genetic information processing, cell signaling, metabolism, immunity, stress response, cell cycle and aging, etc. These enriched pathways could interact with each other and form a series of complex regulatory networks (reviewed in [8]), supplying new evidence that complex, polygenically expressional variation may be involved in adaptive regulation in diapause, which is likely responsible for the successful colonization of new habitats by P. glacialis populations. In the present study, both the DEG enrichment analysis and GSEA results indicate that enriched pathways related to cell signaling, the immune system and the endocrine system were mostly enhanced, while those related to genetic information processing were generally inhibited in NG samples regardless of whether they were compared to WG or CG samples (Figure 2, Figure 3 and Figure 4 and Table S5). In contrast, enhanced genetic information processing- but inhibited cell signaling-related pathways were found in SG samples relative to CG samples, different from the enrichment results of other pairwise comparisons. Furthermore, a series of duplicated genes (gene clusters including TEs) functioning in germ cell maturation, hormone or sex pheromone biosynthesis, immune defense and longevity regulation, important to survivability, growth and reproductive capacity, were identified to be mostly up-regulated in NG and/or CG samples. It is worth mentioning that one of the TEs herein, SETMAR, has been shown to contribute to the emergence of new gene regulatory networks, in that a modest overexpression of SETMAR can lead to the misregulation of 1500 genes [61]. However, only three gene clusters functionally different from those enriched in CG and NG samples were identified to be significantly enriched in SG samples in the present study (Table 1). Though moderate expression changes were found for the vast majority of duplicated genes herein, the co-expression pattern showing most genes commonly up- or down-regulated probably indicates a transcriptional pattern for P. glacialis populations in diapause under environmental stress conditions, which maybe provide some insights into how adaptation to environmental changes influences duplicated gene expression [58,72], although further investigations are needed. Moreover, the results of our WGCNA also reveal that the featured modules were significantly correlated with sampling localities underlying the habitat-specific adaptability of different P. glacialis populations. The signaling pathways enriched in the featured modules were found those responsible for immune defense, stress resistance and somatic maintenance in the CG samples (Figure 8), which could contribute to the success of colonization from western to central China. This transcriptional regulation pattern seemed to be strengthened with the successive colonization from central to northeastern China. Though a substantial fraction of the enriched signaling pathways underpinning the diapause-linked phenotype were shared among SG, CG and NG samples, many enhanced metabolism- and immune defense-related pathways were uniquely enriched in SG samples compared to CG samples (Tables S5 and S8), implying the importance of metabolic and immune regulation for successive colonization from central to southeastern areas. Based on the results above, it is reasonable to speculate that P. glacialis populations, especially in central to northeastern China, have probably evolved several remarkable adaptive characteristics accompanied by their dispersal out of the QTP, including higher hormone biosynthesis levels, stronger somatic maintenance and more sensitive responses to environmental stimuli than populations in southeastern China. On the other hand, for P. glacialis populations in southeastern China, the decreased ecdysone and/or JH level can induce or promote reproductive arrest, slowing aging and long-range migration [67,68]. Thus, we speculate that adult P. glacialis populations in southeastern China are more similar to migrant adults of monarch butterfly [68], and could temporarily suspend reproduction in response to environmental stress (e.g., relatively higher annual mean temperature and precipitation in southeastern than in northeastern China, as shown in Figure S5). Moreover, under the regulation of upstream signaling pathways (e.g., 20HE, JH and IIS) [67], they probably utilize the lipids and glycogen energy reserves stored in their body for their survival and growth. The results of GSEA and WGCNA confirm that various unique pathways mainly responsible for energy metabolism were significantly enhanced in SG samples, including oxidative phosphorylation, thermogenesis, fatty acid degradation, glycolysis/gluconeogenesis, amino sugar and nucleotide sugar metabolism, and glyoxylate and dicarboxylate metabolism (Figure 8f and Table S5). All these pathways can catabolize energy reserves, such as fatty acids, glucose and other sugar, to generate ATPs for flight and survival [64,73,74]. The glyoxalate pathway has been known to be important in dauer stages of Caenorhabditis elegans, and has also been reported in the infective juvenile stage of entomopathogenic nematodes [21]. In addition, a number of synergistically enhanced pathways with functions related to microbial defense and immune response (e.g., retrograde endocannabinoid signaling, toll-like receptor and NF-κB signaling pathway) were also identified in GSEAs, all of which may have contributed to the adaptation of P. glacialis in southeastern China. Together, combined with the overall statistics of DEGs, KEGG enrichment analysis, GSEA and WGCNA, all our results consistently reveal the habitat-specific adaptability of different P. glacialis populations, and also suggest that the genome-wide expression patterns of the CG samples were more similar to those of NG samples than to SG samples, which is consistent with the results of population genetics analyses based on the genotyping-by-sequencing (GBS) data of our recent study [15]. ## 4.1. Sample Collection P. glacialis imago individuals ($$n = 24$$) were collected from eight localities, covering nearly the entire known range of distribution in China. For each locality, all sampling was performed at the same time during the day, between 10:00 and 13:00, to avoid the potential effect of circadian variability on the expression profiles. According to the meteorological data of the sampling locality (Figure S5) and the geographical dispersal pattern of P. glacialis as shown previously [15], the samples here were divided into four groups, classified as the western group (WG), central group (CG), northeastern group (NG) and southeastern group (SG), respectively (Figure 1 and Table S1). All samples were initially preserved in RNA stabilization solution (Sangon Biotech, Shanghai, China) in the field and transferred to −80 °C until RNA extraction. Muscle tissues from the thorax of three individuals per sampling locality were used for purified RNA extraction. ## 4.2. mRNA-Seq Library Construction and Illumina Sequencing Library construction and Illumina sequencing were performed following the methods in the previous study [13]. The sequencing library was paired-end-sequenced using the Illumina HiSeq 2500 platform (Shanghai Personal Biotechnology Co. Ltd, Shanghai, China). After the adaptor contamination was removed, the reads were screened to trim the bases with a quality score of Q < 20 using 5-bp windows, and reads of less than 50 bp and ambiguous nucleotides were removed. ## 4.3. Mapping, Transcript- and Gene-Level Abundance Estimation After quality filtering, all the remaining reads were collected and then mapped to the P. glacialis genome sequence to acquire the genes for each sample using HISAT2 v2.1.0 [75] and StringTie v2.1.5 [76]. The assembled transcripts of each sample were merged using StringTie v2.1.5 –merge, creating an updated annotation file for the P. glacialis genome. Transcript abundances were estimated using StringTie v2.1.5 with the parameters –e and –B. A gene-level read count matrix was generated using the prepDE.py script provided as part of the StringTie package. ## 4.4. Expression Level Normalization and Differential Expression Analysis A pipeline was set up to normalize the data for all samples. Firstly, TPM (transcripts per million) values for each gene were calculated based on the read count and exon length using TBtools [77], the sum of which for all genes in each sample was one million. Secondly, the online tool of Majorbio Cloud Platform was used to remove batch effects [78], and then the expression values were normalized by the scaling procedure as previously described [79,80]. Specifically, among the genes with expression values in the interquartile range (25–$75\%$) in terms of average expression levels across samples, a total of 1000 genes with the most conserved ranks across all samples were identified, and their median expression levels were assessed in each sample. Finally, scaling factors that adjust these medians to a common value were derived, and were then used to scale the expression values of all genes in the samples [79]. The resulting gene expression values were used for downstream analyses. Moreover, TPM values without normalization, the sum of which was one million for each sample, were also used for subsequent analyses for comparison. Differential gene expression analysis between groups was performed to reveal the long-term habitat-specific adaptation mechanisms. Thus, five differentially expressed gene datasets, derived from comparisons of the NG vs. WG, SG vs. WG, CG vs. WG, NG vs. CG, and SG vs. CG groups, were focused on. Genes with a change in expression level satisfying \|log2FoldChange\| ≥ 1 and Benjamini–Hochberg adjusted p value < 0.05 were defined as DEGs using DESeq2 and edgeR based on the read counts, with DESeq2 using the relative log expression (RLE) normalization and edgeR using the trimmed mean of M values (TMM) normalization [81,82]. The shared DEGs obtained from DESeq2 and edgeR in each pairwise comparison were retained for further analyses to reduce the false positives. Subsequently, KEGG enrichment analyses were performed to determine the biological features of these DEGs with TBtools, using the adjusted p value < 0.05 as the cutoff value [77]. In addition, principal component analysis (PCA) was conducted to reveal the clustering effects in the transcriptomic profiles of all groups. ## 4.5. Gene Set Enrichment Analysis (GSEA) Multiple gene set enrichment analyses (GSEAs) for pairwise comparisons were performed based on the normalized and non-normalized TPM values, respectively, using the GSEA v4.2.3 software [83]. To decipher gene function enrichment at different levels, gene sets for GSEA were defined using KEGG orthology (KO) identifiers and pathway categories, respectively, and the defined genes from the whole genome were here used as the default background distribution. Gene sets with a normalized enrichment score (\|NES\|) >1, p-value < 0.05 and FDR < 0.25 were considered statistically significant [83]. The commonly enriched KEGG pathways among different comparisons were visualized using the module EnrichmentMap using Cytoscape software [84,85]. For each significantly enriched gene set defined using the KO identifier, the following procedure was also used to verify the members in each gene cluster in the P. glacialis genome. The published representative homologous proteins in Insecta (including Drosophila melanogaster, Bombyx mori, Apis mellifera, Danaus plexippus, Papilio machaon, Papilio bianor, Pieris rapae, etc.) downloaded from the National Center for Biotechnology Information (NCBI, https://www.ncbi.nlm.nih.gov (accessed on 12 October 2022)) or InsectBase (http://www.insect-genome.com (accessed on 12 October 2022)) were used as queries to search against the genome of P. glacialis, using the BLASTP algorithm (E-value < 10−5). The genes with identities lower than $30\%$ were filtered out, and then subjected to InterPro (www.ebi.ac.uk/interpro (accessed on 15 October 2022)) to confirm the presence of the conserved domain [86]. After removing redundancies, the top hits for putative genes were retained. ## 4.6. Weighted Gene Co-Expression Network Analysis (WGCNA) Weighted gene co-expression network analysis (WGCNA) can be used as a data exploratory tool to identify highly interconnected gene clusters in different modules across samples using unsupervised clustering [87]. In this study, WGCNA was used to identify key gene clusters and then correlate their expression patterns to the sampling locality, so as to reveal the habitat-specific adaptation mechanisms of P. glacialis underlying the extraordinary adaptability to local seasonal environmental challenges, with the following parameters: unsigned for TOMType, 30 for minModuleSize, 0.35 for mergeCutHeight, and default values for the other parameters. ## 4.7. Validation of Gene Expression by Real-Time RT-qPCR To validate the expression patterns derived from our RNA-Seq analysis, ten genes, including both DEGs and non-DEGs among the representative samples covering the most well-known marginal range of distribution in western, northeastern and southeastern China, were selected for real-time reverse transcription (RT) quantitative PCR analysis (primers were listed in Table S2). Reversed cDNA was synthesized using the PrimeScript™ 1st stand cDNA Synthesis Kit (Takara, Shanghai, China) from total RNA isolated as described above. All RT-qPCR experiments were run in triplicate using the LightCycler 480 II (Roche Diagnostics, Basel, Switzerland) with SYBR green (Vazyme, Nanjing, China) with the following cycling parameters: 95 °C for 5 min, and 40 cycles of 95 °C for 15 s, 60 °C for 30 s. The amplification and detection of only one PCR product was confirmed using melting curve analysis of the amplification products at the end of each PCR. The expression levels of different genes were analyzed using the comparative CT method (2−ΔΔCt method) [88]. To ensure the robustness of the reference gene, the gene expression stability of commonly used housekeeping genes under biotic conditions was evaluated according to previous studies [89], and the elongation factor 1 alpha (EF1-α) gene was finally chosen as the reference gene. The R values of the Spearman’s correlation coefficient were calculated to represent the correlations between the data obtained from the qPCR and RNA-seq. ## 4.8. Statistical Analysis Correlation analysis, hierarchical clustering, and principal component analysis (PCA) were performed using the SPSS software (version 23.0; IBM Inc., Chicago, IL, USA) or the online tool of Majorbio Cloud Platform [78]. The nonparametric method with Kruskal–Wallis or Wilcoxon signed ranks test was also conducted using the SPSS software. In all analyses, statistical significance was shown by a p-value of less than 0.05. ## 5. Conclusions In the present study, we profiled relatively large-scale transcriptomics of different geographic populations of P. glacialis in China via several strategies for data interpretation. Based on the stringent screening criteria of DEGs and gene function enrichment at different levels, with different groups (WG or CG samples) used as the control, all results consistently indicate that substantial pathways involved in immune response, metabolic processes, cell signaling, developmental processes, reproduction, transcription, translation, protein processing, cell cycle and aging are shared with those revealed in studies of diapausing insect groups, most of which are commonly enhanced or inhibited, thus underpinning the diapause-linked phenotype of the adult P. glacialis populations in central to eastern China. Moreover, different gene enrichment patterns were also revealed, probably suggesting the habitat-specific adaptability of different P. glacialis populations. In addition, a suite of duplicated genes (including two transposable elements) with co-expression patterns could promote the plastic responses of P. glacialis to different environmental challenges. Taken together, our data provide a population-wide and comprehensive analysis of transcriptional changes implying the diapause-like status of geographic populations of P. glacialis in central to eastern China, and show the utility of this mountain butterfly species as a model to analyze the genetics of diapause and its effects on adaptation to heterogeneous environmental conditions. ## References 1. Zhang J., Marshall K.E., Westwood J.T., Clark M.S., Sinclair B.J.. Divergent transcriptomic responses to repeated and single cold exposures in. J. Exp. Biol. (2011) 214 4021-4029. DOI: 10.1242/jeb.059535 2. Chown S.L., Gaston K.J.. Macrophysiology for a changing world. Proc. R. Soc. B-Biol. Sci. (2008) 275 1469-1478. DOI: 10.1098/rspb.2008.0137 3. 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--- title: Establishment of an Individual-Specific Nomogram for Predicting the Risk of Left Ventricular Hypertrophy in Chinese Postmenopausal Hypertensive Women authors: - Ruowen Yuan - Jianshu Chen - Shangyun Zhang - Xiaowei Zhang - Jing Yu journal: Medicina year: 2023 pmcid: PMC10058473 doi: 10.3390/medicina59030598 license: CC BY 4.0 --- # Establishment of an Individual-Specific Nomogram for Predicting the Risk of Left Ventricular Hypertrophy in Chinese Postmenopausal Hypertensive Women ## Abstract Background and Objectives: The physiological phenomenon peculiar to women, namely menopause, makes the occurrence of left ventricular hypertrophy (LVH) in postmenopausal hypertensive women more characteristic. Less is known about the risk of developing LVH in Chinese postmenopausal hypertensive women. Thus, the present study was intended to design a nomogram for predicting the risk of developing LVH in Chinese postmenopausal hypertensive women. Materials and Methods: Postmenopausal hypertensive women aged between 49 and 68 years were divided into either the training set ($$n = 550$$) or the validation set ($$n = 284$$) in a 2:1 ratio. Patients in the validation set were followed up for one year. A stepwise multivariable logistic regression model was used to assess the predictors of LVH in postmenopausal women with hypertension. The best-fit nomogram was executed using R software. The calibration and decision curve were employed to verify the predictive accuracy of the nomogram. The results were evaluated in the validation set. Results: Menopause age (OR = 0.929, $95\%$ CI 0.866–0.998, $$p \leq 0.044$$), BMI (OR = 1.067, $95\%$ CI 1.019–1.116, $$p \leq 0.005$$), morning systolic blood pressure (SBP: OR = 1.050, $95\%$ CI 1.032–1.069, $$p \leq 0.000$$), morning diastolic BP (DBP OR = 1.055, $95\%$ CI 1.028–1.083, $$p \leq 0.003$$), angiotensin II receptor blocker (ARB) utilization rate (OR = 0.219, $95\%$ CI 0.131–0.365, $$p \leq 0.000$$), LDL-C (OR = 1.460, $95\%$ CI 1.090–1.954, $$p \leq 0.011$$) and cardio-ankle vascular index (CAVI) (OR = 1.415, $95\%$ CI 1.139–1.757, $$p \leq 0.028$$) were associated with LVH in postmenopausal hypertension patients. The nomogram model was then developed using these variables. The internal validation trial showed that the nomogram model described herein had good performance in discriminating a C-index of 0.881 ($95\%$ CI: 0.837–0.924) and high quality of calibration plots. External validation of LVH-predictive nomogram results showed that the area under the ROC curve was 0.903 ($95\%$CI 0.900–0.907). Conclusions: Our results indicate that the risk prediction nomogram model based on menopausal age, BMI, morning SBP, morning DBP, ARB utilization rate, LDL-C and CAVI has good accuracy and may provide useful references for the medical staff in the intuitive and individualized risk assessment in clinical practice. ## 1. Introduction Hypertension has been identified as the main risk factor for cardiovascular disease (CVD) and also an important reason for the increased morbidity and mortality of CVD [1,2] It is estimated that various types of CVD account for about $30\%$ deaths worldwide each year, and around $50\%$ of these deaths are affected by CVD directly related to hypertension [3]. Left ventricular hypertrophy (LVH) is one of the most prominent manifestations of target organ damage in hypertensive patients, and an independent risk factor affecting the prognosis of hypertensive patients [4]. In the past few decades, immense researches have specifically focused on long-term pathological cardiac hypertrophy that can lead to arrhythmias, heart failure, and sudden cardiac death, increasing the risk of death [4,5]. Clinical studies have demonstrated that gender affects the formation and development of LVH [5,6]. The prevalence of hypertension and hypertension-mediated organ damage (HMOD) in premenopausal women is generally lower than that in men of the same age, but this gender advantage disappears rapidly after menopause [7]. In fact, menopause significantly increases the prevalence of hypertension and HMOD [8]. The incidence of LVH in postmenopausal women is much higher than that in men of the same age group [9]. Early screening of high-risk groups who may have LVH in postmenopausal hypertension patients and active formulation of intervention measures under the guidance of doctors are of great significance to improve the quality of life and long-term prognosis of postmenopausal women with hypertension. Several studies have focused on risk factors associated with the presence of LVH in postmenopausal women [10]. However, there is no exploratory study to assess the probability of future LVH risk in postmenopausal hypertension. Therefore, the purpose of this study is to establish a personalized nomogram model based on clinical data to predict the risk of LVH in Chinese postmenopausal hypertension, so as to guide the clinical screening of high-risk populations. ## 2.1. Trial Design and Participants 1486 postmenopausal hypertensive women aged between 49 and 68 years were recruited from Lanzhou University Second Hospital December 2017 to December 2019. Inclusion criteria were as follows: [1] the diagnosis of hypertension was determined by experienced physicians in accordance with 2010 Chinese guidelines for the management of hypertension diagnostic criteria for hypertension (systolic blood pressure ≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg) [11]; [2] menopause, which refers to the physiological phenomenon of complete ovarian failure and permanent cessation of menstruation in women with age (elevated blood pressure (BP) in women after one year of physical menopause is called postmenopausal hypertension) [12]; and [3] studies included participants with complete clinical data. Exclusion criteria included: [1] patients who were diagnosed with arterial hypertension before menopause; [2] heart valve disease, coronary artery disease, diabetes mellitus, hyperuricemia, secondary hypertension and heart valve disease, coronary artery disease and other cardiopathies; [2] ovarian hysterectomy; and [3] hepatic and renal dysfunction. After screening, 846 participants were allocated in a 2:1 ratio to either the training set ($$n = 550$$) or validation set ($$n = 284$$). Participants in the validation set were followed up for one year. The sample size was estimated based on expected differences in the main outcome LVH. Based on our team’s preliminary research, sample size estimation was calculated for a sample power of $46\%$, with the allowable error of $4\%$, at the test level of 0.05 [13]. In this study, the permissible dropout rate was $20\%$. This prospective study was reviewed and approved by the Ethics Review Committee of Lanzhou University Second Hospital (2018A-096). ## 2.2. Clinical Data Collection General clinical data were collected including age, body mass index (BMI), educational level, smoking history, drinking history, family history of hypertension, history of antihypertensive drug use, morning systolic BP (SBP), and morning diastolic BP (DBP). Morning hypertension is measured after a patient wakes up without any activity, including taking antihypertensive medications. Morning hypertension is a home BP measurement. BMI was defined as weight divided by height squared (BMI < 18.50 kg/m2 (underweight = 1), 18.5–23.99 kg/m2 (normal = 2), 24–27.99 kg/m2 (overweight = 3), and ≥28.00 kg/m2 (obese = 4)) [14]. Morning BP refers to the home blood pressure monitoring results within 1 h after waking up in the morning (before taking medicine and breakfast) or the BP between 2 h after waking up or 6:00–10:00 in the morning recorded by the ambulatory BP monitoring [15]. ## 2.3. Echocardiography The Philips IE33 ultrasound system was used to measure the cardiac structure. The measurements were based on guidelines from the American Society of Echocardiography and the European Society of Cardiovascular Imaging. The mean values of three cardiac cycles were used as the final measurements for all the indexes. Reflecting cardiac structural indicators include left ventricular end-diastolic diameter (LVEDD), interventricular septal thickness (IVST), LV posterior wall thickness (LVPWT). LV mass index values (LVMi) were calculated by LVMI = 0.8 × 1.04 × [(LVEDD + IVST + LVPWT)3 − LVEDD3] + 0.6/body surface area. The diagnostic criteria for LVH were according to the 2018 ESC/ESH Guidelines for the management of arterial hypertension: LVMI ≥ 115 g/m2 (male) or ≥95 g/m2 (female). Based on the diagnostic criteria of female LVH, postmenopausal female hypertension patients were divided into an LVH group and a non-LVH group. The ultrasonic data of each group were measured repeatedly for 3 times by professionals. The average of the three measurements is taken as the final measurement result. ## 2.4. Laboratory Testing Major laboratory indicators were tested in our central laboratories. The relevant indexes were determined by Cobas-8000 automatic biochemical analyzer (Roche Diagnostics, Mannheim, Germany). ## 2.5. Vascular Function The MB3000 arteriosclerosis tester was used to examine vascular sclerosis, including cardio-ankle vascular index (CAVI) reflecting arterial elasticity and arteriosclerosis. After participants rested on their back for 15 min, trained technicians placed appropriately sized cuffs on the patient’s upper arms and ankles, respectively. Electrocardiogram electrodes were installed on both wrists and the heart sound sensor was attached to the sternum in the second intercostal space. The knee pulse sensor was mounted on the patient’s knee and the airbag was aligned with the center of the popliteal fossa. After entering the patient information, the machine automatically measured and calculated the CAVI value. CAVI = a [(2ρ/ΔP) × ln(Ps/Pd)PWV2] + b (ρ: blood viscosity, Ps: SBP, Pd: DBP, ΔP: Ps-Pd, PWV: pulse wave velocity). ## 2.6. Questionnaire Survey In the form of face-to-face interview and questionnaire, the researchers filled out the survey records. The Mini-mental State Examination (MMSE) scale was used to preliminarily assess the participants’ intellectual status and degree of cognitive impairment [16]. Sexual function in postmenopausal women with hypertension was assessed by the Female Sexual Function Index (FSFI) scale [17]. The study was conducted by trained investigators according to strict form-filling explanations. ## 2.7. Follow-Up Patients in the validation set were followed up for one year. At the end of the follow-up visit, the following contents were recorded: [1] general clinical characteristics; [2] laboratory, echocardiography, and vascular sclerosis examination results; and [3] result of interview and questionnaire. Patients lost to follow-up and with incomplete follow-up data were excluded from the study. ## 3. Statistical Analysis R software and SPSS26.0 statistical software were used to process all the data. Continuous variables were tested for normal distribution by Kolmogorow–Smirnov test. Measurement data that conformed to the normal distribution were expressed as means ± standard deviation (SD), while those that did not conform to the normal distribution were presented as median. The categorical variables were expressed as values and percentages. Continuous variables were compared using the Student T test or the Mann–Whitney U test. The chi-square test was used to compare the classifying variables. Nonparametric tests were applicable to data that were not normally distributed. Variables were subjected to multivariable logistic regression analysis to determine independent factors associated with LVH in postmenopausal hypertensive patients. Finally, a nomogram was established based on the identified independent risk factors. The method of Bootstrap repeated sampling was used for internal validation of the model, and the calibration curve was drawn to evaluate the consistency of the model. The C-index and AUC were used to evaluate the differentiation or accuracy of the model. The closer the C-index and AUC value to one, the more accurate the prediction ability of the column chart would be. We also used the decision curve to evaluate the nomogram. In addition, receiver operating characteristic curve (ROC) was drawn, and area under curve was calculated for external validation. $p \leq 0.05$ was considered statistically significant. ## 4.1. Baseline Characteristics and Risk Factors of LVH Women with Postmenopausal Hypertension From December 2017 to December 2019, 846 participants were screened for eligibility (Figure 1). In the training set, there were 105 LVH patients in the study population, with an incidence of $18.5\%$. In the validation set, 15 patients were lost to follow-up and 9 patients withdrew from the study for personal reasons during the one-year follow-up. 45 patients were eventually assigned to the LVH group and 215 to the non-LVH group. The result of univariate analysis indicated that, compared with the non-LVH group, the LVH group had higher morning BP, BMI, earlier menopause, higher angiotensin II type I receptor blockade (ARB) utilization rate, and lower MMSE score. There was no significant difference in waist-to-hip ratio, educational level and FSFI score between the two groups. All patients had normal left ventricular systolic function and ejection fraction. The analysis showed significant differences in low-density lipoprotein cholesterol (LDL-C), CAVI, LVEDD, IVST, LVPWT, and LVMI between the two groups. There was no statistical difference in the remaining indexes. The clinical data of the postmenopausal hypertensive patients with and without LVH are summarized in Table 1. The indicators of echocardiography and vascular function in the two groups are summarized in Table 2. ## 4.2. Establishment and Internal Validation of LVH-Predictive Nomogram The results of multivariable logistic regression analysis showed that menopause age (OR = 0.929, $95\%$ CI 0.866–0.998, $$p \leq 0.044$$), BMI (OR = 1.067, $95\%$ CI 1.019–1.116, $$p \leq 0.005$$), morning SBP (OR = 1.050, $95\%$ CI 1.032–1.069, $$p \leq 0.000$$), morning DBP (OR = 1.055, $95\%$ CI 1.028–1.083, $$p \leq 0.003$$), ARB utilization rate (OR = 0.219, $95\%$ CI 0.131–0.365, $$p \leq 0.000$$), LDL-C (OR = 1.460, $95\%$ CI 1.090–1.954, $$p \leq 0.011$$) and CAVI (OR = 1.415, $95\%$ CI 1.139–1.757, $$p \leq 0.028$$) were independent predictors of LVH in postmenopausal women with hypertension (Table 3). Based on the above analysis of independent predictors and professional knowledge, a nomogram was constructed to visualize the logistic regression model (Figure 2A). For example, a 55-year-old menopausal patient with hypertension (8 points) who did not take ARB drugs (25 points) had an early morning SBP of 150 mmHg (28 points), DBP of 85 mmHg (58 points), LDL-C of 3 mmol/L (5 points), BMI greater than 24 kg/m2 (20 points), CAVI of 16 (30 points), had a total score of 174 points; the predicted risk value using the nomogram was about $30\%$ (Figure 3). The C-index was used to evaluate the discrimination degree of the nomogram, namely concordance index (C-index) = 0.881 ($95\%$ CI 0.837–0.924), showing its good accuracy (area under the receiver operating characteristic curve (AUC) = C-index = 0.881) (Figure 4A). After the internal verification of the nomogram model by the method of Bootstrap repeated 1000 times sampling, a high-quality calibration curve of the prediction model was obtained, indicating that there was a good consistency between the prediction model and the actual observed results (Figure 4B). In the decision curve, the X-axis represented threshold probability and the Y-axis represented net benefit. The solid blue line represents the nomogram’s prediction of LVH risk in postmenopausal women with hypertension, the solid gray line represents the hypothesis that all patients had exacerbation (all), and the solid black line represents the hypothesis that none of the patients had exacerbation (none), as shown in Figure 4C. The decision curve analysis showed that the use of this nomogram to assess the risk of LVH in postmenopausal women with hypertension had some significance. ## 4.3. External Validation of LVH-Predictive Nomogram About $17.3\%$ of postmenopausal hypertension patients developed LVH during a one-year follow-up in the validation set. The predictive value of the model for the future LVH of postmenopausal hypertension was analyzed by drawing the ROC curve. The results showed that the area under the ROC curve was 0.903 ($95\%$ CI 0.900–0.907) (Figure 2B). ## 5. Discussion In this study, the nomogram based on clinical analysis was constructed to evaluate the risk of LVH in Chinese postmenopausal hypertensive women. The results of this study presented that menopause age, BMI, morning SBP, morning DBP, ARB utilization rate, LDL-C and CAVI were included in the prediction model. The nomogram showed good consistency and discrimination in predicting the risk of LVH in Chinese postmenopausal hypertensive patients. This tool can help clinicians identify high-risk patients with LVH in postmenopausal hypertensive women and initiate appropriate interventions without requiring complex medical examination. Why not use the electrocardiogram (ECG) or echocardiography to assess LVH in postmenopausal women with hypertension? It is well known that the ECG has a low sensitivity for diagnosis of LVH. The sensitivity, specificity, positive predictive value and negative predictive value of ECG criteria for LVH were 12–$29\%$, 93–$96\%$, 62–$71\%$ and 67–$71\%$, respectively [18]. In contrast, three-dimensional echocardiography was more accurate in evaluating LVH results compared with ECG, but has limited usability and high technical requirements. More importantly, ECG and echocardiography can only assess the LVH that has occurred, and cannot predict the possible risk of LVH in the future. However, the nomogram can visualize the results of complex logistics regression equations, and accurately predict the probability of an individual’s actual outcome event based on the value of the prediction parameters [19]. This tool can make the results of predictive models more readable, help clinicians to evaluate patients and formulate effective treatment strategies. At present, more and more studies have used the nomogram model to predict risk and prognosis of disease. In this study, a nomogram based on seven easily accessible items was used to assess the incidence of LVH in postmenopausal hypertensive women in China. The results of the calibration curve and the decision curve showed that the nomogram model had favorable recognition and calibration capabilities, which means that our nomogram may be widely used in clinical practice. After menopause, the ovarian function fails and the estrogen level in the body undergoes significant change [20]. The level of circulating estrogen and estrone would decrease by more than $90\%$ and $70\%$, respectively [21]. Clinical and basic studies have shown that estrogen deficiency will further promote the development and progression of LVH [22,23]. Therefore, the earlier the age of menopause, the less estrogen protects the cardiovascular system and the higher the risk of LVH. The incidence of obesity in postmenopausal women is as high as $40\%$, and it is often accompanied by the occurrence of metabolic syndrome [24]. The increase in body mass is proportional to the incidence of CVD [25]. In their study involving 30,920 individuals including 11,792 obese patients, Lavie et al. found that the incidence of LV geometric abnormality increased by $49\%$ in obese subjects, $34\%$ in patients with centripetal hypertrophy, and $7\%$ in patients with eccentric hypertrophy, which is consistent with the finding of the present study that the lower the BMI, the lower the risk of LVH in postmenopausal women with hypertension [26]. Morning blood pressure was reported to be significantly related to LVH and LV diastolic function [27]. Target organ damage could still be observed in patients with morning hypertension who received antihypertensive therapy [28]. Shibamiya et al. found that the risk of LVH increased by $23\%$ for every 10 mmHg increase in morning systolic blood pressure [29]. The results of this study also demonstrated that inadequate morning blood pressure control was the main reason for the increased risk of LVH in postmenopausal hypertension patients. In addition, this study also suggested that the use of antihypertensive drug ARB was associated with the risk of LVH in postmenopausal women with hypertension. The renin-angiotensin-aldosterone system is an important target for anti-hypertension and reversing LVH [30]. Compared with drugs that simply reduce the level of angiotensin II (AngII), such as angiotensin-converting enzyme inhibitors (ACEI), ARB can activate the ACE2-Ang (1–2)-Mas system by increasing the level of endogenous AngII to play a cardioprotective effect [31]. It is worth noting that the univariate analysis of this study revealed that compared with the non-LVH group, the LVH group had lower MMSE scores and more severe cognitive impairment. There is tropism evidence that LVH is independently associated with cognitive dysfunction. Scuteri et al. reported that the existence of LVH was negatively correlated with cognitive performance, implying that the higher the LVMI, the worse the MMSE score [32]. The possible mechanism linking LVH and cognitive dysfunction is the presence of cerebral white matter damage (WMD) [33]. Studies found that patients with cardiovascular risk factors had varying degrees of WMD in the dorsolateral prefrontal areas and the lateral orbitofrontal circuits [33,34]. However, the reason why MMSE cannot be a risk factor for predicting LVH in future may be that [1] the results of the study were affected by the cross-sectional design; [2] the limitations of cognitive ability assessment using a single MMSE reduced the sensitivity of detecting specific cognitive difficulties from vascular origin. Based on the seven independent risk factors (menopausal age, BMI, morning blood pressure, ARB use of antihypertensive drugs, LDL-C and CAVI), this study established for the first time an individual nomogram model to predict the risk of LVH in Chinese postmenopausal women with hypertension. After menopause, the ovarian function fails and the estrogen level in the body undergoes significant change [20]. After menopause, the ovarian function fails and the estrogen level in the body undergoes significant change [20]. The level of circulating estrogen and estrone may decrease by more than $90\%$ and $70\%$, respectively [21]. Therefore, the prevalence of the post-menopausal women’s hypertension and HMOD is significantly increased. Early screening of high-risk groups who may have HP in post-menopausal women and active formulation of intervention measures under the guidance of doctors are of great significance to improve the quality of life and long-term prognosis of postmenopausal women. Therefore, the purpose of this study is to establish a personalized nomogram model based on clinical data to predict the risk of LVH around the world in post-menopausal women, so as to guide the clinical screening of high-risk populations. It is of great significance for clinicians to identify high-risk groups and take more targeted prevention and treatment measures. However, the sample size in this study was small and the included influencing factors were limited and these data have not been verified in different populations outside China. These deficiencies limit the accuracy of the results, which can be further verified by multi-center and large sample data. ## 6. Conclusions The present study’s results have a great impact on the prevention strategy of LVH in postmenopausal hypertension patients. Our results indicate that the risk prediction nomogram model based on menopausal age, BMI, morning SBP, morning DBP, ARB utilization rate, LDL-C and CAVI has good accuracy and may provide useful references for the medical staff in the intuitive and individualized risk assessment in clinical practice. ## References 1. Buford T.W.. Hypertension and aging. Ageing Res. Rev. (2016) 26 96-111. DOI: 10.1016/j.arr.2016.01.007 2. Petrie J.R., Guzik T.J., Touyz R.M.. Diabetes, Hypertension, and Cardiovascular Disease: Clinical Insights and Vascular Mechanisms. Can. J. Cardiol. (2018) 34 575-584. DOI: 10.1016/j.cjca.2017.12.005 3. 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--- title: Global and Partial Effect Assessment in Metabolic Syndrome Explored by Metabolomics authors: - Marion Brandolini-Bunlon - Benoit Jaillais - Véronique Cariou - Blandine Comte - Estelle Pujos-Guillot - Evelyne Vigneau journal: Metabolites year: 2023 pmcid: PMC10058487 doi: 10.3390/metabo13030373 license: CC BY 4.0 --- # Global and Partial Effect Assessment in Metabolic Syndrome Explored by Metabolomics ## Abstract In nutrition and health research, untargeted metabolomics is actually analyzed simultaneously with clinical data to improve prediction and better understand pathological status. This can be modeled using a multiblock supervised model with several input data blocks (metabolomics, clinical data) being potential predictors of the outcome to be explained. Alternatively, this configuration can be represented with a path diagram where the input blocks are each connected by links directed to the outcome—as in multiblock supervised modeling—and are also related to each other, thus allowing one to account for block effects. On the basis of a path model, we show herein how to estimate the effect of an input block, either on its own or conditionally to other(s), on the output response, respectively called “global” and “partial” effects, by percentages of explained variance in dedicated PLS regression models. These effects have been computed in two different path diagrams in a case study relative to metabolic syndrome, involving metabolomics and clinical data from an older men′s cohort (NuAge). From the two effects associated with each path, the results highlighted the complementary information provided by metabolomics to clinical data and, reciprocally, in the metabolic syndrome exploration. ## 1. Introduction In precision medicine, the ultimate goal is to decipher disease phenotypes in order to improve diagnosis and treatment. Advances in deep phenotyping approaches, in particular using -omics technologies, allowed the emergence of systems biology as an integrated perspective to achieve more precise modeling of complex diseases [1]. Clinical syndromes are defined as a group of signs and symptoms that occur together and characterize a particular biological abnormality (https://disease-ontology.org/, accessed on 31 January 2023). From a numerical point of view, they are defined by a cluster of quantitative clinical variables with specific cut-offs defining the binary outcome. Untargeted metabolomics is now routinely used as a powerful tool to get an integrated view of biological systems, better understand complex phenotypes, discover biomarkers and validate patterns that are characteristic of particular biological states in various populations. However, it generates high-dimensional data that need dedicated treatment to extract biological knowledge. The common strategy for processing such data consists in performing univariate and multivariate statistics to reveal variables of interest that will be further used for biological interpretation [2]. Moreover, in health-related case-control studies, untargeted metabolomics is often integrated with standard clinical information in order to better predict and understand clinical syndromes or diseases of interest. However, extracting correlations as meaningful biological interactions is not trivial, and deciphering the modulation of metabolites from clinical factors is of major importance to achieve more precise modeling of clinical syndromes [3]. From a data analysis point of view, this leads to setting up a supervised model with two blocks of input data (metabolomics, clinical characteristics) being potential predictors of the targeted output to be explained. Such a configuration can be represented with a path diagram where directional links connect each input block to the output. In health-related studies, metabolomics reflects the clinical state to a certain extent suggesting that the input blocks are also interrelated. In this a priori-drawn path diagram, we were interested in evaluating the effect of an input block, either on its own (global effect) or conditionally to another (partial effect), on the output response. In the classical path analysis approach that could be used for such multiblock modeling, the data blocks must be unidimensional, and ‘direct’, ‘indirect’ and ‘total’ effects are estimated on the basis of standardized coefficients (path coefficients) in linear regression models [4,5]. Indeed, the regression coefficient approach is not suitable when the explanatory variables are highly colinear. Due to the multidimensionality of the metabolomic data, the use of PLS regression models is advocated to evaluate the links between the data blocks. Global and partial effects are then defined from the explained variance accounted for each model. In the present work, published data from a project on metabolic syndrome (MetS) within the NuAge longitudinal cohort on aging [6] were used as a case study [7]. In this publication by Comte et al. [ 7], data were acquired by different untargeted metabolomic methods combined in a multiplatform approach followed by a variable selection strategy to build a comprehensive molecular signature of the metabolic syndrome, including 102 metabolites. The objective of our study was to enrich our knowledge about MetS by the assessment and explanation of global and partial effects in path diagrams involving the same metabolomics and clinical input blocks and the same output response consisting of a binary variable indicating the MetS presence (case or control). Then, we sought to identify the most important variables in the global effect and study the effect of introducing the mediating block. As in this study, there were no obvious causal and/or temporal links between clinical and metabolomic perturbations, we adopted a data-driven approach, and two pathway diagrams were therefore studied, differing in the mediating block, which was either the metabolomics or the clinical data. ## 2.1.1. Available Data Published data from a project on MetS within the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge) [6]; (https://nuage.recherche.usherbrooke.ca/en/, accessed on 31 January 2023) were used as a case study, including 121 male subjects [7]; 2 subjects were removed after participant’s withdrawal. A binary variable, y, indicated the subjects’ status regarding the MetS presence (case or control). A clinical data block (Clinic) included the 6 quantitative MetS diagnostic variables collected at baseline, scaled to unit variance. In the present work, only subjects with no missing values (54 cases/45 controls) were kept for analysis. A metabolomic data block (Metabo) included a comprehensive MetS signature of 102 selected variables from serum sample analyses at baseline. The data acquisition, processing, and feature selection strategy, as well as annotations of these 102 variables, are provided in Comte et al. [ 2021] [7]. In the present work, null intensities within the metabolomic dataset were replaced by $80\%$ of the minimum intensity value of the corresponding variable before a logarithm transformation. ## 2.1.2. Path Diagrams The “global” and “partial” effects of an input block on an output response were computed by considering two different path diagrams, named “path 1” and “path 2”, respectively (Figure 1). The output response, y, was a binary variable indicating the MetS presence. The two explanatory, or input, data blocks were metabolomics and clinical datasets, named Metabo and Clinic, respectively. In path 1, Clinic predicts y with Metabo as a mediating block. In path 2, Metabo predicts y with Clinic as a mediating block. ## 2.2.1. Effect Calculation In the framework of multiblock analysis, directed acyclic graphs (DAG) are convenient ways to represent the conditional dependence relations between blocks. Let us consider a graph with three vertices representing three different data blocks, denoted A, B and C (as in Figure 2a,b). Furthermore, suppose three directed arrows between these vertices indicate a direct dependence from A to C and an indirect link connecting A to C through B. With respect to the DAG depicted in Figure 2a, A refers to an independent block (that is to say, an explanatory one), C a dependent block (i.e., to be explained) and B a mediating or intermediary block as far as it depends on A and is predictive with respect to C. As illustrated in Figure 1, in path 1, A corresponds to Clinic, C to y, and B to Metabo. Similarly, in path 2, A corresponds to Metabo, C to y, and B to Clinic. The global effect of A on C corresponds to the amount of variance of C explained by A, while the partial effect of A on C, conditionally to B, is obtained by the amount of variance of C explained by A, taking into account the explanation of A and C by B. Let us denote XA, XB and XC as the data matrices associated with blocks A, B and C, respectively. Without loss of generality, we suppose that XA, XB and XC are column-wise centered. The Froebenius norm of a matrix is noted ‖.‖2. The global effect of A on C is the explained variance accounted for regressing C on A (Figure 2a and Equation [1]). In Equation [1] of the regression model, VAC are the regression coefficients and EAC the residuals. [ 1]XC=XAVAC+EAC The global effect of A on C is therefore equal to [2]‖XACVAC‖2‖XC‖2 The determination of the partial effect of A on C, given B, requires first removing the linear dependence between B and C and between B and A, respectively (Figure 2b). The residuals of C on B, noted EBC, and of A on B, noted EBA, are thus retained:[3]XC=XBVBC+EBC and XA=XBVBA+EBA The partial effect of A on C, given B, is determined as the explained variance accounted for regressing the residuals of C on the residuals of A thus obtained (Figure 2c):[4]EBC=EBAVCBA+ECBA The partial effect of A on C, given B, is therefore equal to [5]‖EBAVCBA‖2‖EBC‖2 Finally, a repeated k-fold cross-validation procedure is performed to take into account sampling variability when estimating these effects. The “global” effect corresponds, therefore, to the average of the cross-validated percentages of explained variance of the output block by the input block. Similarly, the “partial” effect is estimated by averaging the cross-validated percentages of explained variance resulting from a regression between the residuals blocks. ## 2.2.2. Determination of the Models by Means of PLS Regression In a multidimensional framework, with data blocks gathering a large number of highly correlated variables, a PLS regression is carried out for each predictive model to prevent collinearity issues. Thus, the amount of global and partial explained variances are estimated from usual PLS regression models: PLS1 when only one variable is to be predicted, PLS2 otherwise. As far as the complexity of the model depends on the number of components, the optimal number of components to be retained in the different PLS models is tuned by repeated k-fold cross-validation associated with a stratified resampling and the application of the one standard error rule [8]. Such a rule leads to a good compromise between the parsimony and the quality of a model as it corresponds to the most parsimonious model having a cross-validated residual sum of squares lower than the smallest cross-validated sum of squares value plus one standard deviation. Once the optimal model has been determined, the variable importance in the projection (VIP) values are evaluated in both cases, i.e., for models associated with global and partial effect assessments. Bootstrap mean and standard deviation of VIP indices were also computed. The threshold value of mean bootstrap VIP, to determine that a variable is important, was set independently for each path and each model based on the mean bootstrap VIP value diagrams. Finally, log2 fold-changes (Log2 FC) were calculated for each explanatory variable (on data neither mean-centered nor scaled to unit variance) to complete the model interpretation. ## 2.2.3. Software and Implementation Data analysis was performed under the R software (version 4.2.0, R Development Core Team, 2019), using ‘caret’ (createFolds() function) and ‘pls’ (plsr() function) R-packages. Both metabolomics and clinical variables were scaled to unit variance. The choice of the optimal numbers of components and the calculation of cross-validated explained variance was performed with 10-fold cross-validation repeated 50 times, with a resampling frame stratified on the y variable. Bootstrap mean and standard deviation of VIP indices were computed with 500 repetitions. ## 3.1. Global and Partial Effect Estimations and Selected Variables by Means of VIP Indices The explained variances and the number of components of each model are indicated in Table 1. For both paths, global and partial effect estimations were found to be similar. Moreover, the amount of explained variance associated with the partial effect showed greater variability than the global effect. Concerning the global effect estimated for path 1, around $52\%$ of the variance of y was explained by the Clinic block. Three clinical variables that are directly related to carbohydrate and lipid metabolism disturbances, in link with insulin resistance, namely “waist circumference”, “glycemia” and “triglyceridemia”, had variable importance in the projection (VIP) value higher than the threshold that was set to 1. Their observed and mean bootstrap VIP values and Log2 FC are provided in Table 2. These statistics for this global effect for all variables are provided in Supplementary Materials (Table S1). For the partial effect estimated for path 1, after removing the amount of variance explained by the Metabo block, $23\%$ of the variance of the y residuals was explained by the Clinic residuals. The two clinical variable residuals having important VIP values higher than 1 in this model, namely “waist circumference” and “systolic blood pressure”, are presented in Table 2. We observe that “waist circumference” was important both in the global effect and in the partial effect. All the observed and mean bootstrap VIP values for this partial effect are provided in Supplementary Materials (Table S1). In path 2, the global effect of the Metabo block on y represented around $53\%$ of the explained variance of y. The metabolites that were important in this global effect were found to be directly related to carbohydrate and lipid metabolism disturbances in link with insulin resistance. Nineteen annotated metabolomics variables had a significant mean bootstrap VIP value higher than the threshold that was set to 1.2 for this model (Table 3). These metabolites were previously identified as lipids (triglycerides, phosphatidylcholines, LDL, VLDL…), carbohydrates (hexoses, glucose), as well as amino acids (leucine, valine, glutamine) and derivatives [7]. All the Log2 FC (cases vs. controls) and all the observed and mean bootstrap metabolomics variable importance values in the projection in this global effect are provided in Table S2 in Supplementary Materials. The partial effect estimated in path 2 of the Metabo block on y, i.e., after removing what was explained by the Clinic block, showed that around $22\%$ of the variance of the y residuals was explained by the Metabo residuals. Sixteen residuals of metabolomics variables had a significant mean bootstrap VIP value higher than the threshold set to 1.2. Among them, the four previously identified are listed in Table 3. They were metabolites with endogenous and dietary origins (see Section 4) having different effects related to MetS, but not immediately linked to clinical parameters. Moreover, all the observed and mean bootstrap VIP values in this partial effect are indicated in Supplementary Materials (Table S2). ## 3.2. Comparison of Important Variables in the Global and Partial Effects It is interesting to note that the most important variables in the global effect and those that become important in the partial effect were not the same in both paths, except the waist circumference that remained important in path 1 and PC(18:0_20:3), which is an alkylacyl phosphatidylcholine that remained important in path 2. In addition, the VIP indices of the variables in the partial effects had relatively high variability, which has already been noticed for the explained variance. ## 4.1. Interest of Path Modeling Approaches To the best of our knowledge, path modeling approaches have been applied with metabolomics to explain health-related outputs only in a few publications [9,10,11]. But no publications have already applied multiblock path modeling approaches with metabolomics for a clinical syndrome exploration. However, the path modeling or mediation approaches are of major interest compared to supervised multiblock methods, such as multiblock PLS regression, which search for components of the different data blocks providing the same or complementary information with respect to a block to be predicted without taking into account the links between the explanatory blocks. Within the multidimensional framework of multiblock analysis, a path diagram is a convenient way to represent the conditional dependence relations between several blocks. Modeling these relationships may be achieved using components-based SEM (Structural Equation Modeling) methods such as PLS-PM [12], RGCCA [13] and GSCA [14]. More specifically, the approach we applied here, whose objective was to better understand a health-related predictive model, was inspired by an approach recently proposed under the name SO-PLS-PM, for Sequential and Orthogonalized Path Modeling PLS [15,16]. It is interesting to note that, in the particular case where the data blocks are restricted to a single variable, the path modeling approach refers to path analysis, on the basis of which so-called direct, indirect and total effects are defined [4,5]. ## 4.2. Concepts of Global and Partial Effects In order to clarify the difference between the concepts of direct, indirect and total effects from the global and partial effects used in this work, let us consider a unidimensional setting, where blocks A, B and C, shown in Figure 1, are restricted to single variables assumed to be standardized, denoted xA, xB and xC for clarity. The direct, indirect and total effects are assessed by combining the standardized regression coefficients (or path coefficients) of the multiple linear regression of xC as a function of xA and xB, denoted pxC,xA and pxC,xB respectively, as well as the standardized regression coefficients of simple linear regression of xB as a function of xA, which is nothing else than the linear correlation coefficient between xA and xB, rxA,xB. The direct effect corresponds to pxC,xA, the indirect effect is obtained by the multiplication of pxC,xB and rxA,xB, and the total effect is the sum of the direct and the indirect effects. It is equivalent to rxA,xC, the linear correlation coefficient between xA and xC [4,5]. Direct and indirect effects determined by means of the path coefficients are very popular because of specifically addressing causal analysis. Nevertheless, in a multidimensional framework, the path coefficients between A, B and C data matrices are no longer defined globally but have to be determined for each pair of individual variables involved in the three blocks, as in [9,17]. Our point of view was to consider instead, on the one hand, the linear correlation coefficient between xA and xC, rxA,xC, which is the above defined total effect, and, on the other hand, the partial correlation coefficient between xA and xC conditionally of xB, rxA,xC/xB. The squared correlation and the squared partial correlation correspond to the explained variance accounted for the regression models between xA and xC, on the one hand, and between xA and xC given xB, on the other hand. They have been defined as the global effect (Equation [2]) and the partial effect (Equation [5]), respectively. In contrast to the use of direct and indirect effects, the evaluation of the explained variance, and hence the quantification of global and partial effects, are generalizable to the multidimensional case. In our study, we could neither proceed to a selection of variables nor subdivide the explanatory blocks to make them unidimensional, notably because of the large amount of information in the metabolomic block and the risk of obtaining unidimensional blocks that would be uninterpretable. Therefore, to determine the global effect of A on C as well as its partial effect, we recommend using the explained variance of the corresponding regression models. It is worth noting that such an approach is the one proposed by Naes et al. within the framework of SO-PLS-PM [15,16], in which the way the indirect effect is determined is completely different from the classical approach adopted in path analysis. Consequently, we do not refer here to the direct and indirect effect terms, which may be confused with the terms used in the path analysis. It is interesting to note that in our method, there is no weighting of the blocks. It could, therefore, be applied with limited risk of not highlighting important variables when explanatory data blocks are very different in terms of dimensions, information content with respect to a variable to be predicted, transformation or scaling. ## 4.3. Input for the Exploration of Metabolic Syndrome The presented approach can significantly contribute to helping to interpret the links between clinical and metabolomics data, in particular for the exploration of clinical syndromes. Indeed, in such approaches, the strength of each link between the different datasets, considering the others, can be determined simultaneously. Additionally, as in multiblock analyses, the most important variables in these links can be used to highlight corresponding biological effects. From a biological point of view, the present results highlighted the complementary information provided by metabolomics to clinical data and, reciprocally, in the MetS exploration. In particular, as expected, results showed that metabolomics is the measurement of metabolic phenotypes but also the reflection of the secondary functional deficits associated with MetS. Presently, by a global effect, metabolomics data explained, as well as the Clinic dataset, the glycemic and lipid disturbances observed at the blood level in the case of MetS. When the partial effect is analyzed, i.e., when the information explained by the Clinic was removed from the metabolomics, metabolites further linked to dysfunctions were highlighted. These metabolites allowed a more systemic and comprehensive view of the processes involved in the syndrome. It is first illustrated in path 1, where the most important clinical variables in the projection related to the global effects are measurements of blood biochemical parameters, whereas residuals of those important in the partial effect are, secondly, measures of adiposity and vascular dysfunction, respectively. Interestingly, waist circumference is important in both effects, as it could also be linked to the disturbance of the insulin action associated with the accumulation of abdominal fat. Indeed, over the last decades, adipose tissue has emerged not only as a key actor in multiple processes such as metabolism and adipogenesis but also as a very important endocrine organ, being able to secrete hormones and inflammation regulators [18]. Therefore, our results raise the question of waist circumference as a clinical measurement reflecting not only the absolute amount of intra-abdominal or visceral fat but also of subcutaneous adipose tissue, both having different and complex functions, which need to be further investigated within the emerging field of adipocyte biology. Secondly, the importance of the residuals of some metabolomics variables (not explained by the clinical variables) in path 2 brought some statistical evidence of the independence of complex effects that support distinct physiological processes leading to MetS. In detail, PC(18:0_20:3) is an alkylacyl phosphatidylcholine both linked to lipid and cholesterol transports. It was associated with waist circumference, body mass index, C-peptide and leptin [19], but also with high blood pressure and dyslipidemia, which could explain its importance in both effects [20]. Secondly, 1,5-anhydroglucitol, recognized as a short-term marker of glycemic control, was recently identified as a circulating biomarker of the functional ß-cell mass of the islets of Langerhans, which produce insulin. In fact, a close association between 1,5-anhydroglucitol levels and poor glucose control was evidenced in type 2 diabetic patients, although not in nondiabetic subjects. It was shown that the loss of ß-cells was necessary and sufficient to decrease circulating 1,5-anhydroglucitol, not requiring hyperglycemia. It is, therefore, partially not immediately linked to glycemic disturbance [21,22,23,24]. Regarding betaine, this metabolite has both endogenous and exogenous origins, as it is a nutrient obtained from the diet (e.g., some green veggies, whole grains, and shellfish), but also synthesized de novo in the kidney and liver by choline oxidation [25,26]. It is an important osmoprotectant and methyl group donor with anti-inflammatory effects [27]. It has been shown that betaine was also inversely associated with serum non-HDL cholesterol, triglycerides, BMI, percent body fat, waist circumference, and systolic and diastolic blood pressure and positively associated with HDL cholesterol [28]. In the original publication [7], correlation analyses were used to explore the relationships between the molecular signature and clinical parameters. Their results highlighted the links between almost all significantly modulated metabolites and the five individual clinical criteria defining MetS, without that much specificity (i.e., a metabolite chemical family being related to several MetS criteria), revealing the interconnection of complex underlying metabolic processes and MetS components. The present approach allowed going further into the exploration of the relationships between MetS, its clinical criteria and its metabolic signature. Interestingly, the assessment of global and partial statistical effects reflecting orthogonal statistical links revealed corresponding physiopathological independent processes, which can be measured within single metabolomic variables. ## 5. Conclusions In our study, a path-modeling method was implemented in a multidimensional context. This method can be easily applied with correlated variables and different blocks in terms of dimensions, transformations and normalizations. The interpretation of the results, based on the explained variances and VIP values, is also straightforward. The determination of both global and partial effects, together with the identification of the most important variables from the associated models, highlighted the redundancy as well as the complementarity of the clinical and metabolomic information in the MetS explanation. In particular, the disturbances in lipid and carbohydrate metabolism, which exist in metabolic syndrome and are measurable at the plasma level, were highlighted by the important clinical or metabolomic variables in the global effects. Thus, these variables were often no longer important in the partial effect. In particular, in the partial effect of Clinic on y, given the presence of Metabo in the diagram, the residuals of functional variables became important. And in the partial effect of Metabo on y, given the presence of Clinic in the model, metabolic variables not explained by MetS clinical diagnostic variables were highlighted. The present developed approach is of major interest in deciphering the relationships between metabolomic data and clinical measurements, allowing us to go deeper into the interpretation of metabolomic data in the exploration of metabolic phenotypes of clinical syndromes. ## References 1. Haendel M.A., Chute C.G., Robinson P.N.. 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--- title: Co-Expression Network Analysis Identifies Molecular Determinants of Loneliness Associated with Neuropsychiatric and Neurodegenerative Diseases authors: - Jose A. Santiago - James P. Quinn - Judith A. Potashkin journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10058494 doi: 10.3390/ijms24065909 license: CC BY 4.0 --- # Co-Expression Network Analysis Identifies Molecular Determinants of Loneliness Associated with Neuropsychiatric and Neurodegenerative Diseases ## Abstract Loneliness and social isolation are detrimental to mental health and may lead to cognitive impairment and neurodegeneration. Although several molecular signatures of loneliness have been identified, the molecular mechanisms by which loneliness impacts the brain remain elusive. Here, we performed a bioinformatics approach to untangle the molecular underpinnings associated with loneliness. Co-expression network analysis identified molecular ‘switches’ responsible for dramatic transcriptional changes in the nucleus accumbens of individuals with known loneliness. Loneliness-related switch genes were enriched in cell cycle, cancer, TGF-β, FOXO, and PI3K-AKT signaling pathways. Analysis stratified by sex identified switch genes in males with chronic loneliness. Male-specific switch genes were enriched in infection, innate immunity, and cancer-related pathways. Correlation analysis revealed that loneliness-related switch genes significantly overlapped with $82\%$ and $68\%$ of human studies on Alzheimer’s (AD) and Parkinson’s diseases (PD), respectively, in gene expression databases. Loneliness-related switch genes, BCAM, NECTIN2, NPAS3, RBM38, PELI1, DPP10, and ASGR2, have been identified as genetic risk factors for AD. Likewise, switch genes HLA-DRB5, ALDOA, and GPNMB are known genetic loci in PD. Similarly, loneliness-related switch genes overlapped in $70\%$ and $64\%$ of human studies on major depressive disorder and schizophrenia, respectively. Nine switch genes, HLA-DRB5, ARHGAP15, COL4A1, RBM38, DMD, LGALS3BP, WSCD2, CYTH4, and CNTRL, overlapped with known genetic variants in depression. Seven switch genes, NPAS3, ARHGAP15, LGALS3BP, DPP10, SMYD3, CPXCR1, and HLA-DRB5 were associated with known risk factors for schizophrenia. Collectively, we identified molecular determinants of loneliness and dysregulated pathways in the brain of non-demented adults. The association of switch genes with known risk factors for neuropsychiatric and neurodegenerative diseases provides a molecular explanation for the observed prevalence of these diseases among lonely individuals. ## 1. Introduction Physical distancing and social isolation measures implemented during the COVID-19 pandemic had detrimental consequences on the physical and mental health of individuals of all ages. Lack of social interactions and support can directly impact someone’s ability to cope successfully with stressful events and adapt to changes during difficult times. Loneliness, defined as the subjective perception of social isolation, is associated with a decline in physical and mental health [1]. Loneliness has been associated with numerous conditions, including major depressive disorder, anxiety, suicidal ideation, cognitive impairment, and dementia [2,3]. With the emerging increase in disease outbreaks and consequent social lockdowns, it is imperative to understand the biological and molecular mechanisms associated with loneliness and social isolation. Several investigations have explored the neurobiological mechanisms underlying loneliness [4]. Loneliness is associated with altered structure and function in different brain regions, including the prefrontal cortex, insula, amygdala, hippocampus, and ventral striatum [4]. Transcriptomic studies in blood and brain regions have begun to unravel some of the biological and molecular mechanisms involved in loneliness and social isolation. For example, a blood transcriptomic analysis from subjects who experienced chronically high levels of social isolation identified the upregulation of genes involved in immune activation and downregulation of genes related to B lymphocyte function and type I interferon response [5]. The same group of investigators found that loneliness-induced gene expression in blood was derived primarily from antigen-presenting cells [6]. In contrast with blood, an analysis of genome-wide RNA expression in the nucleus accumbens from donors with known loneliness identified differentially expressed genes associated with behavioral processes, Alzheimer’s disease (AD), psychological disorders, cancer, and skeletal and muscular disorders [7]. The nucleus accumbens is a brain region of interest due to its involvement in reward processing and cooperative social behavior [8,9]. Likewise, loneliness-induced gene expression patterns in the dorsolateral prefrontal cortex were associated with AD, psychiatric diseases, immune dysfunction, and cancer [1]. One successful approach to investigating phenotypic transitions between healthy and disease states is the analysis of co-expression networks [10,11]. The two most common and reliable methods for constructing gene expression networks are Weighted Gene Correlation Network Analysis (WGCNA) and SWItchMiner (SWIM) [10,12]. While both approaches use a correlation matrix to construct a gene–gene similarity network, WGCNA considers only the positive correlation between gene pairs. In contrast, one strength of the SWIM method is the consideration of the negative correlation of the correlation distribution. The emphasis on the left tail allows the identification of genetic drivers called ‘switch genes,’ which are anticorrelated with their neighbors in the correlation network. In other words, when switch genes are induced, their interaction partners are repressed and vice versa. These advantages have been explained in detail in ref. [ 13]. One limitation of this approach is that it is based on correlations; thus, causal relationships cannot be conclusively established. Switch genes are molecular drivers responsible for drastic transcriptional changes involved in phenotypic transitions. This network method has been instrumental in the identification of switch genes in AD, vascular dementia, frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS), physical activity, and cancer [14,15,16,17,18,19,20]. Here, we implemented a bioinformatics approach including co-expression networks and comparative transcriptomic analyses to characterize the molecular pathways involved in loneliness and social isolation. We present evidence that molecular determinants of loneliness are intimately related to neurodegenerative and neuropsychiatric diseases. ## 2.1. Database Mining and Study Selection We searched the Gene Expression Omnibus (GEO), BaseSpace Correlation Engine (BSCE, Illumina, Inc, San Diego, CA, USA), and ArrayExpress databases to identify microarrays from subjects with known loneliness (See Section 4). The following arrays were retrieved on 21 July 2022: GEO = 397, ArrayExpress = 6, BSCE = 6. One array, GSE80696, which contained transcriptomic data from individuals with known loneliness, met our inclusion/exclusion criteria and was analyzed further. This dataset can be accessed using the GEO database link: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE80696, 21 July 2022. The overall bioinformatics workflow is presented in Figure 1. ## 2.2. Identification of Switch Genes Associated with Loneliness The dataset GSE80696 was imported into SWItchMiner (SWIM) to identify switch genes. The SWIM analysis was performed using the following comparisons: all subjects (high vs. low loneliness), males (high vs. low loneliness), and females (high vs. low loneliness). The SWIM algorithm was performed as previously described [10,20,21]. First, genes were included (red bars) or discarded (gray bars) using a cut-off of 2.0 or higher (Figure 2a). The gene matrix was imported into SWIM to build the loneliness gene correlation network based on the average Pearson correlation coefficient (APCC). Using the APCC, three hubs were defined; date hubs with low positive co-expression with their partners, party hubs with high positive co-expression, and fight-club hubs with negative APCC values (Figure 2b). Two parameters identified the plane, Zg (within-module degree) and Kπ (clusterphobic coefficient), which was divided into seven regions, each defining a specific node role (R1-R7). High Zg values corresponded to hub nodes within their module (local hubs), whereas low Zg values corresponded to nodes with few connections within their module (non-hubs within their communities, but they could be hubs in the network). Each node was colored according to its APCC value. Yellow nodes were party and date hubs, which were positively correlated in expression with their interaction partners. The switch genes were characterized by low Zg and high Kπ values and were connected mainly outside their module. The switch genes were the blue nodes in region R4 (Figure 2b). An expression heatmap of switch genes is presented in Figure 2c. The data were clustered according to rows and columns representing switch genes and samples, respectively. The samples depicted in red were from subjects with high loneliness. Most switch genes identified in individuals with high loneliness were downregulated (shown in blue). In contrast, those with low loneliness were upregulated (shown in yellow) (Figure 2c). Fight-club hubs differed from the date and party hubs, and switch genes were significantly different from random genes, confirming the analysis’s robustness (Figure 2d). The x-axis represented the cumulative fraction of removed nodes. In contrast, the y-axis represented the average shortest path. Each curve corresponded to the variation in the average shortest path of the correlation network as a function of removing nodes specified by the colors of each line. SWIM analysis identified 48 switch genes in the nucleus accumbens from individuals with high vs. low loneliness. The same analysis was performed by stratifying the samples by sex and level of loneliness. This analysis yielded 27 switch genes in males with increased loneliness compared to low loneliness (Supplementary Figure S1). Switch genes from males with high loneliness depicted with red bars were downregulated (shown in blue) compared to males with low loneliness (Supplementary Figure S1). An analysis of samples from females did not yield any switch genes. ## 2.3. Biological and Functional Analysis of Switch Genes Functional associations were explored using the HUGO database. Gene ontology revealed that some switch genes from individuals with high loneliness were associated with angiogenesis and hemostasis (SERPINA1, FN1, KLK3, COL4A1), innate immunity and inflammation (CD59, GPNMB, LILRA2, NECTIN2, UBE2V1), lipid metabolism (GPR3, SRD5A1, ACSL5, ACACB), and neuronal development and function (ARF1, FN1, DPP10, DMD, TH, SYT8, FOXN4). In males with high loneliness, switch genes were involved in the inflammatory response (HAMP, ZFP36, PELI1, CXCL1, HLA-DRB5, S100A8, SPN) and regulation of transcription (NPAS3, AGO2, FOS, TAF6). The list of switch genes and their gene ontology annotations is provided in Supplementary Table S2. Network analysis revealed 12 unique pathways associated with loneliness (Figure 3a,b, Supplementary Table S3). The top pathways implicated in loneliness were adherens junctions, TGF-β, FOXO, Hippo, PI3K-AKT, WNT, AGE-RAGE, acute myeloid leukemia, microRNAs in cancer, JAK-STAT, and endometrial cancer (Figure 3b). Network analysis identified 18 unique pathways associated with loneliness in males (Figure 3c,d, Supplementary Table S3). The male pathways were predominantly associated with infection, innate immunity, cancer-related pathways, and autoimmune diseases (Figure 3d). Venn diagram analysis indicated that 15 pathways were shared between both groups. The complete list of pathways is provided in Supplementary Table S3. ## 2.4. Gene–Disease Association Analysis A gene–disease association network analysis was performed in NetworkAnalyst. Switch genes obtained from lonely individuals were connected to 16 diseases, including cancer, liver cirrhosis, HIV infection, bipolar disorder, depression, schizophrenia, and mental retardation (Figure 4a, Supplementary Table S4). Male-specific switch genes were connected to six diseases, including liver cirrhosis, cocaine-related disorders, alcoholic intoxication, mammary neoplasms, and hypersensitivity (Figure 4b, Supplementary Table S4). ## 2.5. Gene–Transcription Factor Network Analysis Transcription factor analysis of loneliness-related switch genes identified 65 master regulators. The most significant transcription factors according to degree and betweenness centrality were IRF1 and TGIF2 (Supplementary Table S5). Analysis of loneliness switch genes from males identified 41 transcriptional regulators. The most significant transcription factors based on network topology measurements were KLF9 and ZFX (Supplementary Table S5). The lists of transcription factors were analyzed further using the String database (https://string-db.org/, accessed on 1 September 2022). Analysis of the list of transcription factors from individuals with chronic loneliness compared to low loneliness identified 195 biological processes. The most significant processes were associated with the negative regulation of transcription, RNA metabolic process, nucleobase-containing compound metabolic process, and cellular macromolecule biosynthetic process. Transcription factors were related to zinc finger protein domains C2H2 type. In contrast, transcription factors from males with chronic loneliness were associated with the positive regulation of nucleic-acid transcription, RNA metabolic process, cellular macromolecule biosynthetic process, and cellular metabolic process. Venn diagram analysis showed that TFs from males with chronic loneliness were enriched in 12 unique biological pathways, including positive regulation of RNA metabolism, regulation of erythrocyte differentiation, lymphocyte differentiation, response to alcohol, leukocyte activation, leukocyte differentiation, cellular response to IL-6, positive regulation of pri miRNA transcription, cellular response to IL-7, erythrocyte differentiation, cellular response to oxygen-containing compound, and response to lipopolysaccharide (Supplementary Table S5). ## 2.6. Loneliness-Related Switch Genes Associated with Neuropsychiatric and Neurodegenerative Diseases We investigated whether loneliness-related switch genes were involved in neuropsychiatric and neurodegenerative diseases. We compared the results from this study to our previous analyses of switch genes in AD, FTD, ALS, and physical activity [14,15,19]. Several loneliness-related switch genes were identified as switch genes in different neurodegenerative diseases. For instance, ACACB and DLEC1 were identified as switch genes in the entorhinal cortex of AD patients [14]. Further, ACACB and GPNMB were identified as switch genes in the frontal cortex of FTD patients [15]. We curated the literature to explore the associations between loneliness-related switch genes and brain diseases. Specifically, we used the search terms “neurodegeneration”, “dementia”, “Alzheimer’s disease”, “Parkinson’s disease”, “Frontotemporal dementia”, “Amyotrophic lateral sclerosis”, “Lewy body dementia”, “neuropsychiatric disorders”, “major depressive disorder”, and “schizophrenia” for each switch gene individually. This search identified the association of 25 switch genes with neurodegenerative and neuropsychiatric diseases. For instance, 13 switch genes, GPNMB, TH, CD59, COL4A1, ZBTB16, TSPAN15, DMD, LEF1, GPR3, UBE2V1, DPP10, NECTIN2, LGALS3BP, CDKN1A, SERPINA1, and DMP1 were linked to AD, PD, FTD, PD dementia, Creutzfeldt Jakob disease, and LBD (Table 1). Nine switch genes from the male dataset, AGO2, HLA-DRB5, ALDOA, S100A8, CTSG, CXCL1, CYTH4, PELI1, and FPR1, were associated with AD, HD, PD, LBD, and FTD. Five switch genes, HLA-DRB5, CYTH4, NPAS3, DMD, and DPP10, were related to neuropsychiatric disorders (Table 1). ## 2.7. Comparative Gene Correlation Analysis between Loneliness and Neuropsychiatric and Neurodegenerative Diseases Given the associations between loneliness and brain diseases, we performed a correlation analysis between the switch genes identified from chronically lonely subjects (GSE80696) and the most common neuropsychiatric and neurodegenerative diseases using the BSCE database. We used the search terms “Alzheimer’s disease”, “dementia”, “Parkinson’s disease”, “major depressive disorder”, “depression”, and “schizophrenia” to identify arrays. Studies were filtered only to include human studies. The correlation analysis showed that loneliness-related switch genes overlapped in $82\%$ ($\frac{53}{65}$) of human studies on AD deposited in the BSCE database (Table S6). The most significant genetic overlap was observed in studies of entorhinal and frontal cortex pyramidal neurons from early-stage AD patients. Specifically, 23 ($$p \leq 1.60$$ × 10−9) and 36 (6.10 × 10−7) switch genes overlapped in the entorhinal and frontal cortices, respectively. Furthermore, several loneliness-related switch genes were associated with variants previously identified as risk factors for AD in 30 different GWAS studies (Supplementary Table S7). For instance, variants in BCAM and NECTIN2 have been related to the risk of AD in more than 10 GWAS from diverse populations, including European, Caucasian, and Japanese (Supplementary Table S7). NPAS3, RBM38, and PELI1 were associated with the risk of AD in APOE4 [-] individuals and AD with psychosis in a European cohort. Finally, ASGR2 was associated with the response to cholinesterase inhibitors in discovery and replication cohorts of AD individuals (Supplementary Table S7). The same analysis was performed with PD studies. Loneliness-related switch genes overlapped in $68\%$ ($\frac{40}{59}$) of human studies on PD (Table S8). The most significant genetic overlap was observed in the globus pallidus internal of PD patients with 12 overlapping switch genes ($$p \leq 2.50$$ × 10−6). Several switch genes overlapped with known risk loci in PD patients. For example, variants in NPAS3, HLADRB5, ALDOA, and GPNMB have been linked to PD risk in several populations (Supplementary Table S9). In the context of neuropsychiatric diseases, loneliness switch genes overlapped in $70\%$ ($\frac{16}{23}$) of human studies on major depressive disorder (Supplementary Table S10). Nine switch genes, HLA-DRB5, ARHGAP15, COL4A1, RBM38, DMD, LGALS3BP, WSCD2, CYTH4, and CNTRL, overlapped with known genetic variants in depression (Supplementary Table S11). Similarly, switch genes overlapped in $64\%$ ($\frac{16}{25}$) of human studies in schizophrenia (Supplementary Table S12). Seven switch genes, NPAS3, ARHGAP15, LGALS3BP, DPP10, SMYD3, CPXCR1, and HLA-DRB5, were associated with known risk factors for schizophrenia (Supplementary Table S13). ## 3. Discussion We performed a bioinformatics approach to identify genes responsible for drastic transcriptional changes occurring in the brain of individuals exposed to chronic levels of loneliness. Co-expression network analysis using SWIM identified 48 switch genes in the postmortem nucleus accumbens from individuals with high loneliness compared to low loneliness. Analysis stratified by sex identified 27 switch genes in males with chronic loneliness. Network analysis of loneliness-related switch genes revealed enrichment in several unique pathways, including adherens junction, TGF-β, Hippo, FOXO, PI3K-AKT, WNT, JAK-STAT, AGE-RAGE signaling in diabetic complications, and cancers. Among these pathways, TGF-β has been implicated in the pathogenesis of neuropsychiatric mood disorders and neurodegeneration due to its central actions in regulating the stress response [69]. For example, deficient TGF-β signaling triggered neurodegeneration by promoting amyloid β accumulation and dendritic loss in a mouse model of AD [70]. Likewise, FOXO and PI3K-AKT have been implicated in neurodegeneration. FOXO1 and genes under its regulation have been implicated in the pathogenesis of PD [71]. FOXO and PI3K-AKT signaling are involved in lipid metabolism and insulin signaling and may be shared pathways between diabetes and AD [72,73,74]. Similarly, advanced glycation end products (AGE) and their receptor RAGE may contribute to or protect against AD by regulating inflammatory mechanisms [75]. Transcription factor analysis identified IRF1 and TGFI2 as the most significant regulators of loneliness switch genes. IRF1 plays a role in immunity, anti-viral mechanisms, macrophage polarization, and microglial activation [76,77,78]. Interestingly, IRF1 is regulated by BIN, the second most common risk factor for AD, and has essential roles in regulating the brain inflammatory response and microglial function [79,80]. TGFI2 is associated with neuronal apoptosis, neocortical development, neurogenesis, brain defects, and mental retardation [81,82]. In contrast, switch genes from lonely males were enriched predominantly in infection, autoimmune diseases, and antigen processing and presentation. These findings were consistent with previous work in which antigen-presenting cells in blood were identified as the primary targets and most transcriptionally sensitive immune cells to social isolation [6]. Genetic changes associated with loneliness were derived primarily from plasmacytoid dendritic cells, monocytes, and B cells. Furthermore, several immune-related switch genes, including HLA-DRB5, CXCL1, and PELI1, were exclusively identified in males exposed to chronic isolation. Network analysis of transcription factors identified KLF9 as the most significant regulator of loneliness-related switch genes in males. KLF9 has been identified as an important transcriptional regulator in the hippocampus of AD patients [14]. Furthermore, KLF9 promotes the expression of PGC1α, a critical factor in hepatic gluconeogenesis [83], mitochondrial function, and a potential therapeutic target in PD [84,85]. Biological and functional analyses revealed interesting differences in pathways regulated by transcription factors identified from males with chronic loneliness and those from all subjects. Transcription factors obtained from all subjects were enriched primarily in the negative regulation of both transcription and RNA metabolism. In contrast, transcription factors from males with chronic loneliness were involved in the positive regulation of both transcription and RNA metabolism. In this regard, disrupted RNA metabolism and processing has been recognized as a critical determinant in neurological diseases including ALS, AD, FTD, and PD [86,87,88]. Moreover, transcription factors were enriched in chromatin organization and C2H2 zinc finger protein, which are involved in chromatin closing [89]. Interestingly, transcription factors from males were uniquely enriched in pathways related to the response to alcohol, leukocyte differentiation, and the cellular response to IL-6, IL-7, and lipopolysaccharide. These findings reinforce the involvement of alcohol addiction and innate immunity in males with chronic loneliness. Together, these findings suggest that loneliness directs transcriptional changes that influence the dysregulation of pathways involved in lipid metabolism, insulin signaling, RNA metabolism, and inflammatory processes. Given the evidence from blood and brain studies, it is plausible to speculate that pathways related to innate immunity are predominantly disrupted in males exposed to chronic loneliness. We next investigated the linkage between loneliness-related switch genes and other diseases. Disease–gene network analysis revealed that chronic loneliness switch genes were associated with various cancers, liver cirrhosis, and neuropsychiatric conditions, including mental retardation, depression, bipolar disorder, and schizophrenia. Switch genes identified in males exposed to chronic loneliness were linked to cocaine addiction, mammary neoplasms, hypersensitivity, and alcoholic intoxication. These findings suggest that loneliness induces the transcription of genes associated with malignancies and neuropsychiatric conditions. Males exposed to chronic loneliness may be more prone to alcohol use, cocaine addiction, and infection. For example, depressed men reported higher rates of anger attacks, aggression, substance abuse, and risk-taking than women [90]. Moreover, male-specific transcriptional rewiring of genes involved in alcohol and cocaine addiction has been recently identified in AD patients ([91]). Loneliness has been documented to promote cognitive decline and neurodegeneration, but the specific molecular determinants underlying this association are unclear. We investigated how loneliness-related switch genes are associated with neurodegenerative and neuropsychiatric diseases. Interestingly, manual curation of the literature revealed that 25 loneliness-related switch genes had been implicated in various neurodegenerative and neuropsychiatric disorders, including AD, PD, HD, FTD, depression, and schizophrenia. Correlation analysis showed that loneliness-related switch genes overlapped with $82\%$ of human gene expression studies in AD deposited in the BSCE database. Notably, several switch genes are associated with risk variants for AD. Loneliness-related switch genes BCAM, NECTIN2, NPAS3, RBM38, PELI1, DPP10, and ASGR2 were previously identified as risk factors for AD in several populations [92,93,94,95,96,97,98,99,100]. Furthermore, loneliness switch genes significantly overlapped with $68\%$ of human gene expression studies in PD. Similar to AD, several switch genes are associated with known genetic loci in PD. Mutations in NPAS3, HLA-DRB5, ALDOA, and GPNMB have been associated with PD risk in several GWAS [101,102,103,104]. These findings suggest that loneliness induces drastic gene expression changes consistent with a neurodegeneration phenotype. Individuals exposed to chronic loneliness may be more susceptible to AD or PD, possibly through different pathways. Several studies have indicated a linkage between loneliness and neuropsychiatric diseases. A population-based study reported that higher loneliness scores were associated with higher depression symptom severity [105]. In this study, loneliness-related switch genes significantly overlapped with $70\%$ and $64\%$ of human gene expression studies in major depressive disorder and schizophrenia, respectively. Several loneliness switch genes have been reported as genetic risk factors for these diseases. For example, HLA-DRB5, ARHGAP15, COL4A1, RBM38, DMD, LGALS3BP, WSCD2, CYTH4, and CNTRL overlapped with known genetic variants in depression, reinforcing the idea that loneliness may increase disease susceptibility [106,107,108]. Likewise, NPAS3, ARHGAP15, LGALS3BP, DPP10, SMYD3, CPXCR1, and HLA-DRB5 were associated with known risk factors for schizophrenia [97,109,110,111,112]. In this regard, social isolation during the pandemic correlated with paranoid ideation [113]. A genetic variant near the switch gene CPXCR1 was associated with schizophrenia risk in Japanese males in a replication cohort [114]. Sex-specific differences in symptoms and conditions have been noted among lonely individuals. For example, loneliness was associated with major depressive disorder and anxiety, especially in men, during the COVID-19 pandemic [115]. Specifically, men reported higher rates of depressive symptoms and suicidal ideation than women during the COVID-19 pandemic [116]. Symptoms of depression in males may be different from those observed in females. In this regard, when male-type symptoms of depression are included in depression rating scales, a higher proportion of males than females met the criteria for depression [90]. Identifying loneliness-related switch genes in males but not females may suggest that loneliness may have a more drastic transcriptional impact in the brain of males, making them more susceptible to some neurodegenerative and neuropsychiatric disorders. Future longitudinal and sex-stratified studies are needed to understand how loneliness impacts the brain of males and females differently. Lifestyle changes may be useful strategies to mitigate the negative effects of loneliness in older adults. Physical activity, for example, has been shown to promote synaptic growth and reduce inflammation, thus protecting the brain against oxidative stress and neurodegeneration [19]. Other lifestyle modifications, including diet, sleep hygiene, mindfulness, and meditation, have been proposed to benefit the brain against depression, cognitive decline, and neurodegeneration [117,118,119,120]. Several limitations are noteworthy. The findings presented herein are derived from bioinformatics analyses. Further mechanistic studies are needed to confirm the functional role of these switch genes. Validation of these results in an independent human gene expression dataset will be critical to determine the reproducibility of these findings in other patient populations. The study GSE80696 contained transcriptomic data from White, non-Hispanic individuals; thus, the switch gene analysis is not representative of the overall population. Notably, lonely individuals in this cohort showed poorer cognitive function than non-lonely subjects; therefore, correlations between loneliness-related switch genes and neurodegeneration are not unexpected. Nonetheless, the findings presented herein provide evidence that loneliness, in combination with environmental and genetic factors, induces gene expression changes in the brain that may lead to the development of several neuropsychiatric and neurodegenerative diseases (Figure 5). The association of switch genes with known risk factors for neuropsychiatric and neurodegenerative diseases provides supporting molecular evidence for the observed prevalence of these diseases among lonely individuals. Future longitudinal studies on loneliness will be crucial for a better understanding of the impact of loneliness on brain health. ## 4.1. Microarray Dataset Selection We searched the GEO (https://www.ncbi.nlm.nih.gov/gds, accessed on 21 July 2022), BSCE, and ArrayExpress databases in August 2022 for transcriptomic studies using the search terms “homo sapiens”, “human”, “loneliness”, and “social isolation.” The inclusion criteria were: [1] human microarrays from relevant tissues in loneliness or social isolation, [2] 3 samples or more. The exclusion criteria were: [1] animal and cellular models. One dataset met our criteria and was processed for SWIM and pathway analyses. The dataset GSE80696 included postmortem transcriptomic data from the nucleus accumbens from 26 White, non-Hispanic subjects without known dementia and depression at enrollment in the Rush Memory and Aging Project (MAP) [7]. These participants were selected from a cohort of 247 MAP participants with reported loneliness scores. The clinical characteristics of the study participants in GSE80696 are described in detail elsewhere [7] and in Supplementary Table S1. ## 4.2. Identification of Switch Genes Raw data from GSE80696 were imported into SWIM to identify switch genes. The SWIM algorithm has been described in detail in ref. [ 10,20,21]. We performed the following comparisons: all individuals with high vs. low loneliness, and samples stratified by sex, males and females with high vs. low loneliness. Genes with no or low expression were removed in the preprocessing stage. SWIM analysis works best with a network size between 1000–2000 nodes. The fold change parameter was adjusted to optimize the network size. For comparing all subjects with high vs. low loneliness, a fold change threshold of 2.0 was used. For the sex-stratified analysis, a fold change threshold of 4 was used. These fold changes were set for each array in the filtering step, and genes that were not significantly expressed between cases compared to controls were removed. The False Discovery Rate method (FDR) was used for multiple test corrections. Pearson’s correlation test was performed to build a co-expression network of genes differentially expressed between individuals with high vs. low loneliness. The k-means algorithm was used to identify communities within the network. SWIM uses a Scree plot to determine the number of clusters, and the clusters with the lowest number of sums of the square error (SSE) values among the replicates are designated as the number of clusters. We built a heat cartography map using the clusterphobic coefficient Kπ and the global-within module degree Zg. The coefficient Kπ measures the external and internal node connections, whereas Zg measures the extent to which each node is connected to others in its community. A node was considered a hub when Zg > 5. The average Pearson’s correlation coefficient (APCC) between the expression profile of each node and its nearest neighbors was used to build the heat cartography map. Three hubs were defined; date hubs that showed low positive co-expression with their partners (low APCC), party hubs that showed high positive co-expression (high APCC), and nodes that had negative APCC values were called fight-club hubs. Switch genes interact outside their community, are not in local hubs, and are mainly anticorrelated with their interaction partners. ## 4.3. Functional Analysis of Switch Genes Gene ontology associations were explored for each switch gene using the HUGO database (https://www.genenames.org/, accessed on 1 September 2022). For pathway analysis, official gene symbols were imported into NetworkAnalyst (https://www.networkanalyst.ca/, accessed on 1 September 2022) [121]. Tissue-specific networks were built using the nucleus accumbens protein-protein interaction database in NetworkAnalyst. The minimum connected network was selected for further pathway analysis. Data derived from KEGG were used for pathway selection. A gene–disease association network analysis was performed in NetworkAnalyst. Nodes were ranked according to network topology measures, degree, and betweenness centrality. A p-value and FDR of less than 0.05 were considered significant. ## 4.4. Transcription Factor Analysis Transcription factor analysis was performed in NetworkAnalyst. The lists of switch genes obtained from subjects exposed to chronic loneliness and those obtained from males with high loneliness were analyzed separately. Transcription factor data were derived from the Encyclopedia of DNA Elements (ENCODE). ENCODE uses the BETA Minus Algorithm in which only peak intensity signal <500 and the predicted regulatory potential score <1 are used. Transcription factors were ranked according to network topology measurements, including degree and betweenness centrality. Biological and functional analysis of transcription factors was performed using the String database (https://string-db.org/, accessed on 1 September 2022). Pathways with FDR < 0.05 were denoted as significant. ## 4.5. Gene Expression and Correlation Analyses Gene correlation analysis was performed using the curated BSCE database. The switch genes identified in subjects with chronic loneliness were compared to gene expression profiles from subjects with neuropsychiatric and neurodegenerative diseases using the correlation tool. The genetic overlap between GSE80696 and the other datasets was analyzed as previously described [19,74]. For the correlation analysis, the number of shared genes was compared between any two datasets. BSCE uses a “Running Fisher” algorithm to compute the overlapping p-values between different gene expression datasets [122]. Genes below the 20th percentile of the combined normalized signal intensities were removed. 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--- title: 'Late-Onset Psoriatic Arthritis: Are There Any Distinct Characteristics? A Retrospective Cohort Data Analysis' authors: - Chrysoula G. Gialouri - Gerasimos Evangelatos - Alexios Iliopoulos - Maria G. Tektonidou - Petros P. Sfikakis - George E. Fragoulis - Elena Nikiphorou journal: Life year: 2023 pmcid: PMC10058512 doi: 10.3390/life13030792 license: CC BY 4.0 --- # Late-Onset Psoriatic Arthritis: Are There Any Distinct Characteristics? A Retrospective Cohort Data Analysis ## Abstract As life expectancy increases, psoriatic arthritis (PsA) in older individuals becomes more prevalent. We explored whether late-onset versus earlier-onset PsA patients display different clinical features at diagnosis and/or during the disease course, as well as different treatment approaches and comorbidity profiles. We retrospectively collected data from consecutive PsA patients attending two rheumatology centers (December 2017–December 2022). Late-onset PsA patients (diagnosis-age: ≥60 years) were compared to those diagnosed before 60 years old. Univariate analyses and logistic regression were performed to examine for factors associated with late-onset PsA. For sensitivity analyses, the cohort’s mean diagnosis age was used as the cut-off value. Overall, 281 PsA patients were included (mean ± SD diagnosis-age: 46.0 ± 13.3 years). Of them, $14.2\%$ ($$n = 40$$) had late-onset PsA. At diagnosis, after controlling for confounders, no demographic and clinical differences were identified. During the disease course, the late-onset group exhibited $65\%$ fewer odds of manifesting enthesitis (adjusted Odds-ratio—adOR 0.35; $95\%$ confidence interval 0.13–0.97), but higher frequency of dyslipidemia (adOR 3.01; 1.30–6.95) and of major adverse cardiovascular events (adOR 4.30; 1.42–12.98) compared to earlier-onset PsA group. No differences were found in the treatment approaches. In sensitivity analyses, PsA patients diagnosed after 46 (vs. ≤46) years old had an increased frequency of hypertension (adOR 3.18; 1.70–5.94) and dyslipidemia (adOR 2.17; 1.25–3.74). The present study underpins that late-onset PsA is not uncommon, while the age at PsA onset may affect the longitudinal clinical expression of the disease. Patients with late-onset PsA were less likely to manifest enthesitis but displayed increased cardiovascular risk. ## 1. Introduction Psoriatic arthritis (PsA) is a chronic, inflammatory arthritis which is classified under the umbrella of spondyloarthritides (SpA). PsA is a highly heterogeneous disease, presenting with a variety of clinical manifestations. Apart from the skin, the peripheral joints and/or the spine, the entheses and other extra-musculoskeletal organs such as the eyes and bowel are commonly involved in PsA. In addition, patients with PsA exhibit higher cardiovascular morbidity and mortality compared to the general population. The pathogenesis of cardiovascular disease in PsA seems to be multifactorial, depending on several interrelated variables. These include traditional cardiovascular risk factors, both modifiable (e.g., hypertension, dyslipidemia, diabetes mellitus, and obesity, which are common comorbidities in PsA) and non-modifiable (e.g., gender, age, and genetic predisposition), as well as the effects of chronic underlying inflammation [1,2]. Furthermore, mental-health disorders (e.g., depression and anxiety) are often encountered in patients living with PsA and impose a significant burden over the disease course [3,4]. Considering all the above, many investigators have adopted the term “psoriatic disease” to reflect on the complexity of this clinical entity. The prevalence of PsA varies by geographic region between 0.1–$1\%$ in the general population and 10–$30\%$ in patients with psoriasis [5,6], with a median time interval between the two diagnoses of about one decade [7]. Notably, PsA typically develops in patients with a preceding diagnosis of psoriasis, whereas the onset of arthritis occurs before the diagnosis of psoriasis only in about $15\%$ of PsA cases [8]. The distribution of PsA is almost equal in males and females [9], while the incidence of PsA rises with aging, reaching a peak just before the age of 60 years and thereafter sharply declines [10]. Given the advancing aging of the population, the diagnosis of PsA in older individuals is becoming more prevalent in daily clinical practice [11,12]. In parallel, the management of PsA in this subgroup seems to be more complicated by the multimorbidity and the polypharmacy burden that comes along with this, in addition to the altered pharmacokinetics and/or pharmacodynamics [13,14,15]. Of note, it has been suggested that in psoriasis and in PsA, comorbidities might accumulate earlier than expected, introducing so-called “premature” aging [16,17,18]. Furthermore, the increased age-related risk of adverse events may influence therapeutic decisions, explaining the observed hesitancy for prescription of biologic agents in older PsA patients [19,20,21], although the available data from studies on patients with psoriasis or rheumatoid arthritis do not support any effect of the age on treatment efficacy [22,23]. In the context of psoriasis, the age of disease onset represents a well-defined covariate used to classify patients into two subpopulations, with distinct clinical and immunogenic patterns [24]. Accordingly, in PsA, there are limited data supporting that higher age of disease onset is associated with different genetic, histopathological, laboratory, and clinical traits, as well as with worse disease outcomes (e.g., more bone erosions) [16,25,26]. In addition, some investigators have estimated, through retrospective and cross-sectional studies with small sample sizes, that within the PsA populations there are differences in the prevalence of cardiovascular risk factors (e.g., of hypertension), reporting higher rates in patients with late-onset PsA than those with earlier disease onset [19,27]. In this retrospective cohort, we aimed to explore whether patients with late-onset PsA differ from those with earlier disease-onset, displaying distinct features at the time of PsA diagnosis and/or during the disease course, as well as different comorbidity profiles and treatment approaches. ## 2.1. Participants and Data Collection Data were retrospectively collected from medical charts of consecutive patients with PsA diagnosis who attended the outpatient rheumatology clinic of two tertiary hospitals (“Laiko” general hospital, Athens and 417 “NIMTS” Army Shared Fund Hospital, Athens), from December 2017 up to December 2022. All patients included in this study fulfilled the CASPAR classification criteria [28]. Patients who had at least one follow-up visit were included; no other exclusion criteria were applied for this study. The following data were recorded. [ 1] Demographic characteristics: gender, age at PsA diagnosis, body mass index (BMI), status (positive/negative) for HLA-B27, family history (i.e., first- and second-degree relatives) of psoriasis or SpA, and disease duration (time-interval between diagnosis and last follow-up visit). [ 2] PsA-related clinical characteristics present at the time of diagnosis and/or during the disease course (i.e., up to the last follow-up visit): axial disease (sacroiliitis and/or involvement of the cervical, thoracic, or lumbar spine; radiologically confirmed by X-ray or magnetic resonance imaging; and relevant clinical symptomatology), peripheral arthritis, the 68 tender joint count (TJC) and the 66 swollen joint count (SJC), the presence of active skin psoriasis, nail psoriasis, enthesitis, dactylitis, uveitis (confirmed by ophthalmologist), and inflammatory bowel disease (confirmed by colonoscopy). [ 3] Ever-present comorbidities (i.e., up to the last follow-up visit): hypertension (defined as systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg in two measurements and/or prescription of antihypertensive medication), dyslipidemia (defined as total cholesterol >200 mg/dL and/or triglycerides >150 mg/dL and/or prescription of lipid-lowering therapy), diabetes mellitus (defined as fasting blood sugar ≥126 mg/dL and/or prescription of anti-diabetic medication), obesity (BMI ≥30 kg/m2), major adverse cardiovascular events (MACE, defined as a history of myocardial infarction, angina, and/or stroke), and depression (as indicated by the use of antidepressants prescribed by a psychiatrist). [ 4] PsA-related treatment history, recorded as the ever use of steroids (yes/no) and the total number of conventional-synthetic (cs) and biological (b) disease modifying antirheumatic drugs (DMARD) received from the time of PsA diagnosis. Of note, apremilast was included (for this study) in the latter group. Furthermore, in this cohort, no JAK inhibitors had been prescribed up to the last recorded visit. ## 2.2. Study Design and Statistical Analyses For the main analyses, patients were categorized into two groups: those with late-onset PsA (i.e., age at diagnosis: ≥60 years) and those with earlier-onset PsA (i.e., patients diagnosed before the age of 60 years) as in previous PsA studies [26]. In addition, sensitivity analyses were performed, using the mean age at diagnosis of the overall cohort (Supplementary Figure S1) to dichotomize our sample. Patients with an age at PsA diagnosis of >46 years were compared to patients who were diagnosed at an age of ≤46 years. Continuous variables are presented as mean ± standard deviation (SD) or median (interquartile range, IQR) if distributed normally or not, respectively, and categorical variables as absolute frequency (n) and percentage (%). Comparisons between the two PsA groups were made using the Student’s t-test or Mann–Whitney U test for the continuous variables (if distributed normally or not, respectively), and the chi-square test for the categorical variables. For both main and sensitivity analyses, simple and multiple logistic regression were conducted to investigate for factors associated with late-onset PsA (dependent variable). The multivariable model was constructed including the gender, the disease duration and the variables which displayed significant differences in the univariable analyses. Firstly, a backward stepwise selection model was applied so as to find a reduced model which could best explain the data. Thereafter, we reran the multiple regression, including the same independent variables, using the enter method. In the case of the same results, the enter model was decided to be reported. Statistical significance was considered for p-values less than 0.05. GraphPad Prism 9 and STATA 13.0 software were used. ## 2.3. Ethical Approval This study was approved by the Institutional Review Board of “Laiko” (scientific council; number 780-21) and “NIMTS” hospital (scientific council; number 196-19). The study was conducted in accordance with the principles of the Declaration of Helsinki for human studies. Written informed consent was obtained from all participants. ## 3. Results In total, 281 PsA patients were included, of whom most were females ($58.0\%$) with a mean ± SD age at diagnosis of 46.0 ± 13.3 years (Supplementary Figure S1). Among them, 40 ($14.2\%$) had late-onset PsA ($52.5\%$ males, mean ± SD age at diagnosis: 66.7 ± 5.3 years, Supplementary Figure S2) versus 241 ($85.8\%$) patients who had been diagnosed before the age of 60 years ($40.2\%$ males, mean ± SD age at diagnosis: 42.5 ± 10.8 years, Supplementary Figure S2). Characteristics of this cohort groups are presented in detail in Table 1. In the univariable analysis, no significant differences were identified in the comparison of gender, family history of psoriasis or spondyloarthritis, BMI, or smoking habits between the late- and earlier- onset PsA group. The disease duration was found to be shorter in the late- than the earlier-onset PsA group (median [IQR]: 21 [1.5–93.5] vs. 54 [18–142] months, $$p \leq 0.002$$). At the time of diagnosis, patients with late-onset PsA had similar clinical manifestations to those diagnosed before the age of 60 years, in terms of axial disease, peripheral arthritis (including non-significant differences in the number of tender or swollen joints), active skin psoriasis lesions, enthesitis, dactylitis, and inflammatory bowel disease. Over the disease course, patients with late-onset PsA manifested less frequently axial disease compared to those with earlier disease onset ($22.5\%$ vs. $39.0\%$, $$p \leq 0.045$$), whereas no significant differences were found for the other clinical features of PsA (Table 1). Notably, the percentage of patients who at least once exhibited enthesitis was lower in the late-onset PsA group. However, the difference was marginally non-significant ($17.5\%$ in the late-onset vs. $32.8\%$ in the earlier-onset PsA group, $$p \leq 0.052$$). Furthermore, among the recorded comorbidities, hypertension, dyslipidemia, and MACE were significantly more frequent among patients with late-onset PsA ($55\%$ vs. $31\%$, $$p \leq 0.003$$; $75\%$ vs. $48.1\%$, $$p \leq 0.002$$; $22.5\%$ vs. $5.0\%$, $p \leq 0.001$, respectively). Finally, patients with late-onset PsA were found to have received an overall lower number of bDMARDs compared to those with an earlier disease onset ($$p \leq 0.035$$). In multiple logistic regression (enter model, Table 2), having the gender, the disease duration, and the variables which displayed significant differences in univariate analyses as independent variables, patients with late- (vs. those with earlier-) PsA onset -who had a shorter disease duration- demonstrated $65\%$ fewer odds of manifesting enthesitis during the disease course (adjusted Odds Ratio—adOR 0.35; $95\%$ CI 0.13–0.97). On the other hand, patients with late-onset PsA had a 3-fold increased frequency of dyslipidemia (adOR 3.01; $95\%$ CI 1.30–6.95, $$p \leq 0.010$$) and 4.3-fold increased frequency of MACE (adOR 4.30; $95\%$ CI 1.42–12.98, $$p \leq 0.010$$) compared to patients who were diagnosed before 60 years old. ## Sensitivity Analyses When we repeated the analyses using as the cut-off value the mean age at PsA diagnosis of the overall cohort (46 years), we did not find any differences in demographic characteristics and clinical features present at the time of diagnosis. Instead, in univariate comparisons, the frequency of uveitis during the disease course was found to be lower in the group of patients diagnosed after the age of 46 years, versus those with an age at diagnosis of ≤46 years ($0.7\%$ vs. $4.5\%$, $$p \leq 0.041$$). In addition, patients diagnosed after 46 years old were found to have a significantly increased frequency of hypertension ($48.3\%$ vs. $19.4\%$, $p \leq 0.001$), dyslipidemia ($65.1\%$ vs. $37.6\%$, $p \leq 0.001$), diabetes ($24.8\%$ vs. $13.4\%$, $$p \leq 0.004$$), and MACE ($11\%$ vs. $3.7\%$, $$p \leq 0.021$$). No difference was observed in the treatment approach between these groups. Details are presented in Supplementary Table S1. However, after adjusting for confounders (i.e., gender, disease duration, and the above mentioned significantly associated factors from univariate analyses), it was found that patients who were diagnosed after 46 years old differed from those who were diagnosed at an age of ≤46 years in terms of a higher frequency of traditional cardiovascular risk factors only. In particular, the former group was about three times more likely to have hypertension (adOR 3.18; $95\%$ CI 1.70–5.94; $p \leq 0.001$) and about two times more likely to have dyslipidemia (adOR 2.17; $95\%$ CI 1.25–3.74; $$p \leq 0.005$$) (Supplementary Table S2). ## 4. Discussion In older individuals, the clinical expression of PsA as well as the burden of comorbidities may differ from those with a younger age at disease onset, given the age-related pathophysiological alterations. Moreover, at the time of SpA onset, older patients may present with a mixture of features, some of which could resemble other rheumatic diseases with increased prevalence in older ages, challenging thus sometimes the diagnosis [29]. With this retrospective study, we aimed to add more evidence pertaining to whether patients with late-onset PsA differ from those with earlier PsA onset, at the time of diagnosis and/or during the disease course. We showed that patients with late-onset PsA had similar demographic and clinical characteristics at the time of diagnosis to those patients diagnosed before 60 years old, but were significantly less likely to manifest enthesitis during the disease course. In addition, patients with late-onset PsA displayed an increased cardiovascular risk, having more frequently dyslipidemia and MACE. Importantly, even patients diagnosed at a younger age (>46 years old vs. those diagnosed ≤46 years old) displayed an independent increased frequency of cardiovascular risk factors. Previous studies on PsA patients investigating the influence of the age at the time of diagnosis on disease-related features are scarce. In addition, there is no consensus thus far on whether the age at disease onset should be analyzed as a continuous or binary variable, while in the latter case, different cut-off values have been used and so direct comparisons are not feasible [19,26,27,30,31,32]. In our main analyses, we included those patients who were diagnosed with PsA at the age of 60 years or older in the late onset group, in line with other studies conducted in the field. Besides, this is in agreement with the definition used by the United Nations for older persons [33]. In addition, recent findings from a population-based German study support that most of the new PsA cases occur between the age of 50 and 59 years, whereas the risk of developing PsA after 60 years becomes rapidly lower [10]. Notably, given that older persons are also referred to as those aged over 65 years old, we repeated the same analyses using this cut-off, but we found the same associations. In our cohort, $14.2\%$ of patients were diagnosed after the age of 60 years, which reflects the need to better characterize this PsA subgroup. In the main analyses, we found that patients with late-onset PsA had similar demographic characteristics as well similar clinical features at the time of diagnosis to those patients with earlier-onset PsA. Punzi et al. were the first to prospectively study a small ($$n = 66$$) cohort of PsA patients using the 60 years as the age threshold. In this study, the investigators suggested that patients with late-onset PsA had a more severe disease onset, with elevated inflammation markers in the serum and synovial fluid, more tender and/or swollen joints, and more bone erosions after two years of observation. On the other hand, in agreement with our findings, no differences were identified at the time of disease onset in terms of axial involvement (although the detection of sacroiliac joints involvement was made through bone scintigraphy in that study) and dactylitis presence. However, one has to note that in this study, a limited number of patients were included and only some of the clinical features of PsA were examined. Furthermore, a multivariable analysis that would correct for possible confounders was not applied [26]. In our dataset, we also estimated, after adjustment for confounders, that patients with late-onset PsA manifested less frequently enthesitis during the disease course, whereas no differences were observed in other ever-present clinical manifestations. In addition, patients with late-onset PsA showed an increased frequency of dyslipidemia and MACE compared to patients with earlier-onset PsA. On the other hand, no differences were identified in the treatment approach, as assessed in this study by the ever use of steroids and by the total number of ever received cs- or b-DMARDs. In agreement with our findings, a previous retrospective study of 180 PsA patients, with cut-off age for symptoms initiation at 65 years, showed that patients with late-onset PsA had a significantly higher rate of hypertension, diabetes mellitus, and coronary heart disease compared to those with early-onset PsA. Similarly to our findings, the analyses applied in this dataset showed that the late-onset group was also less likely to display enthesitis, but this group also manifested less frequently in dactylitis and nail psoriasis as well as in a greater skin psoriasis score. However, correction for possible confounders was not performed [19]. Furthermore, Queiro and colleagues conducted a cross-sectional study more recently that was based on a large sample of PsA patients ($$n = 227$$). This study also demonstrated (again only through univariate analyses) that patients with disease onset after the age of 65 years had a shorter disease duration and higher frequency of traditional cardiovascular risk factors (namely hypertension, dyslipidemia, and diabetes mellitus) compared to PsA groups diagnosed at a younger age. Moreover, patients with late-onset PsA were found to have a significantly lower use of bDMARDs, which is in concordance with our findings. However, in contrast to us, authors did not correct for cofounders and so the interpretation of this finding cannot be robust. Finally, in line with our results, no differences were found in the articular pattern (axial and/or peripheral), nor in the family history of psoriasis or PsA [27]. We also performed sensitivity analyses (Supplementary Tables S1 and S2), using the mean age at PsA diagnosis as the cut-off value of the overall cohort to define the late-onset group (>46 years old at diagnosis). We found that patients who were diagnosed after the age of 46 years had an independent increased cardiovascular risk, with a higher frequency of hypertension and dyslipidemia. On the other hand, these groups did not exhibit differences in the clinical expression of the disease at diagnosis a well as during the disease course, nor in the treatment options. This approach for defining the age threshold to compare early- and late-onset patients has not been used in previous PsA studies, but only in one retrospective study of patients with SpA [34]. The interpretation of the observed increased cardiovascular risk in the late-onset versus earlier-onset PsA group is complicated. One could speculate that there is an interplay between the higher age at PsA diagnosis and the cardiovascular burden. Given the underlying inflammatory nature of PsA upon its onset, PsA could promote or exacerbate the pre-existing age-related cardiovascular risk. On the other hand, it has been proposed that pro-inflammatory conditions such as adiposity, smoking, microbiome dysbiosis, immunosenescence, and “inflammageing”, as well as comorbidity-related drivers that may lead to a break in tolerance and to the corollary initiation of autoimmune inflammatory diseases later in life [12]. However, a lot of research is still required to fuel these theories. We acknowledge that the present study has some limitations. Firstly, we had missing values which mainly pertained to the clinical features of patients at the time of diagnosis, given the retrospective nature of the study. Hence, the potential differences in disease presentation are still open to be explored. In addition, data for the exact date of comorbidities diagnosis were not available. The second limitation is consistent with previous studies and, as expected, is that the late-onset group had, significantly shorter disease duration and so other potential differences in clinical features during the disease course cannot be excluded. Thirdly, it is impossible to account for any residual confounding despite the multiple variables tested in the models. Finally, data for the date of psoriasis onset and for psoriasis duration up to the onset of joint disease are not available [35]. However, when we compared the frequency of patients in which psoriasis preceded the diagnosis of PsA, we did not observe a significant difference ($65.9\%$ in patients diagnosed before 60 years old and $62.5\%$ in patients with late-onset PsA, $$p \leq 0.668$$). Our study also has important strengths. First of all, this is the largest PsA sample used to compare late- and earlier-onset disease so far. In addition, we have included data both from the time of diagnosis and from the disease course, so as to capture differences at presentation as well as in the longitudinal clinical expression of the disease. Importantly, given the lack of a uniformly accepted definition of late-onset disease in the context of PsA, we also performed sensitivity analyses testing various values as the optimal cut-off for distinguishing the sub-group of late-onset PsA. ## 5. 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--- title: CT-Derived Body Composition Is a Predictor of Survival after Esophagectomy authors: - Kartik Iyer - Cameron A. Beeche - Naciye S. Gezer - Joseph K. Leader - Shangsi Ren - Rajeev Dhupar - Jiantao Pu journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10058526 doi: 10.3390/jcm12062106 license: CC BY 4.0 --- # CT-Derived Body Composition Is a Predictor of Survival after Esophagectomy ## Abstract Background: Body composition can be accurately quantified based on computed tomography (CT) and typically reflects an individual’s overall health status. However, there is a dearth of research examining the relationship between body composition and survival following esophagectomy. Methods: We created a cohort consisting of 183 patients who underwent esophagectomy for esophageal cancer without neoadjuvant therapy. The cohort included preoperative PET-CT scans, along with pathologic and clinical data, which were collected prospectively. Radiomic, tumor, PET, and body composition features were automatically extracted from the images. Cox regression models were utilized to identify variables associated with survival. Logistic regression and machine learning models were developed to predict one-, three-, and five-year survival rates. Model performance was evaluated based on the area under the receiver operating characteristics curve (ROC/AUC). To test for the statistical significance of the impact of body composition on survival, body composition features were excluded for the best-performing models, and the DeLong test was used. Results: The one-year survival model contained 10 variables, including three body composition variables (bone mass, bone density, and visceral adipose tissue (VAT) density), and demonstrated an AUC of 0.817 ($95\%$ CI: 0.738–0.897). The three-year survival model incorporated 14 variables, including three body composition variables (intermuscular adipose tissue (IMAT) volume, IMAT mass, and bone mass), with an AUC of 0.693 ($95\%$ CI: 0.594–0.792). For the five-year survival model, 10 variables were included, of which two were body composition variables (intramuscular adipose tissue (IMAT) volume and visceral adipose tissue (VAT) mass), with an AUC of 0.861 ($95\%$ CI: 0.783–0.938). The one- and five-year survival models exhibited significantly inferior performance when body composition features were not incorporated. Conclusions: Body composition features derived from preoperative CT scans should be considered when predicting survival following esophagectomy. ## 1. Introduction Approximately $90\%$ of cancer-related mortality following esophagectomy occurs due to distant disease. The current approach to predict survival primarily relies on pathologic or clinical staging and response to neoadjuvant treatments [1]. Identifying factors associated with postoperative survival may provide valuable guidance to clinicians and patients regarding treatment and prognosis [2]. Radiographically derived variables and machine learning analyses are taking a foothold in thoracic surgery, with sophisticated image processing being used more frequently to predict clinical outcomes [3,4,5,6]. In fact, some models utilizing radiomic features have outperformed traditional clinicopathologic models [7], demonstrating the potential of these techniques for improved prediction of postoperative survival. Most models that predict long-term survival after esophagectomy rely on demographic, clinical, and pathologic variables without consideration of radiographically derived features [8,9]. However, CT scans contain an extensive amount of information related to bone, fat, and muscle, collectively known as body composition. Although body composition has been studied as a prognostic variable in other cancers [10,11], it remains relatively unexplored in esophageal cancer. There are other radiomic variables that have predictive capabilities after esophagectomy, such as sarcopenia and myosteatosis [12,13]. However, and quite importantly, most radiomic variables calculate tissue composition based on single images at a single anatomical location (i.e., from a single CT scan slice). To our knowledge, only one study has evaluated a survival model incorporating radiomic, PET, and body composition variables [14], finding sarcopenia to be an independent predictor of survival. Quantifying various body composition tissues depicted on CT scans using traditional manual approaches can be technically challenging and time-consuming. Moreover, practical consideration often necessitates compromises in the calculations, such as using a single slice with cutoffs to calculate sarcopenia, which does not account for intermediate values of body tissues in other locations. To overcome some of these challenges, we developed computer software to automatically segment three-dimensional body composition from CT images [15], allowing for extensive and accurate quantification. Compared to other methods, our software computes a larger number of variables and provides precise values for each body tissue type [16]. In this way, a more comprehensive assessment of body composition can be made compared to evaluating sarcopenia from a single image slice. In this study, we built a post-esophagectomy survival model that incorporates a comprehensive set of body composition features from pretreatment CT scans, tumor radiomic features from preoperative CT and PET-CT scans, and clinical features (including pathologic stage). The model was designed to: [1] predict post-esophagectomy survival, [2] assess the impact of body composition features on the model performance, and [3] compare the performance of our model to other models. ## 2.1. Study Population This study was approved by the University of Pittsburgh Institutional Review Board (IRB #: STUDY20100305) on 5 February 2021. Our dataset was developed from a prospectively collected database of all patients undergoing esophagectomy at the University of Pittsburgh Medical Center (UPMC) between 2008 and 2021. Inclusion criteria were patients who underwent esophagectomy for esophageal cancer, had available preoperative PET-CT and CT scans, and did not have preoperative chemotherapy or radiation. Data from 301 patients were de-identified and re-identified with a unique study ID number by an honest broker, and after removing patients with missing information, 183 patients ultimately met the inclusion criteria. Demographic (age, race, gender), clinical (stage, height, weight, smoking history), survival, and radiologic data were collected. CT scans were used to generate radiomic, tumor, and body composition features (described below). PET scans were used to generate SUV features, Total Lesion Glucose (TLG), and Metabolic Tumor Volume (MTV). Patients were followed for a mean of 31 months (0.1–132 months) post-surgery, and subjects without follow-up survival data were censored. ## 2.2. Image Acquisition CT scans were performed over 13 years using Discovery STE (GE Healthcare, Waukesha, WI, USA) or Siemens Biograph scanners. The acquisition parameters are as follows: 120 kV or 130 kV, 60 mAs to 444 mAs, reconstruction field of view 275 × 450 mm, and image thicknesses ranging from 2–5 mm. ## 2.3. Image Features Body composition: A three-dimensional (3-D) convolutional neural network (CNN) [15] was used to automatically segment five different body tissues depicted on CT scans, including visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), intramuscular adipose tissue (IMAT), skeletal muscle (SM) and bone (Supplemental Figure S1). Each body tissue was quantified with three measurements: mass, volume, and density (measured in average Hounsfield units (HU)). Mass was estimated from CT HU values, where x is the HU value and y is the density (g/cm3) of a CT voxel [17] (Equation [1]). [ 1]$y = 0.0011$×x+1.136 Tumor radiomic features: The esophageal tumor contours were manually annotated on CT and PET-CT images using our in-house software system [18]. Three groups of image features were computed from pretreatment CT and PET scans based on the manual outlines:[1]Basic tumor features: (a) volume (mL), (b) density (HU), (c) mean diameter (mm), (d) maximum length (mm), and density based on average HU value.[2]CT-based tumor radiomic features: High-dimensional radiomic features ($$n = 500$$) were automatically extracted from the segmented regions on the CT images, which included summary, first order, shape, and gray-level co-occurrence features [19].[3]Tumor PET features: PET features were quantified by mapping tumor ROIs from the CT images onto PET images and then extracting functional characteristics, including maximum SUV, minimum SUV, average SUV, SUV entropy, SUV P75, PET metabolic tumor volume (MTV)/mL, and PET total lesion glycolysis (TLG). ## 2.4. Clinical Features Clinical and demographic information included post-surgery survival time, pathologic stage, height, weight, BMI, age, sex, race, and smoking status (current-smoker, former-smoker, or never-smoker). ## 2.5. Statistical Analysis Cox proportional-hazard model was used to perform survival analysis. All variables were initially evaluated by univariate analysis. Then, multivariate Cox proportional-hazard models were created using backward-stepwise regression. The final model kept all variables with a p-value less than 0.05. The primary performance metric for the Cox proportional-hazard model was the concordance index (c-index). Independent time-point survival classification was performed on subsets of the cohort at three time points: one-year, three-years, and five-years post-esophagectomy. Patients were included into the time points if their survival time was greater than the time of consideration or their date of expiration was known (not censored). Models constructed include the logistic regression modeling with L1 penalty [20], the Naïve Bayes model with a Gaussian prior [21], the random-forest model with the Gini impurity index [22], and the support vector machine (SVM) with the radial basis kernel function [23,24]. Models were trained and tested on both normalized and un-normalized data; the model with superior performance was selected. Z-score normalization was used to standardize the data. Two sets of models were created for each time point. One model was created using just pathologic T-, N-, and M-stage variables, herein termed the “reference model”. The second model included stage variables in addition to the clinical and radiomic features. A multivariable model was constructed using stepwise forward logistic regression on each variable group (i.e., radiomic, tumor, PET, body composition, and clinical features). Intermediate variable models were then combined to create the final nested model using forward stepwise logistic regression. Training and validating the models were performed using 10-fold cross-validation. The performance metric was the area under the receiver operating characteristic curve (AUC/ROC). The DeLong test was used to assess the difference in performance between our model and the reference model, as well as to assess the impact of variables on the performance of the final model [25]. All statistics were performed in R 3.4.1 or Python. A p-value less than 0.05 was considered statistically significant. ## 3.1. Body Composition The cohort had 183 patients who had an esophagectomy but did not receive preoperative chemotherapy or radiation. Demographic and clinical information are summarized in Table 1. Supplemental Table S1 lists the body composition and tumor features. There was no significant difference between body composition distribution based on any demographic categories. ## 3.2. Cox Regression Analysis Sixteen of the 500 radiomic features had statistical significance in the univariate Cox proportional-hazard models for overall survival. Clinical features that contributed to mortality were advanced pathological T- and N-stage, being a former smoker, being older, and having low BMI (Table 2). VAT density was the only body composition from the univariate Cox proportional-hazard model that was statistically significant (Table 3). The final post-esophagectomy five-year survival model generated a concordance index (c-index) of 0.754, using eight variables, including four clinical features (race, BMI, pathological N-stage, pneumonia) and four body-composition features (bone density, muscle density, IMAT volume, SAT volume) (Table 4). ## 3.3. One-Year Survival One-year survival had 147 patients included in the analysis. The SVM model for predicting one-year post-esophagectomy survival exhibited significantly higher performance than the logistic regression, Naïve Bayes, and random forest models (Supplemental Figure S2). Specifically, the SVM model had an AUC of 0.817 ($95\%$ CI: 0.0.738–0.897) using five clinicodemographic (race, BMI, pathological n-stage, effusion, pneumonia), one radiomic feature (DV), 1 PET feature (SUV p75) and three body composition variables (bone density, bone mass, VAT density) (Supplemental Table S2). In contrast, the reference model, which used only pathological T-, N-, and M, yielded an AUC of 0.584 ($95\%$ CI: 0.461–0.725). The performance of the SVM model was significantly better than the reference model (Figure 1A, $$p \leq 0.0005$$). Furthermore, the full SVM model’s performance was significantly superior to the SVM model without body composition variables (Figure 1B, $$p \leq 0.0286$$), which produced an AUC of 0.725 ($95\%$ CI: 0.612–0.838). ## 3.4. Three-Year Survival Three-year survival had 113 patients included in the analysis. The random forest model for predicting three-year post-esophagectomy survival exhibited superior performance compared to the other three models (Supplemental Figure S3) with an AUC of 0.693 ($95\%$ CI: 0.594–0.792). This model incorporated six radiomic features (Mean intensity, 10th percentile intensity, root-mean-squared average intensity, summed average intensity, and grey-level co-occurrence matrix autocorrelation), four clinical features (race, pathological T-stage, pathological M-stage, smoking history), one PET feature (minimum SUV uptake), and three body composition features (bone mass, IMAT mass, IMAT volume) (Supplemental Table S3). The reference model achieved an AUC of 0.598 ($95\%$ CI: 0.491–0.706), and the SVM model did not show a significant difference (Figure 2A, $$p \leq 0.127$$). The performance of the full random forest model was not statistically different from that of the random forest model without body composition variables, which achieved an AUC of 0.678 ($95\%$ CI: 0.578–0.777) (Figure 2B, $$p \leq 0.629$$). ## 3.5. Five-Year Survival The five-year survival had 99 patients included in the analysis. The SVM model for predicting five-year post-esophagectomy survival outperformed other models (Supplemental Figure S4) with an AUC of 0.861 ($95\%$ CI: 0.783–0.938). This model incorporated four radiomic features (mean, root-mean-squared mean, median, and 10th percentile intensity), three clinical features (age, BMI, pathological T-stage), one tumor feature (mean diameter), and two body composition features (VAT mass and IMAT volume) (Supplemental Table S4). Compared to the reference model with an AUC of 0.731 ($95\%$ CI: 0.617–0.845), the SVM model’s performance was significantly better (Figure 3A, $$p \leq 0.022$$). The full SVM model, including body composition variables, performed significantly better than the model without body composition variables ($$p \leq 0.042$$), which had an AUC of 0.801 ($95\%$ CI: 0.711–0.891) (Figure 3B). ## 4. Comment Although studies have explored the potential of radiomics as a prognostic tool for cancer stage and survival [26,27], the impact of body composition on postoperative survival has received limited attention. We used a prospectively collected database of patients who underwent esophagectomy and specifically selected patients who did not receive neoadjuvant treatments. This approach allowed us to accurately determine the “true” pathologic stage, as that is a well-known predictor of survival. Our model, which incorporated clinicopathologic, radiomic, and body composition variables, showed significantly higher performance in predicting one-year and five-year survival compared to a reference model that only used pathologic T, N, and M. Body composition variables were found to be important predictors. Although our three-year model had a higher AUC than the reference model, their difference was not significant according to the DeLong test (Figure 2A). This lack of significance could partly be due to the conservative nature of the DeLong test, which becomes increasingly conservative in “nested” models [28]. Sarcopenia on a single CT slice has been studied as a predictor of clinical outcomes, as it is thought to reflect a subject’s nutritional status, general health, and physical activity. However, our approach using body composition variables derived from a full-body CT scan may provide a more comprehensive assessment of overall health. Our univariate Cox proportional-hazard models indicated that the adipose tissue-related features (VAT, SAT, and IMAT) were all marginally significant, while SAT volume, IMAT volume, bone density, and muscle density volume became significant ($p \leq 0.05$) predictors in the multivariate Cox proportional-hazards model. This suggests that increased subcutaneous and intramuscular adipose tissue volumes and muscle density are associated with decreased survival after esophagectomy, while increased bone density is associated with improved survival outcomes. The role of IMAT in cancer patients is not well understood, but some theory suggests that increased IMAT may be linked to metabolic risk factors, such as insulin resistance, as well as negative effects on immune pathways and wound healing [29]. Previous studies have utilized logistic regression as the primary method for their survival prediction models post-esopahgectomy [5,8,9]. However, we took a different approach by evaluating sophisticated machine learning methods and conducted a comprehensive comparison of the four most common machine learning methods. We found that SVM had the best performance, even with a relatively small number of predictors (~10). Although logistic regression is a simpler method for prediction modeling and performs well with a smaller set of variables, SVM generates a high-dimensional feature landscape and improved separation of classes when incorporating a broader array of features. The importance of including non-significant variables in the multivariate analysis should be noted, as some of the variables may become significant when included with other predictors in the model. Traditionally, only variables that show significance in univariate analysis are included in the multivariate analysis. However, the suppression principle in statistics recognizes that the addition of a third variable can provide more insight into the relationship between an independent and dependent variable [30]. Therefore, we have included some variables in the multivariate models that did not show significance in the univariate analysis to better understand the complex relationships between variables. This study has several limitations that should be acknowledged. First, our analysis only include patients who did not receive neoadjuvant treatment, which allowed us to have accurate pathologic staging as a reference for survival prediction. However, our analysis does not take into account postoperative treatments, although postoperative complications were included into models. While our cohort only included preoperative CT-scans, future work that includes not only preoperative, but also postoperative CT-scans could greatly improve our understanding of how changes in body composition will affect overall survival outcomes. Additionally, we did not consider other potential prognostic factors, such as tumor grade or location, although most of the patients had distal esophageal adenocarcinoma. The use of various CT protocols over a 13-year period also introduced a diverse set of images used for model training, which could affect the generalizability of our findings. While we used an automated body composition segmentation tool, its accuracy is not perfect, but we find the results encouraging and believe that future studies should explore this further. Finally, external validation and larger cohorts are needed to establish the robustness of our work. 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--- title: Valproic Acid Inhibits Progressive Hereditary Hearing Loss in a KCNQ4 Variant Model through HDAC1 Suppression authors: - Yoon Seok Nam - Young Mi Choi - Sungsu Lee - Hyong-Ho Cho journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10058529 doi: 10.3390/ijms24065695 license: CC BY 4.0 --- # Valproic Acid Inhibits Progressive Hereditary Hearing Loss in a KCNQ4 Variant Model through HDAC1 Suppression ## Abstract Genetic or congenital hearing loss still has no definitive cure. Among genes related to genetic hearing loss, the potassium voltage-gated channel subfamily Q member 4 (KCNQ4) is known to play an essential role in maintaining ion homeostasis and regulating hair cell membrane potential. Variants of the KCNQ4 show reductions in the potassium channel activity and were responsible for non-syndromic progressive hearing loss. KCNQ4 has been known to possess a diverse variant. Among those variants, the KCNQ4 p.W276S variant produced greater hair cell loss related to an absence of potassium recycling. Valproic acid (VPA) is an important and commonly used histone deacetylase (HDAC) inhibitor for class I (HDAC1, 2, 3, and 8) and class IIa (HDAC4, 5, 7, and 9). In the current study, systemic injections of VPA attenuated hearing loss and protected the cochlear hair cells from cell death in the KCNQ4 p.W276S mouse model. VPA activated its known downstream target, the survival motor neuron gene, and increased acetylation of histone H4 in the cochlea, demonstrating that VPA treatment directly affects the cochlea. In addition, treatment with VPA increased the KCNQ4 binding with HSP90β by inhibiting HDAC1 activation in HEI-OC1 in an in vitro study. VPA is a candidate drug for inhibiting late-onset progressive hereditary hearing loss from the KCNQ4 p.W276S variant. ## 1. Introduction Currently, the genetic cause of hearing loss (HL) is being extensively investigated. It has been reported that genetic causality is detected in $50\%$ of early-onset deafness [1]. Nonetheless, there are currently no definitive methods with which to cure congenital or genetic HL. Hearing aids and cochlear implantations are still the main rehabilitation methods for congenital HL [2]. Identifying the problematic gene is more for predicting the prognosis and subsequent patient counseling. Late-onset HL acquires hearing problems after birth. In contrast to congenital HL, late-onset HL provides a larger period for interventions, such as gene editing or gene replacement. Clinical trials for HL gene therapy have begun for gene defects such as GJB2 or Otoferlin (OTO-825 and AK-OTOF, respectively). The slower the progression of hearing loss, the larger the time period will be for the intervention. The potassium voltage-gated channel subfamily Q member 4 (KCNQ4) is highly expressed in the outer hair cells of the organ of Corti [3]. It is also expressed in the brainstem, especially along the central auditory pathway [4]. In the outer hair cell, the KCNQ4 is expressed in both the basal and lateral membranes immediately following birth. However, it is expressed only in the basal membrane after the onset of hearing (P14 in mice) [4,5]. The expression is higher in the basal turn and weaker in the apical turn. It was suggested that the KCNQ4 extrudes K+ ions that entered outer hair cells from the apical membrane [6]. KCNQ4 mutations are etiologically linked to one of the most common types of non-syndromic HL: deafness non-syndromic autosomal dominant 2 (DFNA2) [7,8,9]. Fortunately, hearing loss in DFNA2 patients exhibits a late onset and progresses slowly over decades [8]. KCNQ4 knock-out mice demonstrate a similar pattern, thus providing a good model for late-onset progressive hereditary HL. Using these mouse models, it was suggested that DFNA2 HL is caused by the slow progressive damage of the outer hair cells through chronic depolarization [6]. Histone deacetylase (HDAC) is an important player in chromatic structure condensation and suppressing gene expression [10]. HDAC inhibitors have been used for a wide variety of purposes including anticancer, anti-aging, anti-inflammatory, antioxidative, and neuroprotection [11]. Similarly, the ability of HDAC inhibitors, SAHA and trichostatin A, to manage hearing deficits including drug-induced or noise-induced HL has been investigated [11]. Treatment with sodium butyrate showed a protective effect on gentamicin-induced hair cell loss through HDAC1 modulation [12]. Valproic acid (VPA), originally an anticonvulsant, also provided an HDAC inhibitory effect and regulated HDAC class I and II [13]. Interestingly, VPA showed its antiepileptic effect by preserving the KCNQ family M-current activity [14]. In addition, the combination of CHIR99021 and VPA is in the clinical trials (FX-322) to treat sensorineural hearing loss [15]. HDAC inhibitors, which are central players in epigenetic gene modification and regulation of intracellular signaling, are involved in HL gene regulation [11]. Therefore, VPA treatment is also well suited for modulating HL in a KCNQ4 variant model. Herein, we investigated the protective effects of VPA on the auditory functions of the KCNQ4 variant and analyzed the feasibility of using an HDAC inhibitor to modulate late-onset genetic HL. ## 2.1. Valproic Acid (VPA) Inhibits Progressive Hearing Deterioration in a KCNQ4 p.W276S Variant Mouse Model Kharkovets et al. [ 6] reported that staining for the KCNQ4 protein revealed its presence at the base of the wild-type (WT) outer hair cell (OHC). Likewise, the KCNQ4 was detected in the OHCs from WT mice (Supplement Figure S1). The KCNQ4 p.W276S variant in 4–16-week-old mice showed significantly reduced hearing by click ABR (Supplement Figure S2A). In addition, there was also a significantly decreased tone burst ABR in the KCNQ4 p.W276S variant mice (Supplement Figure S2B). The KCNQ4 p.W276S variant led to the onset of deafness in mice before 4 weeks. Therefore, VPA (200 mg/kg body weight, once daily) treatment was administered by intraperitoneal (IP) injection to wild-type (WT, +/+), heterozygote (hetero, KI/+), and homozygote (homo, KI/KI) KCNQ4 p.W276S variant mice from 3 weeks to 6 weeks (21 days) (Figure 1A). At an age of 6 weeks, the hearing was normal in WT mice (30 ± 0 dB SPL), whereas it worsened in the hetero mice (75 ± 5 dB SPL). While the homo mice were nearly deaf (92.6 ± 1.94 dB SPL) without the VPA injection, the administration of VPA significantly improved the hearing of the homo mice (83 ± 1.72 dB SPL). Moreover, VPA treatment had a similar tendency in the hetero mice, although it was not statistically significant (70 ± 4.53 dB SPL). The VPA injection to WT mice produced no harmful effects and showed similar results to the non-treated WT (30 ± 0 dB SPL) (Figure 1B). Furthermore, tone burst ABR significantly attenuated the HL at 8, 16, 24, and 32 kHz in the homo KCNQ4 p.W276S variant mice (Figure 1C). The continuous administration of VPA by osmotic pump (200 mg/kg, from 3–7 weeks) also presented significant hearing preservation at the 5- and 6-week timepoints (Supplement Figure S3). Ultimately, all the treatment groups lost their hearing at 7 weeks. This result demonstrates that VPA can preserve the auditory function and delay the onset of HL in a KCNQ4 p.W276S variant in vivo. ## 2.2. Systemic Injection of VPA Directly Affects the Cochlea We examined the gene expression in the brain and cochlear following the IP injection to determine whether the protection provided by VPA was due to a direct effect on the cochlea and brain. An intravenous injection of VPA (200 mg/kg) was administered, after which VPA activated the survival motor neuron (SMN) gene mRNA expression [16]. The expression of the SMN gene was increased in the brain of VPA-treated mice compared to the non-treated control brains (3.1 ± 0.4 vs. 1 ± 0.1) (Figure 2A). In the cochlea, the expression of SMN was 2-fold higher in the VPA-treated group than the non-treated group (2 ± 0.4 vs. 1 ± 0.2) (Figure 2B). According to Lauren E et al. [ 17], VPA treatment is associated with histone acetylation levels and SMN gene expression through HDAC2 inhibition. To determine if HDAC is inhibited by VPA treatment in the cochlea, we stained for histone H4 acetylation and analyzed by immunostaining. In all three parts of the cochlea (apex, middle, and base), the histone acetylation staining was more pronounced in the SV (stria vascularis), SL (spiral ligament), OC (Organ of Corti), and SG (spiral ganglion) (Figure 2C, white square) of the VPA-treated cochlea when compared to the VPA untreated mice (Figure 2C), as evidenced by the histology analysis (Figure 2D–F). Therefore, we concluded that a VPA injection can provide direct effects inside the cochlea. ## 2.3. VPA Rescues the OHC from Cell Death in the KCNQ4 p.W276S Variant We showed that the KCNQ4 variant-induced hearing loss is improved by VPA treatment, and the cochlea were investigated using whole-mount immunofluorescence (Figure 3A). The OHC cell staining was conducted using Prestin and revealed that the KCNQ4 homo p.W276S variant contained a large number of OHC loss in the middle and base areas (Figure 3B). Staining with Myo7a showed that there was no damage to the IHCs (Figure 3B). The number of OHCs was decreased at all levels of the cochlea in the VPA non-treated homo group, although predominantly at the base turn. However, the number of OHCs was higher in the VPA-treated homo mice at the base and the rest of the cochlea turns. Despite a substantial loss of OHCs in the KCNQ4 hetero and homo p.W276S variants, in the middle and the base, the VPA treatment significantly improved the overall OHC survival (Figure 3B). Thus, by reducing HDAC activity with VPA, the OHCs were protected from cell death in the KCNQ4 p.W276S variant mice. ## 2.4. VPA Upregulated KCNQ4 Expression by Inhibiting HDAC1 Activity Next, we demonstrated that VPA regulated the expression of KCNQ4 and HSP90β in HEK293T cells. VPA treatment promoted the expression of KCNQ4 in pcDNA3.1-KCNQ4-EGFP-8xHis transfected HEK293T cells (Figure 4A). Similarly, the expression of transfected pcDNA3-HA-HSP90β was increased using VPA treatment (Figure 4B). VPA is known to be an HDAC class I and class IIa specific inhibiter [18]. We performed several class I and class IIa HDAC overexpression tests in HEK293T cells to determine which HDAC member was regulated by the VPA treatment in the cochlea (Supplement Figure S4A,B). Indeed, transfection of pCs2+-3myc-HDAC1 led to overexpression in HEK293T cell lines, which reduced the expressions of KCNQ4 and HSP90β (Supplement Figure S4A). Likewise, transfection of pCs2+-3myc-HDAC1 decreased the expressions of pcDNA3.1-KCNQ4-EGFP-8xHis and pcDNA3-HA-HSP90β in a dose-dependent manner (Figure 4C,D). In addition, endogenous KCNQ4 and HSP90β expressions were reduced by the overexpression of HDAC1 in a dose-dependent manner (Figure 4E). ## 2.5. VPA-Induced HSP90β Expression and HSP90β–KCNQ4 Interaction Yanhong et al. [ 19] reported that HSP90α and HSP90β possess key roles in controlling the KCNQ4 homeostasis through the HSP40-HSP70-HOP-HSP90 chaperone pathway and the ubiquitin-proteasome pathway. Indeed, HSP90α and HSP90β both bind to KCNQ4 and exert opposite effects on the KCNQ4 channel. Most importantly, HSP90β restored KCNQ4 surface expression in cells mimicking the heterozygous conditions of DFNA2 patients. Next, we performed an immunoprecipitation assay and transfected HEK293T cells with the pcDNA3.1-KCNQ4-EGFP-8xHis and pcDNA3-HA-HSP90β plasmid. An anti-GFP antibody was used for the KCNQ4 immunoprecipitation, and HSP90β was detected with an anti-HA (HSP90β) antibody. The KCNQ4 successfully recruited HSP90β and the VPA treatment increased binding in HEK293T cells (Figure 5A). However, HDAC1 (myc) interrupted the HSP90β (HA)–KCNQ4 (His) binding by recruiting KCNQ4 (Figure 5B). This result showed that KCNQ4 binding competed with HDAC1 and HSP90β and that the KCNQ4–HDAC1 binding affinity was stronger than that of KCNQ4–HSP90β. Overall, VPA treatment upregulated HSP90β and increased HSP90β–KCNQ4 binding by inhibiting HDAC1 activation. Altogether, these results suggest that VPA treatment represents an intriguing candidate for the future therapy of DFNA2 patients (Figure 6). ## 3. Discussion This study is the first to elucidate that hearing loss induced by the KCNQ4 variant can be protected by inhibiting HDAC1 activation. In addition, we also showed that HDAC1 can regulate KCNQ4 and HSP90β expression through its interaction with KCNQ4. The overexpression of HDAC1 downregulated KCNQ4 and HSP90β expression and disrupted the binding of KCNQ4 to HSP90β. Thus, we propose that HDAC1 is an upstream signal transduction regulator of KCNQ4 and HSP90β. VPA activated its known downstream target, the SMN gene within the cochlea [17]. VPA treatment in mouse brain tissues increased histone acetylation levels, while associated HDAC2 levels increased at the SMN transcriptional start site. It represents an effective strategy for the treatment of spinal muscular atrophy (SMA). Brain and cochlea SMN mRNA expressions were markedly increased by VPA treatment (Figure 2A,B), while VPA treatment also increased histone H4 acetylation in the cochlea (Figure 2C). Thus, the intraperitoneal injection of VPA produced notable effects on the cochlea apex, middle, and base of the SV, SL, OC, and SG signaling regulations (Figure 2D–F). Our data suggest that VPA can reach the cochlea and works directly inside the cochlear tissue, instead of causing a secondary effect through other organs. VPA is known to be the elevated level of gamma-aminobutyric acid (GABA) in the brain. It modulates neuronal discharge by increasing GABA levels in pre- and postsynaptic neurons. Therefore, VPA enhances GABA activation and amplifies the neuronal response [20]. In the cardiovascular system, VPA ameliorated cardiac dysfunction, cardiac hypertrophy, and fibrosis [21]. Furthermore, VPA improves glycemic control by enhancing the number of β-cells in rat diabetic models [22]. In a model of diabetic nephropathy, Sun et al. found that VPA attenuated diabetes-mediated renal injury by suppressing endoplasmic reticulum-induced stress and apoptosis [23]. In addition, VPA also showed anticancer actions, whereby MCF-7 breast carcinoma cells, NCI-1299 and NCI-H460 lung cancer cells, NB-2 and UKF-NB-3 neuroblastoma cell lines, and HL-60 leukemia cells all underwent enhanced VPA-mediated apoptosis [24]. Previous studies indicated that HDACs are associated with the development and progression of hearing loss. The HDAC inhibitor, TSA, showed a protective effect on gentamicin-induced hair cell loss [25]. Moreover, pretreatment with SAHA markedly reduced noise-induced OHC loss in the NIHL model [26]. Likewise, SAHA could protect against cisplatin ototoxicity [27]. Furthermore, the HDAC inhibitor, sodium butyrate, reduced hair cell loss [12]. Recent studies have elucidated that HDAC functions are implicated in hair cell death characterized by inflammation and ROS production. VPA treatment caused an increase in histone H4 acetylation in the SV, SL, OC, and SG regions. These suggest that HDAC activity is involved in the development of hearing loss and by inhibiting HDAC activities the progression of hearing loss can be modulated. From preclinical studies to clinical trials, HDAC inhibitors have demonstrated powerful therapeutic effects in various cancers. HDAC inhibitors can significantly attenuate tumor burden by limiting tumor growth and restraining aberrantly proliferated vessels. HDAC inhibitors can also induce DNA damage, cell cycle arrest, apoptosis, and autophagy to promote cancer cell death mentioned above [28]. Indeed, Merkel cell carcinoma (MCC) is partially determined by histone post-translational modifications, including histone acetylation, methylation, and phosphorylation. This malignant behavior of MCC cells can be reverted with HDAC inhibitors [29]. The most striking observation in this study was that VPA inhibited the KCNQ variant-induced HL. VPA is known to be an HDAC inhibitor [30], which selectively inhibits the catalytic activity of class I and class IIa HDACs [31]. Above all, in class I and class IIa HDACs, only HDAC1 contributed to reducing KCNQ4 and HSP90β expressions (Supplement Figure S4). Previous investigations show that VPA targets HDAC1 and HDAC2 [32]. However, our study showed that only HDAC1 had an effect on the expressions of KCNQ4 and HSP90β. Forthun et al. [ 33] reported that HSP90β is upregulated in response to VPA and increased survival in more than $20\%$ of patients. In addition, our study showed that the upregulation of KCNQ4 and HSP90β by VPA (Figure 4A,B) increased the survival of the OHCs (Figure 3A,B). The overexpression of HDAC1 contributed to the downregulation of the expressions of KCNQ4 and HSP90β (Figure 4C–E). This observation provides an indication for the potential therapeutic application of VPA to augment the HSP90β-KCNQ4/HDAC1 signaling cascade. Moreover, VPA markedly increased the physical interaction between KCNQ4 and HSP90β (Figure 5A), which caused the upregulation of the protein expression of both KCNQ4 and HSP90β in HEK 293T cells. Furthermore, HDAC1 disrupted the KCNQ4–HSP90β physical interaction (Figure 5B), which promoted the reduction in their protein expressions. In addition, CHIP (C-terminal of HSP70-interacting protein, NM_005861.2), major E3 ubiquitin ligase for HSP90 client proteins, associate with HSP70-CHIP complexes and to be targeted for degradation via ubiquitination-proteasome pathway. This pathway controls KCNQ4 homeostasis via the HSP40-HSP70-HOP-HSP90 chaperone pathway and the ubiquitin-proteasome pathway [19]. The high potential of the ubiquitin-proteasome system in regulating many human diseases is beginning to receive a broad recognition. Proteins of the ubiquitin-proteasome system and E3 ubiquitin ligases, in particular, are emerging as promising molecular targets for drug discovery in various diseases, including autoimmune and neurodegenerative [34]. In the present study, the reduction of HDAC1 activity by VPA increased KCNQ4 expression and protected against HL in the cochlea. In addition, we found that VPA non-treated KCNQ4 p.W276S variants showed significant OHC death in the middle and base regions of the cochlea. However, treatment with VPA promoted an increased survival of these OHCs in the cochlea of the KCNQ4 p.W276S variants (Figure 3A,B). In addition, Wakizono et al. [ 35] reported that VPA, along with growth factors (EGF and bFGF) combination treatment, recovers spiral ganglion neurons. These results also provided beneficial outcomes for hearing in both the click and tone burst evaluations (Figure 1B,C). There are some studies reporting an ototoxic effect of VPA [36,37]. This contradicts our current study’s findings. Several factors may account for this discrepancy. The effect of VPA might differ according to the dose, age of the recipient, combination with other drugs, frequency of administration, and duration of treatment. VPA might also act differently depending on the type of hearing loss. In genetic hearing loss, such as in our study, the effect of gene regulation may be more effective than the general ototoxic effect. In addition, combinatorial CHIR99021 and VPA treatment is in the clinical trials (FX-322) to treat sensorineural hearing loss. Precise application of VPA on different hearing condition and further patho-mechanistic studies are needed. The reports showed that heterozygous KCNQ4 dimer conformation was attenuated with the KCNQ4 WT and decreased the surface expression of the KCNQ4 p.W276S variant with the WT co-expression [38]. Furthermore, HSP90β significantly improved the cell surface expression of the KCNQ4 WT and KCNQ4 variants and promoted the HSP90β rescue of the KCNQ4 variant channel function, as a result of the surface KCNQ4 expression being significantly improved by the HSP90β molecular chaperone. Moreover, the KCNQ4 variant protein expression was rescued by the dose-dependent expression of HSP90β. Functional KCNQ channels are assembled in homo- or heterotetrameric pore-forming subunits. Therefore, we proposed that the KCNQ4 variant-induced HL is a result of an attenuated KCNQ4 pore assembling and that rescue KCNQ4 pore-forming subunits occur by the molecular chaperone HSP90β. Gene therapy that replaces the missing gene or corrects the defect site is developing progressively these days, while gene therapy has been attempted in genetic hearing loss as well. For example, in delivering Vglut3 by using an adeno-associated virus 1 to Vglut3 knockout mouse, the Vglut3 expression was restored in the inner hair cell, which improved functional hearing [39]. Similarly, injecting the Cas9-guide RNA complex into the Tmc1 Beethoven mouse model, corrected the single defective base pair and rescued the hearing [40]. Moreover, gene editing has previously been conducted in a KCNQ4 p.W276S mouse model. Kv7.4 channel activity and functional hearing were restored by dual adeno-associated virus (AAV) system using CRISPR-based gene therapy [41]. These are all promising strategies for genetic hearing loss. However, one key point in these gene therapies remains, whereby they were performed in the mouse pup, which is still in its developmental stage. In humans, the representative time period is before birth, and performing an intra-cochlear gene delivery through the uterus will be extremely challenging [42]. Delaying the hearing loss progression has a great meaning to meeting the practical time for gene therapy. Our study showed that the progression of hearing deterioration could be inhibited by VPA in a KCNQ4 p.W276S variant model. In summary, VPA suppressed HDAC1, leading to upregulation of KCNQ4, HSP90β expression, and interaction between KCNQ4 and HSP90β. Further study is needed to understand the regulation of downstream target gene by inhibiting HDAC1. Furthermore, although we observed that inhibiting HDAC1 recovers KCNQ4 and HSP90β expression, it remains to be elucidated whether this can restore potassium channel current. For this reason, HDAC inhibitor application maybe needed in the future. Despite the search for insufficient HDAC1 downstream gene regulation, VPA is an excellent candidate drug for inhibiting KCNQ4 variant-induced genetic hearing loss. ## 4.1. VPA Treatment and Generation of Hearing Loss Animals We used KCNQ4 p.W276S variant mice with a C57BL/6N background, which were aged from 3 weeks to 16 weeks. VPA was administered by daily intraperitoneal injection (200 mg/kg) or subcutaneously implanted with an osmotic pump (200 mg/kg/day) for 4 weeks. The Alzet® micro-osmotic pump was purchased from DURECT (DURECT Corporation, Cupertino, CA, USA). The mice were sheltered in a standard-conditioned vivarium, with free access to food and water. Cages were changed every week, and food and water were replenished every three days. Mice were monitored daily for the health status and any signs of discomfort. All mice were healthy until sacrifice. The care and use of the animals in this study were approved by the Institutional Animal Care and Use Committee at Chonnam National University Medical School (CNUHIACUC-21045). KCNQ4 variant mice were kindly provided by professors Jinsei Jung and Jae Young Choi (Yonsei University, College of Medicine) [7,41]. ## 4.2. Auditory Brainstem Response for an Animal Hearing Evaluation We recorded the ABR with a 3RZ6 TDT system (Tucker-Davis Technologies, Alachua, FL 32615, USA), which provided stimuli ranging from clicks to tone bursts. Needle electrodes of 1.5 mm in length were inserted sub-dermally at the dorsal midline between the eyes (none inverting), at the scalp, and posterior to both pinnae. At each frequency, we tested various stimuli intensity levels in decreasing order, from 90 to 20 dB of the visual ABR threshold. Mice were anesthetized using a cocktail of ketamine 80 mg/kg and xylazine 10 mg/kg while performing ABR and remained asleep during all ABR recordings. ## 4.3. Expression Constructs pcDNA3-HA-HSP90β (plasmid #22487) and pcDNA3.1-KCNQ4-EGFP-8xHis expression vectors were purchased from Addgene (plasmid #111453, Watertown, MA, USA). pCs2+-3myc-HDAC1, pCs2+-3myc-HDAC2, pcDNA3.1-HDAC3-Flag, and pAP3neo-HDAC4-Flag were kindly provided by Professor. Gwang Hyeon Eom (Chonnam National University Medical School, Hwasun, Korea). ## 4.4. Immunohistochemistry for OHCs Mice were euthanized with a cocktail of ketamine and xylazine (80 and 10 mg/kg, respectively) before the extraction of the cochlea. Using a 0.5-cc syringe, a hole was created at the apex of each cochlea and the cochlea was then perfused with phosphate-buffered solution (PBS), followed by $4\%$ paraformaldehyde (PFA). It was then immersed in a $4\%$ PFA solution for 1 h with gentle rotation at 4 °C. The cochlea were rinsed twice with PBS before decalcification with 0.12 mM ethylenediaminetetraacetic acid (EDTA) for 1 h on gentle rotation at 4 °C. To reveal the Organ of Corti, the bone and stria vascularis surrounding the cochlea were dissected, and the tectorial membrane was removed. Three small pieces were cut from each cochlea (apex, middle, and base), and the tissue samples were immersed in a blocking buffer for 1 h at room temperature (RT) before being incubated with primary antibodies overnight at 4 °C. After three washing cycles with $0.1\%$ PBS-T (30 min each wash), the samples were incubated in secondary antibodies for 2 h at room temperature. Finally, the samples were washed three times with $0.1\%$ PBS-T for 30 min, stained for 3 min with DAPI and washed in PBS for 30 min. A vector protection solution was used to mount the samples on glass slides and the slides were examined using an LSM 800 laser scanning microscope (Carl Zeiss Microscopy GmbH, Promenade 10, 07745 Jena, Germany). The following antibodies and titers were utilized: myosin-7a (1:200, # 25-6791, Proteus), Prestin (1:1000, # A12379, Cell Signaling Technology, Danvers, MA 01923, USA), KCNQ4 (1:200, #PA5-101767, Thermo Fisher Scientific Inc., Waltham, MA, USA) and DAPI (1:10000, Invitrogen, Carlsbad, CA 92008, USA). ## 4.5. Counting of Hair Cells The number of OHCs in the cochlea was ascertained. The cochlea were divided into the apical, middle, and basal turns, and the hair cells in each turn were counted under 200× magnification. The number of hair cells per 100 µm cochlear turn length was averaged for each group ($$n = 5$$). The lengths of the cochlear turns were measured for each study group. Confocal z-stacks of three areas were generated from each cochlea using a high-resolution confocal microscope (LSM 800 laser scanning microscope). Image stacks were converted using image editing software. At least 12 hair cells were found in each cochlear turn (apex, middle, and base). ## 4.6. Antibodies Primary antibodies used in this study were anti-histone H4ac (39926, Active Motif, Carlsbad, CA 92008, USA), anti-Myo7a (#25-6790, Proteus, Ramona, CA 92065, USA), anti-Prestin (MBS423494, MyBioSource, Inc., San Diego, CA 92195, USA), anti-Flag (F3165), anti-Actin (A2066, Sigma-Aldrich, Inc., St. Louis, MO, USA), anti-KCNQ4 (#PA5-101767, Thermo Fisher Scientific Inc., Waltham, MA, USA), anti-HSP90 beta (ab32568, Abcam, Waltham, MA, USA), anti-HA (#3724), and anti-Myc (#2276, Cell Signaling, Beverly, MA, USA). Anti-GFP (sc-9996) and anti-His (sc-8036) antibodies were purchased from Santa Cruz Biotechnology, Inc. (Santa Cruz, CA, USA). ( HRP)-conjugated secondary antibodies were from Thermo Fisher Scientific Inc., (Waltham, MA, USA), including goat anti-mouse-HRP [31430], and goat anti-rabbit-HRP [32460]. ## 4.7. Protein Preparation For Western blot and immunoprecipitation, cell lysates were obtained using NP lysis buffer ($1\%$ Nonidet-P40, 50 mM Tris pH 8.0, 150 mM NaCl, 10 mM NaF, 1 mM Na3VO4, 5 mM EDTA, 1 mM EGTA, 1 mM PMSF, 1 mM DTT) supplemented with protease inhibitor cocktail. ## 4.8. Co-Immunoprecipitation The transfected cells were lysed in NP40 lysis buffer supplemented with protease inhibitor cocktail (P8340, Sigma-Aldrich, St. Louis, MO, USA), on ice for 30 min. Cell lysates were cleared by centrifugation at 14,000 rpm for 10 min at 4 °C and incubated with primary antibodies, as indicated, at 4 °C for 24 h. The protein complexes were isolated and purified using protein A/G PLUS-Agarose (sc-2003, Santa Cruz), following the manufacturer’s protocol, and analyzed by Western blot. ## 4.9. In Vitro HEK293T Culture and Transfection HEK293T cells were used for all experiments. These cells were maintained according to the manufacturer’s instructions. All transfections were performed using TurboFect™, as described by the manufacturer (Thermo Scientific). Following transfection, the cells transfected with plasmid DNA were incubated at 37 °C for 24 h. ## 4.10. RNA Isolation and Real-Time Polymerase Chain Reaction RNA isolation and real-time polymerase chain reaction were performed for downstream gene analysis. Cochlear whole tissues were harvested, and total RNA was extracted with Trizol reagent (Invitrogen, Carlsbad, CA 92008, USA). The quantity of RNA was determined by spectrophotometry (Spectrophotometer ND-1000 Nanodrop, Technologies Inc., Wilmington, MA, USA) at an absorbance of A260/A280 nm. The results were analyzed using ND-1000 Software. The experiments were performed three times, and each sample was assayed in triplicate. Denaturation was performed for 10 min and 10 s at 95 °C, and the annealing phase took place at 62 °C for 20 s, followed by 72 °C for 30 s with 40 cycles. The primers for each gene are as follows: GAPDH_For (5′-ACC ACA GTCCAT GCC ATC AC-3′); GAPDH_Rev (5′-TCCACCACCCTG TTG CTG TA-3′); SMN_For (5′-GAATGCCACAACTCCCTTG-3′); SMN_Rev (5′-GCAGCCGTCTTCTGACCAA-3′). ## 4.11. Statistical Analysis All data are presented as mean ± SEM. Differences among groups were assessed by a one-way analysis of variance (ANOVA) followed by a post hoc Tukey’s test. Comparisons between the two groups were performed using a Student’s t-test. All statistical analyses were performed with GraphPad Prism 6.0. A value of $p \leq 0.05$ was considered statistically significant. ## 5. Conclusions In this study, we found that VPA inhibited HL progression in a KCNQ4 p.W276S variant model. VPA suppressed HDAC1, leading to upregulation of KCNQ4, HSP90β expression, and interaction between KCNQ4 and HSP90β. 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--- title: 'Plant-Derived Extracellular Vesicles as a Delivery Platform for RNA-Based Vaccine: Feasibility Study of an Oral and Intranasal SARS-CoV-2 Vaccine' authors: - Margherita A. C. Pomatto - Chiara Gai - Federica Negro - Lucia Massari - Maria Chiara Deregibus - Cristina Grange - Francesco Giuseppe De Rosa - Giovanni Camussi journal: Pharmaceutics year: 2023 pmcid: PMC10058531 doi: 10.3390/pharmaceutics15030974 license: CC BY 4.0 --- # Plant-Derived Extracellular Vesicles as a Delivery Platform for RNA-Based Vaccine: Feasibility Study of an Oral and Intranasal SARS-CoV-2 Vaccine ## Abstract Plant-derived extracellular vesicles (EVs) may represent a platform for the delivery of RNA-based vaccines, exploiting their natural membrane envelope to protect and deliver nucleic acids. Here, EVs extracted from orange (Citrus sinensis) juice (oEVs) were investigated as carriers for oral and intranasal SARS-CoV-2 mRNA vaccine. oEVs were efficiently loaded with different mRNA molecules (coding N, subunit 1 and full S proteins) and the mRNA was protected from degrading stress (including RNase and simulated gastric fluid), delivered to target cells and translated into protein. APC cells stimulated with oEVs loaded with mRNAs induced T lymphocyte activation in vitro. The immunization of mice with oEVs loaded with S1 mRNA via different routes of administration including intramuscular, oral and intranasal stimulated a humoral immune response with production of specific IgM and IgG blocking antibodies and a T cell immune response, as suggested by IFN-γ production by spleen lymphocytes stimulated with S peptide. Oral and intranasal administration also triggered the production of specific IgA, the mucosal barrier in the adaptive immune response. In conclusion, plant-derived EVs represent a useful platform for mRNA-based vaccines administered not only parentally but also orally and intranasally. ## 1. Introduction Membrane vesicles secreted by cells have been described as a well-preserved evolutionary mechanism involved in communication among cells [1,2]. These vesicles originally described in eukaryotes, including mammalians, were subsequently found to be present in prokaryotes and in plants [3]. Virtually released by any cell type, secreted membrane vesicles are a heterogenous population with a complex structure that reproduces cell complexity at the nanoscale [1,2]. In fact, they are constituted by a lipid bilayer membrane containing several cell constituents that can be shared from the cell of origin with other cell types. This mechanism is the basis for a cell-to-cell mediated transfer of information [1,2,4]. Interestingly, the discovery of a horizontal transfer of vesicle-encapsulated nucleic acids [5,6,7,8,9,10] protected from enzyme degradation by the vesicle membrane opened up a new field of research that is now rapidly expanding. The term “extracellular vesicles” (EVs) [11] was proposed to include in this heterogenous population membrane vesicles released from multivesicular bodies, also named exosomes, and membrane vesicles originated by budding of plasma membrane, termed microvesicles or ectosomes. Independently of their origin, EVs share a common mechanism of action: the transfer of regulatory transcripts that target genes involved in defined pathways in recipient cells [5,6,7,8,9]. Of interest, the lipid bilayer membrane of EVs guarantees protection of nucleic acid from enzyme degradation, thus preserving the EV cargo [12]. Different reports showed the possibility to engineer EVs with an exogenous nucleic acid using the green fluorescent protein (GFP) mRNA that, once transferred to target cells, was translated into protein [6,7]. Several subsequent studies focused on the exploitation of EVs for drug delivery, with a particular interest in nucleic acids, showing that encapsulated mRNA, non-coding RNA, or DNA can be shared among cells [13]. In addition, strategies to load vesicles with selected membrane proteins have been developed. For instance, a fusion protein interacting with the Endosomal Sorting Complexes Required for Transport (ESCRT) cellular machinery was used to sort a chimeric protein into EVs [14]. The ability of EVs to transfer proteins or nucleic acids to the antigen-presenting cells (APCs) makes them a potential candidate as vaccine carriers [15]. Cells have been engineered to express proteins of SARS-CoV-2 in the EVs to develop a vaccine that induces long-lasting cellular and humoral responses [16]. Bacteria EVs decorated with Spike receptor-binding domain derived from mammalian cell culture were also used to generate anti-viral protein antibodies after intranasal administration [17]. Moreover, a potent SARS-CoV-2 CD8+ T immune response was obtained by generating engineered EVs released by muscle cells [18]. EVs from human cells can be engineered for encapsulating therapeutic agents due to the ability to transfer a great number of biomolecules [19]. However, scalable production of EVs from human cells in GMP conditions is difficult, time-consuming and highly expensive. With respect to human cell-derived EVs, plant-derived EVs may represent a good option for drug delivery because they are non-toxic, are an extractive product that can be produced on a large scale and can be directly manipulated and modified with a wide range of agents [20,21,22,23,24]. In the present study, we evaluated the possible use of edible plant-derived EVs as a delivery platform for mRNA-based vaccines. In fact, due to their resistance, plant-derived EVs represent an ideal natural source for the delivery of drugs such as small interfering RNAs (siRNAs), microRNAs (miRNAs) or poorly soluble natural compounds (e.g., curcumin) [24]. Plant EVs have the advantage, with respect to synthetic nanoparticles, of a high cellular internalization rate, good gastrointestinal stability and low intrinsic immunogenicity [25]. The aim of the present study was to evaluate whether plant-derived EVs were suitable for the delivery of SARS-CoV-2 mRNA as a vaccine via oral and intranasal administration routes. We tested three different SARS-CoV-2 mRNAs coding for full-length surface glycoprotein (FS) (commonly known as S protein), Spike-RBD subunit of S protein (S1) and nucleocapsid phosphoprotein (N). For this purpose, we directly engineered EVs extracted from an easily obtainable liquid source, orange (Citrus sinensis) juice, (oEVs) with a proprietary technique and evaluated in vitro the efficiency of mRNA molecules’ loading and their protection from degrading stress (RNase enzymes and simulated gastric fluid), the EV delivery of mRNA into target cells, the mRNA translation into protein and the subsequent activation of lymphocyte response. We investigated in vivo the effective production of serum antibodies versus the specific S protein of SARS-CoV-2, the specific immune cell activation and the effect of multiple routes of administration including intramuscular, oral and intranasal routes. ## 2.1. oEV Isolation and Loading oEVs were isolated from freshly squeezed orange juice from Citrus sinensis, type Tarocco, purchased from a local certified organic producer (Arancebio srl, Francofonte, SR, Italy) in January 2021 and throughout 2022. The orange juice was filtered with a strainer and centrifuged at 4000× g for 30 min. The supernatant was ultracentrifuged at 10,000× g for 1 h at +4 °C (Optima L-90K ultracentrifuge, rotor 45 Ti, polycarbonate tubes, Beckman Coulter, Milan, Italy). The supernatant was then filtered to reduce the presence of fibers and re-ultracentrifuged at 100,000× g for 2 h at +4 °C (Optima L-90K ultracentrifuge, rotor 45 Ti, polycarbonate tubes, Beckman Coulter, Milan, Italy). The pellet was re-suspended in saline solution (NaCl $0.9\%$, B. Braun, Milan, Italy) added with $1\%$ DMSO (Sigma-Aldrich, Merck, Darmstadt, Germany), filtered with 0.22 filters (Millex, Millipore, Merck, Darmstadt, Germany) for sterilization and stored at −80 °C for further experiments. mRNA sequences were designed as described in Table 1 and purchased from RiboPro (Oss, The Netherlands). No codon optimization or other mRNA modifications were applied to mRNA sequences. The mRNAs were completed with a 5’UTR designed for high expression, a poly-A tail and a Cap1 with methylation of the first nucleotide to produce a Cap1 structure. After mRNA synthesis, dsRNA was removed to avoid innate immune-mediated translational repression. mRNAs were loaded into oEVs with a proprietary technique described in the patent application WO/$\frac{2022}{152771}$A1 using cation-based interaction combined with controlled osmotic shock. ## 2.2. oEV Characterization oEVs were analyzed through nanoparticle tracking analysis (NTA) using the NanoSight NS300 system (Malvern Panalytical, Malvern, UK), equipped with NTA 3.4 analytic software. The instrument uses a laser source to inspect the sample and analyzes the Brownian movements of detected particles. The analytic software uses the Stokes–Einstein equation for converting this information into size and concentration parameters. For each sample, oEVs were diluted in a range of 1:200–1:2000 in 1 mL of saline solution (NaCl $0.9\%$, B. Braun, Milan, Italy) previously filtered with 0.1 µm membranes (Millex, Millipore, Merck, Darmstadt, Germany). Three videos of 30 s duration were recorded and camera levels were set to 15 for all the acquisitions. Settings for NTA post-acquisition were optimized and maintained constant among all samples, and each video was analyzed to measure the mean size and concentration of oEVs. The morphology and integrity of oEVs were analyzed by transmission electron microscopy (TEM) as previously described [26]. Briefly, oEVs were left to adhere on 200 mesh nickel formvar carbon-coated grids (Electron Microscopy Science, Hatfield, PA, USA) for 20 min. Then, grids were incubated with $2.5\%$ glutaraldehyde plus $2\%$ sucrose. After washing in distilled water, samples were negatively stained with Nano-W and NanoVan (Nanoprobes, Yaphank, NY, USA) and analyzed using a Jeol JEM 1400 Flash electron microscope (Jeol, Tokyo, Japan). ## 2.3. RNA Extraction and qRT-PCR Total RNA was extracted from cells and oEVs using a miRNeasy mini kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. RNA was eluted in nuclease-free water (Ambion, Thermo Fisher Scientific, Waltham, MA, USA) and the RNA concentration was assessed by measuring the absorbance at 260 nm with a spectrophotometer (mySPEC, VWR, Radnor, PA, USA). Samples were stored at −80 °C until analysis. RNA was retro-transcribed to cDNA using a High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific, Waltham, MA, USA) following the manufacturer’s instructions (100 nanograms for cell analysis and 10 µL for oEV analysis). Syn-cel-miR-39 (Qiagen, Hilden, Germany) was added to oEV samples as spike-in during the retro-transcription procedure. For qRT-PCR, each sample was run in triplicate; the primers (Eurofins Genomics, Milan, Italy) are listed in Table S1. For syn-cel-miR-39, the universal primer (Qiagen, Hilden, Germany) was used as the reverse primer. Human ACTB was used as the endogenous control for mRNA incorporation into target cells, whereas cel-mir-39 was used as the endogenous control for mRNA loading into oEVs. cDNA (5 nanograms for cell analysis and 2.5 µL for oEV analysis) was combined with SYBR GREEN PCR Master Mix (Thermo Fisher Scientific, Waltham, MA, USA) as described by the manufacturer’s protocol. The Real-Time Thermal Cycler Quant Studio 12k and ExpressionSuite Software 1.0.3 (Thermo Fisher Scientific, Waltham, MA, USA) were used to calculate relative quantification (RQ) values via the 2−ΔΔCt method. For the generation of standard curves for absolute quantification of mRNAs, each mRNA (S1, FS and N) was spectrophotometrically quantified and 200 ng were reverse transcribed using the High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific, Waltham, MA, USA). cDNA was serially diluted 1:5 from a starting point of 10 ng to have 11 dilutions. Serial dilutions were run in five replicates using Relative Standard Curve on a 96-well QuantStudio 12K Flex Real-Time PCR system, as described by the manufacturer’s protocol (Thermo Fisher Scientific Scientific, Waltham, MA, USA). The calibration curve was used to convert the Ct values of each sample into the corresponding amount of mRNA. The percentage of engineering yield was calculated as follows: (final amount mRNA/oEV)/(starting amount mRNA/oEV). EV loading was repeated in three independent experiments for each mRNA used. ## 2.4. PCR and Electrophoresis cDNA was amplified with iProofTM High-Fidelity DNA Polymerase (Biorad, Hercules, CA, USA) following the manufacturer’s instructions. The PCR reaction mix was composed of 4 ng cDNA, 500 nM primer (Eurofins Genomics, Milan, Italy), 0.5 µL iProof DNA Polymerase (Biorad, Hercules, CA, USA), 10 µL 5x iProof HF buffer, 1 µL dNTPs, 0.5 µL MgCl2, and nuclease-free water (Thermo Fisher Scientific, Waltham, MA, USA) to reach the reaction volume of 50 µL. The CTR DNA template was amplified with 1.3 kB primers (both provided by the kit) as the internal reaction control. The PCR was performed with VERITI Thermal Cycler (Thermo Fisher Scientific, Waltham, MA, USA), with 30 amplification cycles run. For gel electrophoresis, 15 µL of PCR products was mixed with 3 µL of 6X TriTrack DNA Loading Dye from a GeneRuler 100 bp Plus DNA Ladder Kit (Thermo Fisher Scientific, Waltham, MA, USA). Then, 15 µL of the mix was loaded on a $5\%$ Mini-PROTEAN® TBE Gel (Biorad, Hercules, CA, USA). The electrophoresis cell was filled with 1X TBE buffer (Biorad, Hercules, CA, USA) and the run was performed at 100 V for 45 min. Gels were soaked for 20 min in ethidium bromide (Biorad, Hercules, CA, USA) diluted to 0.5 µg/mL in 1X TBE buffer and subsequently washed in sterile water (B.Braun, Milan, Italy) for 20 min at RT. Images were acquired with a ChemiDoc System (Biorad, Hercules, CA, USA). Data were obtained from three independent experiments. ## 2.5. Cell Culture Human macrophages (MV-4-11), human dermal microvascular endothelial cells (HMEC-1) and normal human dermal fibroblasts (NHDF) were obtained from ATCC (Manassas, VA, USA) and cultured following the manufacturer’s instructions with, respectively, Iscove’s modified Dulbecco’s medium (IMDM, ATCC, Manassas, VA, USA), MCDB131 medium (Gibco, Thermo Fisher Scientific, Waltham, MA, USA) and fibroblast growth basal medium (FBM, Lonza, Basel, Switzerland) supplemented with $10\%$ fetal bovine serum (FBS, Life Technologies, Thermo Fisher Scientific, Waltham, MA, USA). Human primary peripheral blood mononuclear cells (PBMC) were isolated from the peripheral blood of healthy donors provided by the Centro Produzione e Validazione Emocomponenti of the A.O.U. Città della Salute e della Scienza di Torino with internal ethical approval. PBMC were isolated via a density gradient using Histopaque®-1077 (Sigma Aldrich, Merck, Darmstadt, Germany), washed with PBS (Thermo Fisher Scientific, Waltham, MA, USA) and plated at a concentration of 2 × 106 cells/mL in a 12-well plate with RPMI 1640 (Euroclone, Milan, Italy) supplemented with $10\%$ FBS (Life Technologies, Thermo Fisher Scientific, Waltham, MA, USA). All cells were incubated at 37 °C with $5\%$ CO2. The effect of oEVs on cell viability was evaluated with a MTT Cell Growth Assay Kit following the manufacturer’s instructions (Sigma-Aldrich, Merck, Darmstadt, Germany). Briefly, HMEC-1 was plated at a density of 5000 cells/well in 96-well plates (Euroclone, Milan, Italy) and treated with four increasing doses of oEVs (10,000, 50,000, 100,000 and 200,000 particles/cell) diluted in medium (DMEM low glucose with $5\%$ EV-depleted FBS) (Euro-clone, Milan, Italy). The viability measurement was performed after 24 h of treatment, comparing cells cultured with medium, medium plus oEVs or medium plus $50\%$ DMSO as the positive control (Sigma-Aldrich, Merck, Darmstadt, Germany). Data were obtained from three independent experiments. ## 2.6. mRNA Stress Resistance To test the resistance to enzyme degradation of mRNAs loaded into oEVs, samples were treated with 0.4 µg/mL AmbionTM RNase A (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) and incubated at 37 °C for 30 min as previously described [27]. The reaction was stopped by adding Ambion™ RNase inhibitor (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s instructions. Samples were washed by ultracentrifugation at 100,000× g for 2 h at +4 °C using a 10 mL polycarbonate tube (SW 90 Ti rotor, Beckman Coulter Optima L-90 K ultracentrifuge, Beckman Coulter, Milan, Italy) and were resuspended in saline buffer solution for analysis. The resistance to gastrointestinal degradation was investigated as previously described [28]. Briefly, a simulated gastric fluid (SGF) was prepared using $18.5\%$ w/v HCl (pH 2.0), 24 mg/mL of bile extract, pepsin solution (80 mg/mL in 0.1 N of HCl, pH 2.0) and 4 mg/mL of pancreatin in 0.1 N of NaHCO3 (Sigma-Aldrich, Merck, Darmstadt, Germany). Next, 100 µL of each oEV sample was incubated with 1.34 µL of SGF at 37 °C for 60 min. Then, the pH value was adjusted to 6.4 with 1 N NaHCO3 to mimic the intestinal solution and incubated for 60 min. Free mRNA was used as a control and the percentage of resistance was defined as the percentage of mRNA remaining after stress treatments in comparison to starting material. Data for each mRNA were obtained from three independent experiments. For experiments with Triton X-100, samples were treated with $1\%$ Triton X-100 (Biorad, Hercules, CA, USA) for 1 h at +4 °C before RNAse treatment and molecular analysis. ## 2.7. mRNA Incorporation into Target Cells Human macrophages were plated 60,000 cells/well in 24-well plates (Sarstedt, Milan, Italy) and treated with different stimuli: medium (IMDM plus $10\%$ FBS), or medium plus oEVs, oEV-S1, oEV-FS or oEV-N (1.2 × 1010 oEVs containing 1 µg mRNA/well). As a control, cells were co-incubated or transfected with a similar amount of each mRNA with Lipofectamine® 2000 Reagent (Thermo Fisher Scientific, Waltham, MA, USA) following the manufacturer’s instructions. Next, 0.75 µL/well lipofectamine and 1.0 µg/well mRNA were diluted in DMEM low glucose (Euroclone, Milan, Italy), incubated for 5 min at room temperature and added to wells containing medium. After 24 h, cells were harvested and processed for molecular analysis. Data were obtained from three independent experiments. ## 2.8. Cytofluorometric Analysis of mRNA Translation into Protein HMEC-1 was plated at 50,000 cells/well in 24-well plates (Sarstedt, Milan, Italy) and treated with different stimuli: medium (MCDB131), or medium plus oEVs, oEV-S1, oEV-FS or oEV-N (1.2 × 1010 oEVs and 1 µg mRNA/well). As the control, cells were transfected with a similar amount of each mRNA using Lipofectamine® 2000 Reagent (Thermo Fisher Scientific, Waltham, MA, USA) following the manufacturer’s instructions. Briefly, 0.75 µL/well lipofectamine and 1.0 µg/well mRNA were diluted in DMEM low glucose (Euroclone, Milan, Italy), incubated for 5 min at room temperature and added to each well containing MCDB131 medium plus $10\%$ FBS. Treatment with only lipofectamine reagent was used as the transfection control. After 24 h of treatment, cells were collected and treated using an Inside Perm Kit (Miltenyi Biotec, Bologna, Italy) for the intracellular staining, following the manufacturer’s instructions. Briefly, cells were treated with Fix Inside reagent for 20 min at room temperature, washed with PBS and mixed with anti-N-protein rabbit antibody (1:250, PA1-41098, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) or anti-S1-protein mouse antibody (1:100, MA5-38033, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) for 1 h at room temperature. After washing, samples were incubated with 5 µg/mL fluorescent secondary antibody anti-mouse (green, A32723, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) or anti-rabbit (red, A32740, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) for 1 h at room temperature. Finally, samples were washed and resuspended in saline solution for acquisition with CytoFLEX (Beckman Coulter, Milan, Italy) and CytExpert software (v 2.3.0.84, Beckman Coulter, Milan, Italy). Data were obtained from three independent experiments. ## 2.9. Confocal Microscopy Analysis of mRNA Translation into Protein HMEC-1 were plated at 10,000 cells/well in 8-well chamber slides (Thermo Fisher Scientific, Waltham, MA, USA) and treated with different stimuli: medium (MCDB131), or medium plus oEVs, oEV-S1, oEV-FS or oEV-N using a particle dose of 1.2 × 1010 oEVs/well and 1 µg mRNA/well. As control, the cells were transfected with a similar amount of nude mRNA S1, FS, N. Transfection was performed with Lipofectamine® 2000 Reagent (Thermo Fisher Scientific, Waltham, MA, USA) following the manufacturer’s instructions. Briefly, 0.16 µL/well Lipofectamine® 2000 Reagent and 1.0 µg/well mRNA were diluted in DMEM low glucose (Euroclone, Milan, Italy), incubated for 5 min at room temperature and added to each well containing MCDB131 medium plus $10\%$ FBS. Treatment with only Lipofectamine® 2000 Reagent was used as the transfection control. After 24 h of treatment, cells were washed with PBS, fixed with ice-cold methanol:acetone (1:1), incubated at −20 °C for 10 min and air dried. Then, wells were blocked with PBS with $1\%$ bovine serum albumin (BSA, Sigma-Aldrich, Merck, Darmstadt, Germany) for 30 min at 37 °C, and after washing, were incubated with anti-N-protein rabbit antibody (1:250, PA1-41098, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) or anti-S1-protein mouse antibody (1:100, MA5-38033, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) for 1 h at RT. After three washes with PBS, samples were incubated with anti-mouse (1:1000, green, A32723, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) or anti-rabbit (1:1000, red, A32740, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) fluorescent antibodies for 1 h at room temperature, protected from light. After three washes with PBS, samples were incubated with DAPI at 300 nM (Thermo Fisher Scientific, Waltham, MA, USA) for 10 min at room temperature, protected from light. Then, samples were washed three times with PBS and air-dried. One drop of Fluormount Aqueous Mounting Media (Sigma Aldrich, Merck, Darmstadt, Germany) was added to each spot and the glass was covered with a coverslip. Images were acquired with the confocal microscope Axiovert 200M equipped with LSM5 Pascal and analyzed with LSM image browser (Zeiss, Oberkochen, Germany). Data were obtained from three independent experiments. ## 2.10. Cytofluorometric Analysis of oEV-GFP GFP translation after oEV-mediated delivery was evaluated after 24 h of treatment of HMEC-1 was plated at 30,000 cells/well in 24-well plates (Sarstedt, Milan, Italy) with medium (MCDB131), or medium plus oEVs (1 × 1010 oEVs/well), oEVs loaded with GFP mRNA (oEV-GFP) (1 × 1010 oEVs and 0.83 µg mRNA/well) (OZ Biosciences, Marseilles, France), GFP mRNA or GFP mRNA transfected with lipofectamine. Transfection was performed with Lipofectamine® 2000 Reagent (Thermo Fisher Scientific, Waltham, MA, USA) following the manufacturer’s instructions using 1.67 µg/well mRNA. After 24 h, cells were harvested and analyzed. oEV uptake and GFP delivery were also investigated after RNase and SGF stress. For that purpose, oEVs were previously stained with 1:100 diluted PKH26 fluorescent dye (Sigma-Aldrich, Thermo Fisher Scientific, Waltham, MA, USA) for 30 min at 37 °C and washed by ultracentrifugation at 100,000× g for 2 h at +4 °C (SW 90 Ti rotor, Beckman Coulter Optima L-90 K ultracentrifuge, polycarbonate tubes, Beckman Coulter, Milan, Italy). Stained oEVs were loaded with GFP mRNA (oEV-GFP). oEVs (1.2 × 1010 oEVs/well), oEV-GFP (1.2 × 1010 oEVs and 0.5 µg mRNA/well) and 0.5 µg of free GFP mRNA were subjected to incubation with RNase and SGF and used to treat 20,000 cells/well NHDF in 24-well plates (Sarstedt, Milan, Italy). mRNA was transfected using Lipofectamine® 2000 Reagent (Thermo Fisher Scientific, Waltham, MA, USA) following the manufacturer’s instructions. Data for each mRNA were obtained from three independent experiments. Analysis was performed with CytoFLEX (Beckman Coulter, Milan, Italy) and CytExpert software (v 2.3.0.84, Beckman Coulter, Milan, Italy). Data were obtained from three independent experiments. ## 2.11. Lymphocytes’ Activation In Vitro Human macrophages plated in 24 well-plates (Sarstedt, Milan, Italy) at a density of 20,000 cells/well were co-incubated with several stimuli: medium (RPMI with $10\%$ FBS), medium plus oEV, oEV-S1, oEV-FS or oEV-N (1.2 × 1010 oEVs and 1 µg /well of mRNA), 2 µg/mL S protein and N protein of SARS-CoV-2 (RP-87706 and RP-87665, Thermo Fisher Scientific, Waltham, MA, USA) and activation beads at 10 µL/well (Dynabeads® Human T-Activator CD3/CD28, Life Technologies, Thermo Fisher Scientific, Waltham, MA, USA). After 5 h, 200,000 PBMC were added to each well, and stimulation with treatments was repeated after 5 days. On day 10 of the experiment, cells were harvested and analyzed. For cell proliferation analysis, PBMC were labeled with CellTrace™ CFSE dye (Thermo Fisher Scientific, Waltham, MA, USA) following the manufacturer’s instructions before incubation with macrophages. At the experiment endpoint, cells were collected and stained with CD4-APC antibody (1:50, 130-113-222, Miltenyi Biotec, Bologna, Italy) using an appropriate isotype. For marker expression, cells were harvested and stained with CD4-FITC (1:50, MHCD0401, CALTAG Laboratories, Burlingame, CA, USA), CD25-APC-Vio®770, CD69-APC-Vio®770 or HLADR-APC-Vio®770 (1:100, 130-123-469, 130-112-616, 130-111-792, Miltenyi Biotec, Bologna, Italy) with appropriate isotypes. Antibody staining was performed for 30 min and washed by centrifugation at 500× g for 10 min. Analysis was performed with CytoFLEX (Beckman Coulter, Milan, Italy) and CytExpert software (v 2.3.0.84, Beckman Coulter, Milan, Italy). Data were obtained from three independent experiments. ## 2.12. Mice Immunization and Sacrifice The study was conducted according to the National Institute of Health Guidelines for the Care and Use of Laboratory Animals, and approved by the Ethics Committee of the University of Turin and the Italian Ministry of Health (authorization number $\frac{514}{2021}$-PR, approved on 12 July 2021). Female BALB/cAnNCrl mice of 6–8 weeks old were purchased from the Department of Molecular Biotechnology and Health Sciences, University of Turin. Behavior and health status were observed daily and weight checked weekly. Immunization was performed by administering empty oEVs and mRNA-loaded oEVs (oEV-S1 or oEV-FS) via intramuscular (IM), oral and intranasal (IN) routes. For IM and IN administration, animals received one immunization (equivalent to 7.2 × 1011 oEVs containing 60 µg mRNA in 100 µL for IM or 40 µL for IN route of saline solution for each dose) at day 0 and one booster immunization after 3 weeks. For intramuscular administration, treatments were injected into the same hind leg for both doses, whereas for intranasal administration, the dose was pipetted into mice’s nostrils. For oral administration, animals received one immunization (equivalent to 1.2 × 1012 oEVs containing 100 µg mRNA in 150 µL of a solution of $1\%$ chitosan for each dose) at day 0 using gavage needle and three booster immunizations after 3 weeks on consecutive days. Mice were euthanized after 2 weeks from the last booster immunization. The group named oEV-S1 received immunization with S1 mRNA ($$n = 6$$ for IM, $$n = 7$$ for IN and $$n = 9$$ for oral), whereas the group named oEV ($$n = 5$$ for IM, $$n = 7$$ for IN and $$n = 6$$ for oral) received an equivalent dose of unloaded oEV as a negative control. The group named oEV-FS received immunization with FS mRNA ($$n = 6$$ for IM, $$n = 3$$ for IN, and $$n = 2$$ for oral), whereas the group named oEV ($$n = 6$$ for IM, $$n = 4$$ for IN and $$n = 3$$ for oral) received an equivalent dose of unloaded oEV as a negative control. Immediately after sacrifice, spleens were collected in HBSS (Thermo Scientific, Waltham, MA, USA) and processed for cell isolation. Blood was collected and centrifuged at 3.000× g for 20 min to obtain serum. Sera were stored at −20 °C until use. The bronchoalveolar lavage (BAL) fluid was collected from mice immunized with oEV ($$n = 2$$) or oEV-S1 ($$n = 3$$) and stored at −20 °C until use. Muscle and intestine morphology was evaluated through formalin-fixed paraffin-embedded tissue staining. Paraffin tissue sections (5 µm thick) were routinely stained for microscopic evaluation with H&E (Merck, Darmstadt, Germany) and photographed with an Axioskop microscope (Zeiss, Oberkochen, Germany) equipped with a Canon DS126181 camera (Canon, Tokyo, Japan). ## 2.13. Antibody Titer Analysis Specific IgG, IgM, and IgA antibodies against the S protein of SARS-CoV-2 virus in mice serum or BAL samples were detected through enzyme-linked immunosorbent assay (ELISA). For that purpose, Nunc Maxisorp ELISA plates (Thermo Fisher Scientific, Waltham, MA, USA) were coated overnight at 4 °C with 100 µL/well of 1 µg/mL SARS-CoV-2 S1 RBD recombinant protein (RP-87706, Thermo Fisher Scientific, Waltham, MA, USA) diluted in BupH carbonate–bicarbonate buffer (Thermo Scientific, Waltham, MA, USA). After three washes with PBS 1X, plates were blocked with 200 µL/well of PBS 1X–$3\%$ bovine serum albumin (BSA, Sigma Aldrich, Merck, Darmstadt, Germany) for 1 h at 37 °C. After five washes with PBS 1X—$0.05\%$ Tween20 (Sigma Aldrich, Merck, Darmstadt, Germany), plates were incubated with 100 µL/well of different serial dilutions of samples in duplicate (starting from dilution 1:100). Dilution buffer was also used as a blank: PBS 1X–$0.05\%$ Tween20–$3\%$ BSA for IgG, PBS 1X–$3\%$ BSA–$5\%$ FBS for IgM and PBS 1X–$0.05\%$ Tween20–$3\%$ BSA–$5\%$ FBS for IgA. Plates were incubated for 1 h at 37 °C for IgG, 2 h at room temperature for IgA or overnight at 4 °C for IgM. After five washes with PBS 1X–$0.05\%$ Tween20, 100 µL/well of secondary antibody was added: goat anti-mouse HRP IgG (1:10.000, 31430, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA), IgM (1:4.000, 62-6820, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) or IgA (1:250, 8850450-88, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA). After 2 h incubation and five washes with PBS 1X–$0.05\%$ Tween20, 100 µL/well of Stabilized Chromogen (TMB, Life Technologies, Thermo Fisher Scientific, Waltham, MA, USA) was added and incubated for 15–30 min at room temperature. The reaction was stopped by adding 100 µL/well of ELISA Stop Solution (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA). The plates were read at 450 nm using a VICTOR® Nivo™ Plate Reader (PerkinElmer, Milan, Italy) and VICTOR® Nivo™ Control Software (v 4.0.7, PerkinElmer, Milan, Italy). End-point titers were calculated as the last dilution with an optical density ≥ 1.5 blank O.D. value or ≥ 2 blank O.D. value for IgA in BAL samples. Specificity was evaluated using a competition assay as the percentage of reduction in O.D. value of serum samples (diluted 1:100 for IgM, 1:1000 for IgG and IgA), either control or pre-incubated with 30 µg/mL of SARS-CoV-2 S1 RBD recombinant protein for 1 h at 37 °C. IgG sensibility was evaluated for the only mouse antibody anti-S protein available, IgG, using serial dilutions of SARS-CoV-2 Spike Protein (RBD) Monoclonal Antibody (MA5-38033, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) ranging from 10 to 0.1 ng/mL following IgG protocol. ## 2.14. Neutralizing Antibody Analysis A SARS-CoV-2 Neutralizing Antibody ELISA Kit (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) was used to detect the level of neutralizing antibodies against SARS-CoV-2 in mice serum following the manufacturer’s instructions. Briefly, serum samples were diluted 1:50 with Assay Buffer 1X, and pre-coated plates were washed one time with Wash Buffer 1X. Next, 100 µL of positive control, Assay Buffer 1X (used as a negative control) and pre-diluted serum sample were added to the appropriate wells in duplicate and incubated for 30 min at room temperature. Plates were washed three times and 100 µL of Biotin Conjugate Solution 1X was added to each well. After incubation at room temperature for 30 min, plates were washed three times and 100 µL/well of streptavidin–HRP conjugate solution was added. Then, plates were incubated for 15 min at room temperature and washed three times, and 100 µL/well of substrate solution was added and left for 15 min at room temperature. The reaction was stopped by adding 100 µL/well of Stop Solution and plates were read on a VICTOR® Nivo™ Plate Reader (PerkinElmer, Milan, Italy) using VICTOR® Nivo™ Control Software (v 4.0.7, PerkinElmer, Milan, Italy) at 450 nm, using 620 nm as the reference wavelength. The percentage of neutralization was calculated using the following formula: 1 − (absorbance of unknown sample/absorbance of negative control) × 100. ## 2.15. Splenocytes’ Isolation Mouse splenocytes were isolated from spleens freshly collected in HBSS (Thermo Fisher Scientific, Waltham, MA, USA). Spleens were disrupted and filtered through a 40 μm cell strainer (PluriSelect, Leipzig, Germany), diluted with PBS (Euroclone, Milan, Italy) and centrifuged at 500× g at 4 °C for 5 min. Each pellet was resuspended in 2 mL cold RBC lysis buffer 1X (Thermo Fisher Scientific, Waltham, MA, USA) and incubated on ice for 5 min to lyse red blood cells. The reaction was stopped with 10 mL ice-cold PBS and cells were pelleted at 400× g at 4 °C for 5 min and resuspended in RPMI 1640 supplemented with $10\%$ FBS. ## 2.16. IFN-γ Detection with ELISPOT Elispot plates (Merck Millipore, Darmstadt, Germany) were activated by adding 15 µL of $35\%$ ethanol to each well, washed twice with PBS, coated with mouse IFN-γ capture antibody (part of Mouse IFN-γ ELISPOT Pair, 551881, BD Bioscience, Eysins, Switzerland) and left overnight at +4 °C. Plates were blocked using RPMI 1640 with $10\%$ FBS for 2 h at room temperature. For each mouse, 3 × 106 fresh splenocytes were plated in each well and re-stimulated with 2 µg/mL S peptide (SARS-CoV-2 S1 RBD recombinant protein, RP-87706, ThermoFisher Scientific, Waltham, MA, USA). For each condition, three technical replicates were performed. Plates were incubated for 44 h at 37 °C with $5\%$ CO2. Cells were removed and plates were washed twice with deionized water and three times with washing buffer (ELISA wash buffer, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA). Next, they were incubated with mouse IFN-γ detection antibody for 2 h at room temperature. Then, plates were washed three times with washing buffer and incubated with streptavidin–HRP (557630, BD Bioscience, Eysins, Switzerland) for 1 h at room temperature. Following that, plates were washed four times with washing buffer and twice with PBS, then incubated with substrate solution (AEC substrate set, BD Bioscience, Eysins, Switzerland) for 15 min until spot development. The reaction was stopped by washing with sterile water, and plates were left to air-dry at room temperature in the dark until completely dry. Plate acquisition was performed using an ELISPOT plate reader with ImmunoSpot (S6 Macro M2, ImmunoSpot, Cleveland, OH, USA), and spot counting was performed automatically by ImmunoSpot Software version 7.0.21.0 (ImmunoSpot, Cleveland, OH, USA). ## 2.17. Cytokine ELISA Analysis Mouse splenocytes were stimulated with 1 µg/mL of S peptide (SARS-CoV-2 S1 RBD recombinant protein, RP-87706, ThermoFisher Scientific, Waltham, MA, USA), and the supernatant was collected after 24 h, then centrifuged at 1400× g × 10 min to remove debris. Quantitative detection of mouse IFN-γ, IL-2, IL-10 and IL-4 levels was performed using a Mouse Th1/Th2 Uncoated ELISA Kit (88-7711-44, Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s instructions. Briefly, 96-well plates (Corning, Glendale, AZ, USA) were coated with 100 µL/well of capture antibody overnight at 4 °C. After washing, plates were blocked with 200 µL/well of ELISA/ELISPOT Diluent 1X for 1 h at room temperature and washed once with Wash Buffer. Mouse IFN-γ, IL-2, IL-10 and IL-4 standards were reconstituted, and two-fold serial dilutions were performed to produce a standard curve for a total of eight points. Next, 100 µL of samples or ELISA/ELISPOT Diluent as the blank were added to the well in duplicate and incubated for 2 h at room temperature. After washing, 100 µL/well of detection antibody was incubated for 1 h at room temperature. Then, 100 µL/well of Streptavidin-HRP was incubated for 30 min at room temperature and washed five times with Wash Buffer. Following that, 100 µL/well of TMB Solution 1X was incubated for 15 min at room temperature. The reaction was stopped by adding 100 µL/well of Stop Solution and plates were read on a VICTOR® Nivo™ Plate Reader (PerkinElmer, Milan, Italy) using VICTOR® Nivo™ Control Software version 4.0.7 (PerkinElmer, Milan, Italy) at 450 nm, subtracting the 570 nm reference wavelength. Standards curves based on standard O.D. values were used to calculate the cytokine amount (pg/mL) for each sample. ## 2.18. Cytofluorometric Analysis of Splenocyte-Derived Immune Cells For ex vivo analysis, mouse splenocytes were stimulated with 1 µg/mL of S peptide (SARS-CoV-2 S1 RBD recombinant protein, RP-87706, ThermoFisher Scientific, Waltham, MA, USA). For marker expression, cells were harvested after 36 h and stained with Viobility Fixable Dye (Miltenyi, Bologna, Italy) and CD3ε-APC (1:50, 130-117-671), CD4-APC-Vio770 (1:50, 130-118-955), CD8-FITC (1:50, 130-122-720), CD69-PE (1:50, 30-115-460), CD3-FITC (1:50, 130-092-962), CD4-VioBlue (1:50, 130-123-208), CD25-PE (1:50, 130-120-696), CD8-FITC (1:50, 130-120-822), CD138-PE (1:50, 130-120-741), CD45R-FITC (1:50, 130-118-323) and appropriate isotypes for each fluorescence (Miltenyi, Bologna, Italy). After staining, cells were washed with PBS, centrifuged at 300× g for 10 min and resuspended in PBS for acquisition. For lymphocyte proliferation, cells were stained using a CellTrace™ CFSE cell proliferation kit (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) before peptide stimulation in vitro following the manufacturer’s instructions. Briefly, 1 × 106 splenocytes were incubated with 1 M CellTrace™ stock solution for 20 min at 37 °C and washed with RPMI 1640 supplemented with $10\%$ FBS. Cells were plated at 1 × 106 cells/mL and stimulated with 1 µg/mL of SARS-CoV-2 S1 RBD recombinant protein (RP-87706, Thermo Fisher Scientific, Waltham, MA, USA). After 5 days, cells were harvested and stained with CD4-APC-Vio770 antibody (1:50, 130-118-955, Miltenyi, Bologna, Italy) and an associated isotype. After staining, cells were washed with PBS, centrifuged at 300× g for 10 min and resuspended in PBS for acquisition with a CytoFLEX flow cytometer (Beckman Coulter, Milan, Italy) using CytExpert software (v2.3.0.84, Beckman Coulter, Milan, Italy). ## 2.19. Biodistribution Male BALB/cAnNCrl mice were treated with fluorescently labeled oEVs using the IN and oral routes. oEVs were stained using 10 µM of Vybrant™ DiD Cell-Labeling Solution (Thermo Fisher Scientific, Waltham, MA, USA). The same amount of dye (DiD) used for oEV staining was administered as a control to set the background. Treatment was performed with 2 × 1012 oEVs for oral or 1.5 × 1012 oEVs for IN administration in one single dose ($$n = 5$$ for stained DiD oEVs, $$n = 3$$ for DiD). After 18 h, mice were euthanized and single organs were collected and imaged using an IVIS 200 small animal imaging system (PerkinElmer, Milan, Italy) as previously described [26]. Briefly, the excitation filter was set at 640 nm and the emission filter at 700 nm. The same illumination settings, such as binning factor [4], exposure time (2 s), f/stop [2] and field of views, were used for acquiring all images. The fluorescence signal was normalized to photons per second per centimeter squared per steradian (p/sec/cm2/sr). Images were acquired and analyzed using Living Image 4.0 software (PerkinElmer, Milan, Italy). The background average photon emission was subtracted from images to normalize the signal. The fluorescence (p/sec/cm2/sr) was quantified in the region of interest (ROI) drawn freehand. Data were expressed as average radiance ± SD. ## 2.20. Statistical Analysis Data were analyzed using GraphPad Prism 6.0 Demo (GraphPad, San Diego, CA, USA). Statistical analyses of three or more groups of data were performed using ANOVA with Dunnett’s or Tukey’s multiple-comparisons test, as appropriate. A t-test was used to compare two groups of data. Values were expressed as their mean ± SD. Statistical significance was established at $p \leq 0.05$ (* $p \leq 0.05$, $p \leq 0.01$, * $p \leq 0.005$ and **** $p \leq 0.001$), whereas ns was used to define no statistical significance ($p \leq 0.05$). ## 3.1. Characterization of oEVs Loaded with SARS-CoV-2 mRNA To evaluate oEV delivery of mRNA-based vaccine, oEVs were loaded with different mRNA of SARS-CoV-2, coding for: N protein (N), full S protein (FS) and the subunit 1 of S protein (S1) (see Table 1). Morphology and size analysis by NTA showed that oEVs loaded with mRNA had a biodistribution profile similar to unloaded oEVs. A small increase in size was observed after mRNA loading (Figure 1A,C), with a mean size of 167 ± 10 nm for empty oEVs and 227 ± 24 nm for loaded oEVs. TEM analysis demonstrated an intact membrane of oEV loaded with mRNA, with a round morphology and an electron-dense core (Figure 1B,D) similar to empty oEVs. RNA loading was similar for all three mRNA sequences, showing a comparable increase in RNA ratio with respect to control oEVs (Figure 1E). qRT-PCR analysis demonstrated a statistically significant mRNA loading of oEVs (Figure 1F) with a mean mRNA encapsulation efficiency of 72 ± $11\%$ (Figure 1G) resulting in a loading capacity of 3.51 ± 1.09 ng/1011 oEVs (Figure 1H). Additional experiments with the mRNA coding for N protein showed that the co-incubation of oEVs and mRNA was less efficient than oEV loading (Figure S1A) and that the dose of mRNA loadable into oEVs could be increased up to 10 times in terms of total RNA (Figure S1B) and mRNA detected with qRT-PCR (Figure S1C). Taken together, these data demonstrated that oEVs were efficiently loaded with different mRNA molecules. ## 3.2. mRNA Loaded into oEVs Was Resistant to Stress The ability of oEVs to protect mRNA from degradation due to RNase and to simulated gastric fluids (SGF) was evaluated in vitro. RNases are enzymes present in all environmental surfaces and are the main enzymes responsible for RNA degradation (Figure 2A), whereas gastric fluids represent the major stress in the gastrointestinal tract (Figure 2B). The integrity of mRNAs loaded into oEVs and free mRNAs was evaluated after RNase or SGF treatment. As shown in Figure 2C,D, respectively, the RNA amount did not change when mRNA was incorporated into oEVs, whereas free mRNA was significantly reduced after RNase and SGF treatment. Moreover, the analysis of each specific mRNA using qRT-PCR revealed that oEVs protected the mRNA in a statistically significant manner in comparison to free mRNA, with a mean percentage of resistance to stress of 83.3 ± $5.5\%$ after RNase and 86.8 ± $28.0\%$ after SGF for mRNA loaded into oEVs in comparison to 11.9 ± $10.5\%$ after RNase and 54.8 ± $17.5\%$ after SGF for free mRNA (Figure 2E,F). Additional experiments with N mRNA demonstrated that the co-incubation (without engineering) of oEV and mRNA did not protect mRNA from degradation (Figure S1D), confirming the poorer efficiency of the co-incubation technique in oEV loading. The protection was conferred by loading inside oEVs because lipid membrane permeabilization with Triton X-100 reduced the resistance to RNase (Figure S1E,F). These data were also confirmed by PCR experiments showing the disappearance of the mRNA-specific band after RNase (Figure 2G) and SGF (Figure 2H) of free mRNA but not of mRNA loaded into oEVs. Taken together, these data showed that the encapsulation of mRNA into oEVs makes them resistant to degrading conditions, which normally reduce free RNA integrity. ## 3.3. mRNA Was Delivered to Target Cells by oEVs and Translated into Protein The effective mRNA delivery to target cells and the translation into protein were evaluated. oEV treatment did not reduce target cells’ viability, as shown in Figure S2A. oEVs engineered with all three SARS-CoV-2 mRNA were incubated with macrophages used as APC cells. After 24 h, the delivery of mRNA was analyzed using qRT-PCR technique, showing the incorporation of each specific mRNA in APC. Classical transfection with lipofectamine was used as a control (Figure 3A–C). The mRNA translation into protein was detected by cytofluorimetric analysis (Figure 3D–F) and confirmed by confocal microscopy (Figure 3G), showing the expression of N, S1 and FS proteins in APC when mRNAs were transferred by oEVs or transfected with lipofectamine as the control. Finally, the ability of oEVs to transfer a functional mRNA was confirmed by APC expression of GFP protein 24 h after incorporation of GFP mRNA containing oEVs (Figure 3H,I). Moreover, the uptake of oEVs by target cells and the subsequent GFP expression were preserved after treatment with RNase and SGF (Figure S2B,C). Together, these experiments demonstrated that oEVs delivered functional mRNA to target cells as it was translated into protein. ## 3.4. oEV-mRNA Activated Lymphocytes in an In Vitro Model mRNA-based vaccines imply that the mRNA incorporated into APC is translated into protein and then presented to immune cells, triggering an immune response. To evaluate these steps in vitro, APC cells were co-incubated with oEV-S1, oEV-FS and oEV-N and, after 5 h, PBMC was added. Five days later, APCs were restimulated with the same treatments, and cells were analyzed at day 10 to detect lymphocyte activation, using cytofluorimetric analysis (see treatment scheme in Figure 4A). The treatment with oEVs loaded with all three mRNAs (oEV-S1, oEV-FS and oEV-N) induced a statistically significant activation of lymphocyte CD4+ in comparison to untreated cells (NT) and cells treated with control oEVs. In particular, cell activation was detected as an increase in cell proliferation by CFSE staining (Figure 4B), and a higher expression of activation markers CD25 (Figure 4C), CD69 (Figure 4D) and HLADR (Figure 4E). As positive controls, cells were stimulated with S and N proteins of SARS-CoV-2 and T-Activator CD3/CD28 beads. In conclusion, these data showed the ability of oEVs loaded with specific mRNA to activate an immune response in an in vitro model. ## 3.5. Mice Immunization via Different Administration Routes Induced Immune Response To evaluate immunization in vivo, female balb/c mice were treated with oEV-S1 or empty oEV as the negative control, using intramuscular (IM), oral and intranasal (IN) administration as schematized in Figure 5A–C. IM and IN treatments were performed with a dose of 60 µg/mice and repeated after 3 weeks following the classical immunization scheme used for SARS-CoV-2 (Figure 5A,C) [29]. Since the gastrointestinal tract is highly dispersive for drugs, oral treatment was administered by gavage with a dose of 100 µg/mice, and the second administration was repeated for three consecutive days (Figure 5B). No treatments induced suffering in animals, with a weight increase similar to controls and the absence of histological alteration in tissue, suggesting a lack of toxicity (Figure S3). Moreover, the biodistribution following the oral and IN routes was assessed, confirming that oEVs targeted, respectively, the gastrointestinal and the respiratory tract (Figure S4). To assess the treatment immunogenicity, mice were sacrificed at the experiment timepoint and serum and splenocytes were collected to investigate immune stimulation. Serum SARS-CoV-2-specific antibody titer demonstrated that all three administration routes elicited significant production of specific IgM (Figure 5D–F) and IgG antibodies (Figure 5G–I) in mice immunized with oEV-S1 with respect to mice treated with the unloaded oEVs used as the negative control. Of note, only oral and IN, but not IM, administration elicited a mucosal immune response with the formation of IgA antibodies (Figure 5J–L). For IN administration, the SARS-CoV-2-specific IgA antibody response was also measured in bronchoalveolar lavage (BAL) fluid, showing the presence of specific secretory IgA antibodies following immunization with oEV-S1 (Figure 5M). All antibody assays (IgM, IgG and IgA) were tested for specificity, and the IgG antibody assay was also analyzed for its sensitivity (Figure S5). Additional investigations revealed that serum samples contained neutralizing antibodies specific for SARS-CoV-2 following all three administration routes (Figure 5N–P). Isolated splenocytes were stimulated with the SARS-CoV-2 S peptide ex vivo to investigate the cell-mediated immune response and verify the activation of Th1 (IFN-γ, IL-2) and Th2 (IL-10, -4). The immunization with oEV-S1 induced specific interferon γ (IFN-γ) secretion in comparison to the vehicle alone (oEV), detected using both ELISPOT assay (Figure 6A–C) and ELISA technique (Figure 6D–F). ELISA measurement of remaining cytokines demonstrated an increase in interleukin-2 (IL-2) in stimulated splenocytes collected by mice immunized with oEV-S1 with respect to oEVs (Figure 6G–I), whereas no enhancement of IL-10 was observed (Figure 6J–L) and IL-4 was not detected. These findings indicate that vaccination with oEV-S1 using all three administration routes (IM, oral and IN) stimulated cell-mediated immune activation, which is associated with a Th1 cytokine (IL-2 and IFN-γ) rather than Th2 response (IL-10, -4). Cytofluorimetric analysis of splenocytes upon stimulation with S peptide demonstrated a statistically significant increase in CD4+ lymphocytes following immunization with oEV-S1 in comparison to oEVs alone (Figure 7A), suggesting a specific immune cell activation. Additional investigations showed higher immune cell activation following oral and IN vaccination rather than IM administration. In fact, only mucosal routes (oral and IN), but not IM administration, were able to induce an increase in CD3+CD69+ (Figure 7B) with a higher presence of both CD3+CD4+ and CD3+CD8+ co-expressing CD69+ in mice treated with oEV-S1 in comparison to oEVs alone (Figure 7C,D). Moreover, only immunization with oral and IN routes, but not IM, significantly reduced the expression of regulatory T cell (T reg) CD3+CD25+ (Figure 7E) with a reduction in CD25+ expression in both CD3+CD4+ and CD3+CD8+ (Figure 7F,G). Notably, the presence of specific plasma cell CD138+CD45R− following treatment with oEV-S1 was also detectable after oral and IN but not after IM immunization (Figure 7H) [30]. In conclusion, these data demonstrated that all three administration routes activated a splenic immune cells response (CD4+) but only oral and intranasal immunization were able to induce a higher effect with an increase in specific plasma cells, an increase in CD69+ and reduction in CD25+ co-expression. In order to also demonstrate in vivo the versatility of oEVs as mRNA carriers, a small number of animals were immunized with oEVs loaded with the bigger mRNA tested during in vitro coding for FS (oEV-FS) and compared to oEVs alone using all three administration routes (IM, oral, and IN). Meanwhile, oEVs efficiently delivered mRNA in vivo, inducing a humoral response with SARS-CoV-2 specific antibody and neutralizing antibodies with all three administration routes (Figure S6). Immune cell stimulation was also confirmed by the increased IFN-γ secretion from splenocytes stimulated with peptide ex vivo (Figure S7). Meanwhile, a change in IL-10 secretion was not observed with oEV-FS in comparison to oEV alone and IL-4 was undetectable, confirming the predominant activation of a Th1 rather than Th2 response (Figure S7). Finally, the splenic immune cell activation was confirmed using FS mRNA, and an increase in CD4+ cell proliferation was induced using all three administration routes (Figure S7). Taken together, these data demonstrated that oEVs can efficiently deliver multiple SARS-CoV-2 mRNAs in vivo and immunize mice, inducing a specific humoral and cell-mediated immune response. ## 4. Discussion In the present study, we provide a proof of concept that plant-derived EVs may represent a versatile platform for mRNA-based vaccines. Plant-derived EVs are an extractive natural product that may have several advantages with respect to synthetic nanoparticles [31]. The natural membrane envelope facilitates their uptake from target cells, they are not cytotoxic and they protect nucleic acids from enzyme degradation and environmental stress conditions [20,21,22,23,24,25]. Here, we used EVs purified from orange (Citrus sinensis) juice, which were expected to lack toxicity and immunogenicity due to their edible source and oral-induced tolerance. Being a natural product, plant EVs can be purified using a simple extraction process that does not require expensive cell culture conditions, and their ability to transfer a great number of biomolecules makes them a good candidate for drug delivery [19,20,21,22,23,24]. As a prototype of an mRNA-based vaccine, to evaluate the efficacy of oEVs as a carrier, we selected mRNA coding for SARS-CoV-2 antigens. In the present study, we demonstrated that oEVs can be efficiently loaded with different mRNA molecules with sizes ranging from 670 to 3820 nt, with a similar encapsulation efficiency and without altering oEVs’ integrity. Previous studies on mammalian EVs have shown that membrane vesicles confer stability to nucleic acid from degradation and from low and high pH conditions [32,33,34]. Here, we demonstrated that mRNA carried by engineered oEVs was highly protected from degradation induced by treatment with RNase enzyme and simulated gastric fluid (SGF) in vitro. Importantly, mRNA conveyed by oEVs was efficiently delivered to target cells and translated into protein. In the target cell, the protein was functional and was able to be presented by APC cells and stimulate a lymphocyte response, detected as the increase in CD4+ proliferating cells and of CD69+, CD25+ and HLADR+ activated cells (Figure 4) [35,36]. These findings suggested the possible efficacy of oEVs as a carrier for mRNA-based vaccines and prompted us to test their effect in mice. In the vaccine field, the interest in EV-mediated antigen delivery is growing based on the observation that mammalian cells infected with viral pathogens release EVs containing viral constituents able to trigger an immune response [37]. Moreover, EVs carrying S protein have been detected in infected patients, and their potential role in inducing a humoral specific immune response has been suggested [38,39]. Interestingly, compared to soluble antigens, EV-associated antigens were shown to elicit a stronger cytotoxic CD8+ T response [18]. Mammalian cells engineered to express a S and N protein in EVs were shown to efficiently immunize mice after IM injections [16]. Here, we selected the well-studied mRNA coding for subunit S1 of SARS-CoV-2 and demonstrated that IM injection in mice elicited a humoral immune response with the production of specific IgM and IgG against S1 protein, the induction of neutralizing antibodies and a T cell immune response. Splenocytes stimulated with the S peptide exhibited a significant increase in CD4+ proliferating cells upon immunization with oEV-S1 with respect to oEV alone, suggesting that the oEV formulation enables general CD4+ cell activation. The same effect on the increase in CD4+ was also observed in other studies, for instance, Perex et al. [ 39] when using IN administration of a modified vaccinia virus Ankara (MVA)-based vaccine, and Corbett et al. [ 29] via IM immunization with mRNA-1273. In this study, immunization with oEV-S1 stimulated a cell-mediated immune response associated with a Th1 cytokine (IFN-γ, IL-2) rather than a Th2 response (IL-10, IL-4). In fact, we observed an increase in the secretion of IFN-γ and IL-2 from splenocytes stimulated with the S peptide, whereas no difference was detected for IL-10 and IL-4. These data are in accordance with other studies demonstrating the major activation of a Th1 response following vaccination with mRNA coding for the SARS-CoV-2 antigen. Corbett et al. [ 29] reported that mice vaccinated with mRNA-1273 elicited a predominant Th1 response, detected as production of cytokines IFN-γ, TNF and IL-2 by total CD4 T cells under ex vivo stimulation with SARS-CoV-2 peptide pools. In a study by Zhang et al. [ 39], the authors showed that splenocytes isolated from mice immunized with SARS-CoV-2 RBD and in vitro re-stimulated with peptide pools covering the SARS-CoV-2 RBD induced a Th1-biased response with a significant increase in IFN-γ and IL-2 secretion, but no differences for Th2 response (IL-6, IL-4) were observed [40]. Moreover, cytokine polarization analysis performed by Sahin et al. [ 41] on PBMC collected by patients vaccinated with BNT162b1 showed secretion of IFN-γ and IL-2 but most individuals failed to secrete IL-4 [41]. IL-10, instead, was associated with Th2 response in SARS patients [42] and with Th2 response upon vaccination [43]. Since more than $90\%$ of the immune system is located in the gastroenteric tract, we also vaccinated mice via the oral route. Oral immunization induced an effective humoral and cellular immune response, similar to IM administration, indicating efficient protection of mRNA carried by oEVs from gastric degradation in vivo. Indeed, plant EVs are good candidates for oral drug delivery due to their resistance to acidic and basic conditions and to efficient intestinal absorption [7,44,45]. Besides the oral route, another suitable site of administration is represented by the intranasal tract with the presence of many immune cell components able to trigger an immune response, such as macrophages and T- and B-lymphocytes [46]. Here, we observed that an intranasal administration of oEV formulation with S1 mRNA was able to trigger a humoral and cellular immune response similar to oral immunization. The intranasal route for EV-based vaccine was confirmed by a previous report using Salmonella typhimurium EV decorated with the Spike receptor-binding domain derived from mammalian cell culture. In this model, intranasal immunization of the golden Syrian hamster resulted in a high level of serum anti-Spike receptor-binding domain IgG as well as a mucosal response [17]. Wang et al. [ 47] showed that human lung-derived EVs conjugated with recombinant SARS-CoV-2 receptor-binding domain efficiently immunized mice and reduced inflammation after a challenge with live SARS-CoV-2 in hamsters. Of interest, both the oral and the intranasal vaccination not only stimulated the specific IgM and IgG antibody production but also the induction of a specific secretory IgA response, a critical component in the mucosal first barrier adaptive immune response [48]. This finding is consistent with the observation that strategies based on mucosal vaccination stimulate IgA secretion in the mucosa [49]. Hassan and colleagues previously showed that an intranasal dose of a chimpanzee adenovirus-vectored vaccine encoding a prefusion stabilized spike protein (ChAd-SARS-CoV-2-S) promoted systemic and mucosal IgA in mice and macaques [50,51,52]. The study of Popowski et al. [ 53] reported the vaccination by direct inhalation using nebulization of lyophilized EVs derived from lung or from conditioned medium of HEK 293T cell line previously engineered with the S protein mRNA via electroporation. When compared with liposomes, mRNA-loaded EVs elicited significantly higher production of specific IgG and secretory IgA antibodies, suggesting that EVs are superior to synthetic liposomes as carriers of mRNA-based vaccines [53]. As expected, the biodistribution of oEVs revealed different accumulations when using the intranasal or oral route, showing efficient mRNA delivery and mice immunization in both administration protocols. Although this did not apply to the intramuscular route, oral and intranasal immunization were shown to also induce increased cell-mediated immune activation. These data are consistent with a previous observation that mucosal vaccine administration can provide not only local but also systemic protection [49,54]. In this study, marker expression of peptide-stimulated splenocytes revealed that oral and IN immunization with oEV-S1 induced an increase in the lymphocyte activation marker CD69+ in comparison with oEV vaccination. We observed an increase in CD69+ expression on both total CD3+ and CD3+CD4+ and CD3+CD8+. This finding was supported by previous studies that reported the induction of CD8+CD69+ [55] and CD4+CD69+ [56] following vaccination against SARS-CoV-2 [57]. Here, oEV-S1 treatment via the oral and IN routes induced a significant reduction in CD3+, CD3+CD4+, and CD3+CD8+ co-expressing CD25+, a typical marker of regulatory T cell (T reg). CD25 (or the IL-2 receptor α-chain) is considered a key regulator of immune response since its high affinity to IL-2 induces IL-2 deprivation, promoting an important immunosuppressive activity that prevents harmful effects due to immune system hyperstimulation [58]. The inhibitory effects of Tregs on immune response induced post-vaccination have been experimentally demonstrated in different mice models of Treg depletion [58]. T reg depletion was proven to increase vaccine-derived protection in an influenza virus infection model [59] and induced a more durable antibody response to mRNA-COVID-19 vaccination in patients with plasma cell dyscrasia [60]. In this study, mice immunized with oEV-S1 via mucosal routes (oral and IN) also exhibited an increased number of splenic plasma cells in comparison to mice treated with oEV vehicle alone. A similar result was also reported by Gao et al. [ 61] as an increase in the ratio of CD19−CD138+ plasma cells in total lymphocytes derived from the spleen of mice immunized with RBD9.1 peptide. Finally, the versatility of oEVs to deliver different immunizing mRNAs was demonstrated using oEVs loaded with FS mRNA in a small number of animals, showing a similar immune response to vaccination with oEV-S1 using all three administration routes (IM, oral, and IN). ## 5. Conclusions In conclusion, we successfully demonstrated that EVs derived from edible plants can serve as a carrier for the therapeutic exploitation of nucleic acids. In fact, they confer protection from degradation and allow for efficient delivery to mammalian cells in vitro and in vivo. They may be suitable for the delivery not only of mRNA but also of other nucleic acid molecules, such as siRNA, miRNA, and DNA. In the present study, we demonstrated that mRNA from a viral protein can be loaded in orange-derived EVs, eliciting an immune response with antibody production and immune cell activation. We tested SARS-CoV-2 mRNAs as a proof of concept, but the cargo can be adjusted for targeting different pathogens, paving the way to several applications in the vaccine field. Among administration routes, oral and intranasal represent several advantages as needle-free techniques and were demonstrated to be superior to the IM route, also conferring IgA mucosal protection and increased splenic cell activation. Therefore, edible plant EVs may represent a platform for the delivery of different therapeutic molecules, especially for mucosal absorption. ## References 1. Ratajczak J., Wysoczynski M., Hayek F., Janowska-Wieczorek A., Ratajczak M.Z.. Membrane-derived microvesicles: Important and underappreciated mediators of cell-to-cell communication. Leukemia (2006) 20 1487-1495. 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--- title: Rapid and Efficient Optimization Method for a Genetic Transformation System of Medicinal Plants Erigeron breviscapus authors: - Yujun Zhao - Yifan Yu - Juan Guo - Yifeng Zhang - Luqi Huang journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10058539 doi: 10.3390/ijms24065611 license: CC BY 4.0 --- # Rapid and Efficient Optimization Method for a Genetic Transformation System of Medicinal Plants Erigeron breviscapus ## Abstract Erigeron breviscapus is an important medicinal plant with high medicinal and economic value. It is currently the best natural biological drug for the treatment of obliterative cerebrovascular disease and the sequela of cerebral hemorrhage. Therefore, to solve the contradiction between supply and demand, the study of genetic transformation of E. breviscapus is essential for targeted breeding. However, establishing an efficient genetic transformation system is a lengthy process. In this study, we established a rapid and efficient optimized protocol for genetic transformation of E. breviscapus using the hybrid orthogonal method. The effect of different concentrations of selection pressure (Hygromycin B) on callus induction and the optimal pre-culture time of 7 days were demonstrated. The optimal transformation conditions were as follows: precipitant agents MgCl2 + PEG, target tissue distance 9 cm, helium pressure 650 psi, bombardment once, plasmid DNA concentration 1.0 μg·μL−1, and chamber vacuum pressure 27 mmHg. Integration of the desired genes was verified by amplifying 1.02 kb of htp gene from the T0 transgenic line. Genetic transformation of E. breviscapus was carried out by particle bombardment under the optimized conditions, and a stable transformation efficiency of $36.7\%$ was achieved. This method will also contribute to improving the genetic transformation rate of other medicinal plants. ## 1. Introduction Erigeron breviscapus (Vant.) Hand-Mazz is a perennial herbaceous plant in the Asteraceae family. This plant is distributed in Hunan, Guangxi, Guizhou, Sichuan, Yunnan, and Tibet provinces in China. It can only be seen in some open slope grasslands and forest margins at altitudes of 1200–3500 m [1] and has been listed as a nationally protected species of traditional Chinese medicine. The chemical components in E. breviscapus mainly include flavonoids, caffeoyls, coumarins, lignans, terpenoids, and other components [2], among which scutellarin has the highest content. Studies have shown that scutellarin can reduce neuronal damage caused by traumatic brain injury, cerebral ischemia, reperfusion injury and hypoxic-ischemic brain injury [3,4,5], and is commonly used to treat acute cerebral infarction in elderly patients [6] and is also effective in patients with diabetic nephropathy [7,8]. Another active ingredient is caffeoylquinic acids (CQAs), which can dilate blood vessels and inhibit thrombosis in vivo [9]. E. breviscapus is currently the best natural biological medicine for the treatment of obliterative cerebrovascular diseases and the sequela of cerebral hemorrhage, with an efficiency of >$95\%$ and slight side effects. According to the World Health Organization, the number of deaths from cardiovascular diseases will increase to 23.6 million by 2030 [10]. Therefore, E. breviscapus is of great significance for recovery and secondary prevention after the first onset of cardiovascular and cerebrovascular diseases. In addition, E. breviscapus is a natural neuroprotective agent for Alzheimer’s disease [1]. At present, according to different doses and routes of administration of E. breviscapus extract, various dosage forms have been developed, such as tablets, capsules, oral liquids, and injections, and international research on E. breviscapus unilateral preparations has also begun. It is expected to become an internationally recognized botanical medicine after ginkgo biloba preparations. At present, scutellarin is mainly derived from extracts of E. breviscapus, but the cost of planting E. breviscapus remains high due to the limited cultivation area, low content of active ingredients, serious pests and diseases, and the degradation of germplasm variation. A yeast cell factory for the total synthesis of scutellarin has been successfully constructed in the Saccharomyces cerevisiae chassis cells, and the total synthesis of scutellarin has been achieved, but it is still a certain distance from industrial production [11]. Therefore, urgent measures are needed to develop varieties with high content of active ingredients, high yield, and disease resistance to achieve sustainable utilization of resources. The development of genetic manipulation, DNA technology, and genetic transformation provides a reliable route for the development of transgenic medicinal plants that are tolerant to abiotic stress, resistant to pests, and have excellent agronomic traits [12]. Direct genetic transformation has become the method of choice for basic plant research and the primary technique for generating transgenic plants [13,14]. Therefore, the development of genetic transformation technology provides an opportunity to accelerate the various improvements of E. breviscapus. The two main methods of plant genetic transformation are Agrobacterium-mediated transformation and biolistic-mediated transformation [15,16]. Particle bombardment is simple to perform and is virtually unlimited in terms of plant ranges and material genotypes [17]. Various types of transformation receptors are suitable for large-sized genetic cargo [18]. Target genes can be introduced into the organelles of plant cells. Therefore, the biolistic-mediated transformation is widely used in the current transgenic research. Agrobacterium-mediated transformation is more efficient in dicots than in monocots and is limited to specific plant host ranges [15,19,20]. On the other hand, Agrobacterium-mediated transformation is generally considered to be more precise and controllable than particle bombardment; however, a report on bombardment strategies [13,21] showed little evidence of major differences in levels of transgene instability and silencing when compared in the same species as in other non-model systems. Both approaches have their advantages and limitations [22,23]. At present, regenerated plants of different explants of E. breviscapus, i.e., true leaves [24], petioles [25], and anther [26], have been successfully obtained and plant regeneration programs have been established. He et al. established an Agrobacterium-mediated transformation system and applied it to the functional verification of biosynthetic pathway genes [27]. Qiu screened suitable acceptor materials for gene gun induction [28]. In this study, the leaves of E. breviscapus were used as explants, and different particle bombardment parameters were optimized using an orthogonal design. After range analysis and variance analysis, the main influencing factors were identified, and the experimental effects were accurately and comprehensively evaluated to obtain the optimal transformation protocol. This is a successful attempt to directly transform E. breviscapus by gene transfer using the particle gun, which fully demonstrates the possibility of stable transformation of E. breviscapus. This study has long-term significance for the genetic engineering research of medicinal plants. ## 2.1. Selection Pressure In plant genetic transformation, the principle of using antibiotics is that they can effectively inhibit the growth, development, and differentiation of non-transformed cells or plants, but do not affect the normal growth of transformed cells or plants, or have little effect on transformed cells. Hygromycin B (Hyg) is widely used in many crops as an ideal screening reagent due to its high selection efficiency and small genotype differences. The induction results of different hygromycin treatments on E. breviscapus callus (Table 1) showed that callus induction frequency drastically decreased as the hygromycin concentration increased. After 2 weeks of culture, only very few calluses initiated from the cut edge on 2.5 mg·L−1 and 5.0 mg·L−1 Hyg. After 4 weeks of culture on medium containing 5 mg·L−1 Hyg, explants turned brown and were completely necrotic. Under 7.5 mg·L−1 Hyg, explants did not develop calluses. Therefore, 7.5 mg·L−1 was the lethal dose for leaf explants. Hyg significantly delayed and inhibited callus initiation and growth as the selection concentration increased. Thus, we used stepwise increasing concentration of Hyg from 2.5 mg·L−1 for 2~4 weeks post-transformation, and 5.0 mg·L−1 for 1–2 months in the callus selection and plant regeneration. ## 2.2. Pre-Culture Period The principle of single-variable experimentation was used to confirm the suitable pre-culture period. The results showed that pre-culture of leaf explants prior to bombardment could enhance transformation efficiency. The optimal pre-culture time was 7 d. For leaf explants, when the pre-culture time was 2–5 d, or more than 3 weeks, most of the explants decayed at the incision after particle gun bombardment, and then gradually died. When the pre-culture time exceeded 7 d, the transformation efficiency did not increase, although more resistant calluses could be produced (Table 2). Therefore, the optimal pre-culture time established in this study was 7 d. ## 2.3. Transformation Conditions In this study, a hybrid orthogonal experiment was adopted to confirm the optimal transformation conditions (Table 3). The particle gun transformation conditions were optimized using one two-level factor (precipitation agents) and five three-level factors (target tissue distance, helium pressure, bombardment times, plasmid DNA concentration, and chamber vacuum pressure). The experimental procedure is shown in Figure 1. The number of transformed adventitious buds was used to assessed transformation efficiency. The results showed the differences of each parameter at different levels (Figure 2). Among them, the peak of the curve showed a significant level. Specifically: precipitation agent: MgCl2 + PEG (level 2), target tissue distance: 9 cm (level 3), helium pressure: 650 psi (level 1), number of bombardments: 3 times (level 3), plasmid DNA concentration: 1 μg·μL−1 (level 3), chamber vacuum pressure: 27 mmHg (level 2). The range value R’ is calculated by the formula (Materials and Methods 4.7). The value of R’ is used to determine the degree of influence of various factors on the conversion efficiency. The influence order of each parameter was as follows (Table 4): precipitation agents > target tissue distance > plasmid DNA concentration > number of bombardments > helium pressure > chamber vacuum pressure. Although the results of the range analysis are more intuitive, they cannot be used to distinguish the fluctuations caused by experimental conditions or experimental errors. However, analysis of variance can be used to compensate for the shortcomings of range analysis. The significance of the parameters was determined by the F-test. To confirm the significant differences between the six parameters, the variance analysis was performed (Table 5). The results showed that precipitant ($p \leq 0.05$), target tissue distance ($p \leq 0.01$), and plasmid DNA concentration ($p \leq 0.05$) had a significant effect on transformation efficiency. However, helium pressure, number of bombardments, and chamber vacuum pressure were not significant. Therefore, the optimal transformation conditions were determined as follows: target tissue distance 9 cm, precipitant MgCl2 + PEG, and plasmid DNA concentration 1.0 μg·μL−1. The remaining transformation conditions could be considered from the perspective of economy and operation, with one bombardment, helium pressure 650 psi, and chamber vacuum pressure 27 mmHg. ## 2.4. Selection and Plant Regeneration Transformed adventitious shoots were randomly selected 48 h after bombardment, and transient eGFP expression was detected by Laser Scanning Confocal Microscope (LSCM) (Figure 3a–c). The transformants were then transferred to callus induction medium (CIM; Murashige and Skoog (MS) + 1.0 mg·L−1 6-benzylaminopurine (6-BA) + 0.1 mg·L−1 1-naphthylacetic acid (NAA) + $3\%$ sucrose + $0.4\%$ phytagel) for 2 weeks and detected by LSCM. The presence of eGFP in the transgenic cells was confirmed by green fluorescent spots (Figure 3d,e). After callus formation, transformants were transferred to selection medium (CIM) containing 2.5 mg·L−1 Hyg for the first round of selection for 2 weeks (Figure 3g). The transformants were then transferred to a regeneration medium (RM; MS + 2.0 mg·L−1 6-BA + 0.2 mg·L−1 NAA + $3\%$ sucrose + $0.4\%$ phytagel, pH 5.8) containing 2.5 mg·L−1 Hyg for a second round of selection for 4 weeks (Figure 3h). For efficient selection, regenerated transformants were transferred to RM containing 5.0 mg·L−1 Hyg for a third round of selection for 6 weeks (Figure 3i). When selection was performed on RM containing Hyg, the non-transgenic tissues gradually turned brown while the presumed transformed tissues remained green and grew slowly (Figure 3g–i). The transformation efficiency was $36.7\%$. The transformation efficiency was calculated as the number of positive shoots that survived after the third round of selection relative to the total number of explants bombarded. After three subculture cycles, the transformed buds were transferred to a shoot elongation medium (SEM; $\frac{1}{2}$MS + 2.0 mg·L−1 6-BA + 0.2 mg·L−1 NAA + $3\%$ sucrose + $0.4\%$ phytagel, pH 5.8) for shoot elongation (Figure 3j,k). Finally, transformed rootless seedlings were transferred to a root induction medium (RIM; $\frac{1}{2}$MS + 0.3 mg·L−1 NAA + 0.5 mg·L−1 indole-3-butyric acid (IBA) + $3\%$ sucrose + $0.4\%$ phytagel, pH 5.8) for further root formation for about 3 weeks (Figure 3l). ## 2.5. Identification of Transgenic E. breviscapus Plants Putative transgenic lines were obtained by multiple rounds of selection following bombardment of E. breviscapus leaf explants. These putative transgenic lines were identified by PCR amplification using the specific primers (Hyg-F/R) and all the products were sequenced by Sanger sequencing to verify the htp gene. The results showed the expected bands of 1026 bp fragment, confirming that the htp gene had been integrated into the genome of E. breviscapus, while the wild-type (WT) plant showed no PCR amplification bands (Figure 4). ## 3. Discussion One of the most effective methods for direct gene transfer is the particle bombardment method. Bacteria are not required during the transformation process. It is widely used and efficient in DNA transfer in mammalian cells, microbes, and monocots [29]. So far, particle bombardment has been used in many medicinal plants, i.e., Catharanthus roseus [30], Hypericum perforatum [31], Centella asiatica [32], Tripterygium wilfordii [33], Momordica charantia [34], Scoparia dulcis [35], etc. In this study, a simple and effective biolistic transformation method was established in E. breviscapus with a transformation efficiency of $36.7\%$. The use of orthogonal design can reduce the number of experiments and the complexity of experimental analysis methods, overcome the blindness in condition optimization, and improve work efficiency and experimental accuracy. The method of biolistic transformation of E. breviscapus was optimized by the hybrid orthogonal design. The main influencing factors were precipitation agents, target tissue distance, and plasmid DNA concentration. The optimum transformation conditions were precipitant agents MgCl2 + PEG, target tissue distance 9 cm, helium pressure 650 psi, bombardment once, plasmid DNA concentration 1.0 μg·μL−1, and chamber vacuum pressure 27 mmHg. At present, a universal optimization strategy (Figure 1) has been developed and applied to a variety of medicinal plants, including Erigeron breviscapus, Salvia miltiorrhiza, Tripterygium wilfordii [33], and Aconitum carmichaelii. The explants used include leaves, stems, suspension cells, and calluses. By optimizing the pre-incubation time, we found that 7–14 days of pre-cultivation was more conducive to the regeneration of explants after bombardment. However, shorter (2–5 d) or longer (21 d) pre-culture times were unfavorable to explants’ regeneration. The same conclusion was reached in the biolistic transformation of wheat-microspore-derived calluses and microspores. Pre-culture for 3–8 days could improve the GUS expression in microspores [36]. The results of optimization experiments of Fistulifera solaris showed that the highest conversion rate was achieved by pre-culturing for 48 h [37]. The above results indicated that the optimal pre-cultivation time varied with individual differences. Therefore, it is necessary to optimize the pre-culture time. The orientation of the plant tissue explants placed on the medium is another important factor affecting the efficiency of plant transformation and regeneration [38]. The abaxial orientation of the leaf implies that the lower surface of the leaf is in contact with the medium, while the adaxial position means that the upper surface of the leaf is in contact with the medium [39]. In our pretest study, we found that more adventitious buds were produced during the regeneration stage when the abaxial side of the leaf was exposed to the medium than the adaxial side. Mazumdar et al. reported that the regeneration efficiency of the abaxial end of explants exposed to the medium was twice as high as that of the adaxial end [40]. Similarly, tomatoes of two different genotypes exhibited higher regeneration efficiency and higher shoot numbers per explant when placed abaxially than when exposed to medium in the adaxial direction [41], as confirmed in earlier studies [42,43]. The PEG/Mg2+ coating protocol in this study showed better stabilization of the transformation than the standard Spd/Ca2+ method. Due to the hygroscopicity, oxidizable nature, and deamination over time of spermidine (Spd) solutions, frozen aliquots should be replaced for fresh at least monthly [44]. Stock solutions of CaCl2 and Spd must be used separately, whereas PEG and MgCl2 can be prepared conveniently as a single stock solution that is stable for many years when stored at −20 °C. The PEG/Mg2+ procedure has been successfully applied to wheat for stable transformation [45]. The distance from the microcarrier to the target tissues can affect the velocity of the microparticles and thus the frequency of transformation [46]. As in previous studies, a target tissue distance of 9 cm was reported as the optimal propagation distance for bananas [47], wheat [48], and cumin [49]. We found that a target tissue distance of 9 cm was a significant factor in improving transformation frequency. This distance can reduce damage to a great extent and ensure the distribution of DNA microcarriers on target tissues [50]. Similar to Jähne et al., we found that changing the helium pressure in the range of 1100–1350 psi had no significant effect on the number of positive shoots [51]. In contrast to the results of this study, Jähne et al. found that lower (450–900 psi) or higher (2000–2200 psi) pressures reduced the frequency of transformation. When Harwood et al. used barley microspores pre-incubated for 1–4 days, they found that a lower pressure of 450 psi increased the number of GUS-positive microspores [52]. We also found that lower bombardment pressures increased the number of positive shoots. When Mentewab et al. compared the effect of using 650 psi or 1100 psi pressure, transient expression of microspores in culture for 1 day was observed only after using low pressure, while multicellular structures of 8 days were only observed when high pressure was applied [53]. It was demonstrated that the optimal helium burst pressure may depend on several factors related to the cell wall properties and the damaging effect of the treatment. Comparing the number of surviving shoots, an overall optimal parameter was observed, i.e., precipitant agents MgCl2 + PEG, target tissue distance 9 cm, helium pressure 650 psi, bombardment once, plasmid DNA concentration 1.0 μg·μL−1, and chamber vacuum pressure 27 mmHg. In this study, the frequency of transformation obtained by biolistic transformation was $36.7\%$. The transformation efficiency of E. breviscapus was not reported for either Agrobacterium-mediated or particle bombardment transformation (three adventitious shoots were obtained). The higher transformation efficiency of the particle gun bombardment may be due to the attempted use of the hybrid orthogonal methods. Optimization strategies are highly efficient compared to the previous single-variable method, thus potentially facilitating genetic modification for improved traits. ## 4.1. Plant Material and Culture Conditions Seeds of E. breviscapus were manually rubbed to remove their pappus, and the plump and undamaged seeds were selected for the experiment. Before inoculation, seeds were soaked for 4 h, dried for 3 h, and then sterilized. Under sterile conditions, seeds were soaked in $75\%$ (v/v) ethanol for 8~10 s and washed 3~4 times with sterile water. After that, they were sterilized with $2.5\%$ (v/v) NaClO for 8~10 min and rinsed with sterile water. Seeds were inoculated on Murashige and Skoog (MS) medium [54] hormone-free medium and cultured at 25 °C, 16 h/d light conditions of 4000 lx to obtain sterile seedlings. ## 4.2. Optimization of Explant Pre-Culture Time Ten leaf explants were placed on each plate containing callus induction medium (CIM; MS + 1.0 mg·L−1 6-BA + 0.1 mg·L−1 NAA + $3\%$ sucrose + $0.4\%$ phytagel, pH 5.8). A total of six conditions of 2 d, 3 d, 5 d, 7 d, 14 d, and 21 d were established in order to confirm the most suitable pre-culture time and the explants were incubated in the dark at 25 °C. After 4 h of osmotic treatment, the leaf explants were bombarded with the following parameters: 6 cm target distance, 27 mmHg, with 1100 psi rupture disks. The optimal pre-incubation time was evaluated by the frequency of transformed shoots. The methods of bombardment are described in 4.4 and 4.5. ## 4.3. Selection Pressure of Leaf Explants to Hygromycin B The concentrations of Hyg were set at five levels of 0, 2.5, 5.0, 7.5, and 10.0 mg·L−1, and the medium was CIM. Leaf explants were placed abaxially and inoculated with each treatment and replicated three times. All the explants were cultured in light at 25 °C for 4 weeks and sub-cultured every 2 weeks. The critical concentration of Hyg was confirmed by counting the induction rate of resistant callus. ## 4.4. Preparation of Gold Microprojectile Plasmid PBI-1300 (provided by Pro. Meng Wang, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences) was isolated using the plasmid maxi kit (Omega, United States) according to the manufacturer’s protocol. Transformation conditions were confirmed by plasmid PBI-1300, which harbors the eGFP reporter gene and the hpt selectable gene, both driven by the cauliflower mosaic virus (CaMV) 35S promoter. The gold particles must be sterilized before being used for DNA coating. An amount of 30 mg of 1.0 μm gold particles were added with 1 mL of $100\%$ ice-cold ethanol and sonicated for 15 s, and were centrifuged at 3000 rpm for 60 s. The supernatant was carefully discarded and the gold particles were resuspended with 1 mL ice-cold ddH2O. The gold particles were centrifuged at 3000 rpm for 60 s and supernatant was removed. The washing step of ddH2O was repeated twice. Finally, the gold particles were suspended with 500 µL of $50\%$ (v/v) sterile glycerin with a final concentration of 60 mg·mL−1. The above microcarriers were stored at −20 °C before use. The DNA/gold-coating method consists of two levels of optimization (Table 1). The first method is based on Bio-Rad protocol. An amount of 5 μL DNA (1 μg·μL−1), 50 μL CaCl2 (2.5 M), and 20μL Spd (0.1 M) were added to 50 uL microparticle solution, and the mixture was vortexed for 2~3 min and left to stand for 1 min. The supernatant was discarded after centrifugation. The particles were washed with 140 μL of $70\%$ ethanol and absolute ethanol. Finally, the pelleted DNA was suspended with 48 μL of absolute ethanol. The second method corresponded to the previous method [45]. An amount of 50 μL of gold particles was coated with 10 μL of DNA (1 μg·μL−1) and supplemented with 10 µL of PM solution ($42\%$ PEG 2000 and 560 mM MgCl2) under vortexing. The mixture was vortexed for 1 min and incubated for 20 min at room temperature. The suspension was centrifuged for 1~5 min. Then, the pelleted DNA was washed with 100 µL of $100\%$ ethanol and was resuspended in 60 µL of $100\%$ ethanol. ## 4.5. Microprojectile Bombardment The bombardments were performed with a particle gun (PDS 1000/He, Bio-Rad). The transformation conditions of the particle gun were optimized using one 2-level factor (precipitation agents) and five 3-level factors (target tissue distance, helium pressure, bombardment times, plasmid DNA concentration, and chamber vacuum pressure). These parameters and the levels of the variables studied are shown in Table 3. A hybrid orthogonal table L18(21 × 35) was designed according to the above six parameters and different levels of each parameter [55], as shown in Table 6, where A to F represent precipitation agents, target tissue distance, helium pressure, number of bombardments, plasmid DNA concentration, and chamber vacuum pressure. Each factor was repeated three times, and the whole set of experiments was repeated twice. ## 4.6. Selection and Regeneration of Transformed Plants The bombarded leaf explants were incubated in the dark at 25 °C for 10~16 h and then transferred to CIM. After 2 days, the transformed leaves were observed for expression of eGFP using Laser Scanning Confocal Microscope (LSM880NLO, Zeiss, German) under an excitation wavelength of 488 nm. The explants were then cut into small pieces of about 1 cm2, placed abaxially on fresh CIM, and cultured at 25 °C, 16 h/d light. After 2 weeks, the transformed cells were observed for the expression of eGFP through LSCM under an excitation wavelength of 488 nm. The explants were then placed abaxially on CIM containing 2.5 mg·L−1 Hyg. After three rounds of selection, the calluses were split into 3~5 pieces and transferred to the regeneration medium (RM; MS + 2.0 mg·L−1 6-BA + 0.2 mg·L−1 NAA + $3\%$ sucrose + $0.4\%$ phytagel, pH 5.8) and incubated at 25 °C under 16 h/d light conditions of 4000 lx. After 2 weeks, green shoots were transferred to shoot elongation medium (SEM; $\frac{1}{2}$MS + 2.0 mg·L−1 6-BA + 0.2 mg·L−1 NAA + $3\%$ sucrose + $0.4\%$ phytagel, pH 5.8). For rooting formation, adventitious buds were transferred to root induction medium (RIM; $\frac{1}{2}$MS + 0.3 mg·L−1 NAA + 0.5 mg·L−1 IBA + $3\%$ sucrose + $0.4\%$ phytagel, pH 5.8). ## 4.7. PCR Analysis The genomic DNA of transformed plants was isolated using CTAB method [56]. PCR analysis was performed with hpt (selection maker gene)-specific primers (F: 5′-ATGAAAAAGCCTGAACTCACCG-3′; R: 5′-CTATTTCTTTGCCCTCGGACG-3′) to confirm the transformed strain. The denaturation temperatures used were 98 °C for 30 s, then 35 cycles for amplification with denaturation at 98 °C for 10 s, annealing at 60 °C for 30 s, extension at 72 °C for 20 s, and final extension at 72 °C for 7 min. Then, all the PCR products were sequenced by Sanger sequencing. ## 4.8. Statistical Analysis The optimization experiment was repeated three times. The different levels of each experimental factor and the contribution rate of each factor were determined by range analysis and variance analysis. The statistical analysis of all data was calculated by formula. 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--- title: Drug-Utilization, Healthcare Facilities Accesses and Costs of the First Generation of JAK Inhibitors in Rheumatoid Arthritis authors: - Irma Convertino - Valentina Lorenzoni - Rosa Gini - Giuseppe Turchetti - Elisabetta Fini - Sabrina Giometto - Claudia Bartolini - Olga Paoletti - Sara Ferraro - Emiliano Cappello - Giulia Valdiserra - Marco Bonaso - Corrado Blandizzi - Marco Tuccori - Ersilia Lucenteforte journal: Pharmaceuticals year: 2023 pmcid: PMC10058541 doi: 10.3390/ph16030465 license: CC BY 4.0 --- # Drug-Utilization, Healthcare Facilities Accesses and Costs of the First Generation of JAK Inhibitors in Rheumatoid Arthritis ## Abstract This study is aimed at describing tofacitinib and baricitinib users by characterizing their prescription and healthcare histories, drug and healthcare utilization patterns, and direct costs from a healthcare system perspective. This retrospective cohort study was performed using Tuscan administrative healthcare databases, which selected two groups of Janus kinase inhibitors (JAKi) incident users (index date) from 1st January 2018 to 31 December 2019 and from 1 January 2018 to 30 June 2019. We included patients ≥18 years old, at least 10 years of data, and six months of follow-up. In the first analysis, we describe mean time, standard deviation (SD), from the first-ever disease-modifying antirheumatic drug (DMARD) to the JAKi, and costs of healthcare facilities and drugs in the 5 years preceding the index date. In the second analysis, we assessed Emergency Department (ED) accesses and hospitalizations for any causes, visits, and costs in the follow-up. In the first analysis, 363 incident JAKi users were included (mean age 61.5, SD 13.6; females $80.7\%$, baricitinib $78.5\%$, tofacitinib $21.5\%$). The time to the first JAKi was 7.2 years (SD 3.3). The mean costs from the fifth to the second year before JAKi increased from 4325 € (0; 24,265) to 5259 € (0; 41,630) per patient/year, driven by hospitalizations. We included 221 incident JAKi users in the second analysis. We observed 109 ED accesses, 39 hospitalizations, and 64 visits. Injury and poisoning ($18.3\%$) and skin ($13.8\%$) caused ED accesses, and cardiovascular ($69.2\%$) and musculoskeletal ($64.1\%$) caused hospitalizations. The mean costs were 4819 € (607.5; 50,493) per patient, mostly due to JAKi. In conclusion, the JAKi introduction in therapy occurred in compliance with RA guidelines and the increase in costs observed could be due to a possible selective prescription. ## 1. Introduction This paper is the extended version of the works presented as abstracts to the 37th International Conference on Pharmacoepidemiology and Therapeutic Risk Management (ICPE) Virtual, 23 August 2021 [1,2], and to the 20th International Society of Pharmacovigilance (ISoP) Annual Meeting “Integrated pharmacovigilance for safer patients” 8–10 November 2021 Muscat, Oman (Hybrid meeting) [3]. Rheumatoid arthritis (RA) is an immune-mediated inflammatory disease (IMID) characterized by progressive joint erosion and articular damage. Cytokines play a key role in the pathophysiology of RA, such as interleukin(IL)-1, tumor necrosis factor (TNF), and IL-6 [4]. These cytokines, designated by scientific research as pharmacological targets, have led to therapeutic approaches with different degree of effectiveness. Type I/II receptors are responsible for binding to these cytokines, which carry out their action using the transduction pathway of Janus kinase (JAK) [5]. Therefore, the JAK represents an important pharmacological target—to achieve control of the pathologic response characterized by immune-based inflammation [6]. Two generations of JAK inhibitors (JAKi) were developed over time [6]. The first one includes drugs featuring by a non-selective inhibition of JAK subtypes [6,7], while the second involves drugs characterized by a selective inhibition of JAKs [6,8]. In Italy, the JAKi approved for the treatment of RA, classified as targeted synthetic disease-modifying antirheumatic drugs (tsDMARDs), were baricitinib and tofacitinib as regards the first generation, and filgotinib and upadacitinib for the second generation [9,10]. In this study, we focused on the first generation of JAKi approved for rheumatoid arthritis. In Italy, tofacitinib has been available since March 2017 [9], as tablets for oral administration in a dose of 5 mg/twice a day [11]. Data on its use are monitored continuously. In February 2021, the public access repository of adverse drug reactions (ADRs) of the Italian Medicines Agency (AIFA, report Reazioni Avverse dei Medicinali, RAM system) reported 171 suspected ADRs for tofacitinib [12]. The most reported ADRs has been observed for the System Organ Class (SOC) general disorders, followed by gastrointestinal complications and infections. On January 2020, the Pharmacovigilance Risk Assessment Committee (PRAC) of the European Medicines Agency (EMA) recommended using tofacitinib in patients older than 65 years old only when no alternative treatment was available due to the increased risk of serious infections, major adverse cardiovascular events, and malignancies [13,14,15]. Indeed, the post-marketing surveillance revealed these signals, particularly with the dosage of 10 mg bis per day [6]. Baricitinib was authorized in Italy in February 2017 [10] as 2 mg and 4 mg film-coated tablets [16]. Serious infections leading to hospitalization or death, including tuberculosis and bacterial, invasive fungal, viral, and other opportunistic infections, were recorded in clinical trials, in addition to high levels of low-density lipoproteins (LDL) cholesterol ($34\%$), upper respiratory infections ($15\%$), and nausea ($3\%$) [16]. In the AIFA—RAM system, 443 ADRs were recorded to be associated with baricitinib, of which the infections were predominates [12]. However, due to its subsequent availability on the market as compared with tofacitinib, baricitinib was initially less used but showed a safety profile in line with the ADRs listed on label [6]. The clinical recommendations for the treatment of RA depict the tsDMARDs as a second-line therapy following a therapeutic failure of the monotherapy with conventional synthetic (cs) DMARDs [17,18]. On the contrary, at the time of the first authorization of tsDMARD on the market, the RA clinical guidelines recommended their use after at least one biologic (b) DMARD [19]. In particular, rheumatologists have to check periodically whether progresses have been achieved in treated patients. The monitoring has to be performed quarterly for the evaluation of a reduction in disease activity until obtaining an in-target disease within 6 months. When a therapeutic strategy fails in the disease outcome, the swap to another drug class of DMARD is recommended, for instance, from a bDMARD to a tsDMARD [6,19]. A recent review on the RA pharmacotherapy showed how the research is working to move from an incurable to curable disease and in particular, this revealed that Italy is among the ten countries with the most prolific publications on the field. As regards the JAKi, the authors highlighted that despite their good safety profile, gastrointestinal, pulmonary, hematological, hepatic, and infective ADRs associated with a tsDMARD have been reported when JAKi was administered after a bDMARD [20]. This study (LEONARDO study) aimed at characterizing the incident RA users of JAKi in the immediate post-approval period (2018–2019). We described drug-utilization and accesses to the healthcare system services before and after the initiation of JAKi, also displaying the direct costs associated with these resources according to the perspective of the regional healthcare system (RHS). ## 2.1. First Analysis We identified 450 incident JAKi users in the inclusion period, and according to the exclusion criteria, the final cohort included 363 patients (Supplementary Material, Figure S1). The mean age of patients was 61.5 (standard deviation, SD = 13.6) years old, and females were $80.7\%$. We found $21.5\%$ and $78.5\%$ of incident tofacitinib and baricitinib users, respectively. In Table 1, the baseline characteristics and distribution of JAKi users are displayed. When the history of DMARD use was explored, we observed $8\%$ of incident JAKi users without previous prescription of any DMARD, and $79\%$ with a record of csDMARD supply. The most frequent csDMARD dispensed were hydroxychloroquine ($44\%$), methotrexate ($42\%$), and leflunomide ($33\%$). Among bDMARD users, patients with a history of anti-TNF were $60\%$, with most receiving etanercept and adalimumab, while patients with bDMARDs with an alternative mechanism of action (MOA) from TNF inhibitors were $41.9\%$, with most using abatacept and tocilizumab (Table S1). About $30\%$ of patients used the first JAKi as a second-line treatment (Table 2). The distribution of JAKi dispensations stratified by DMARD history is shown in Table S2. The mean time from the first ever DMARD and the first ever bDMARD to the JAKi use was 7.2 (SD 3.3) and 4.5 (SD 3.2) years, respectively. Table S3 shows details about the history of DMARD use according to years preceding the JAKi use. Table 3 displays the mean number of events per patient/year as regard emergency department (ED) accesses, hospitalizations, and RA visits, ranging between 0.45 and 0.62, 0.23 and 0.31, and 1.02 and 1.44, respectively. The overall direct healthcare costs from the RHS point of view varied from 1,551,981 € to 1,898,227 €. When the single item of costs was analyzed, we found that costs of hospitalizations ranged from 271,317 € in the 5th year before the cohort entry to 521,431 € in the 1st year before the cohort entry. These corresponded to a mean cost of hospitalization per patient/year of 747.4 € in the fifth year before the cohort entry and 1436.5 € in the first one (Table 4). ## 2.2. Second Analysis We identified 276 incident JAKi users and we included 220 patients in the final cohort (Figure S2). In Table 5, the distribution and baseline characteristics of the JAKi users are shown. As regards the healthcare service accesses in the first 6 months of JAKi utilization, we observed 109 ED admissions, 39 hospitalizations, and 64 RA visits. All baricitinib users have a RA visit ($$n = 38$$), while there were none for tofacitinib users (Table S4 and Table 6). Among 54 patients with at least one ED admission, 14 were males, 46 used baricitinib, and the mean time to the first ED admission was 73.5 days (SD 54.1) in the overall cohort. When hospitalizations were observed, we found that out of 28 patients with at least one hospitalization, nine were males, and six used tofacitinib. In the overall JAKi users, we observed 89.6 (SD 54.8) days to the first hospitalization. The most frequent causes of ED access associated with JAKi use were injury and poisoning (20 cases; $18.3\%$), diseases of the skin and subcutaneous tissue (15 cases; $13.8\%$), and circulatory disorders (12 cases; $11.0\%$) (Table S5). The reported hospitalizations were diseases of the circulatory system (27 cases; $69.2\%$), musculoskeletal and connective tissue disorders (25 cases; $64.1\%$), and disease of the skin and subcutaneous tissue (15 cases; $38.5\%$) (Table S6). Total direct costs were 1,054,530 €, including 887,946 € of drugs, 165,624 € of hospitalizations, and 960 € of RA visits. The corresponding mean cost per patient was 4793.3 € (607.5; 50,306), involving 4036.1 € (607.5; 8387.9) for drugs, 752.8 (0; 43,811) € for hospitalizations, and 4.4 (0; 60) € for RA visits (Table S7). ## 3. Discussion This descriptive exploration of baricitinib and tofacitinib utilization showed that these new drugs were used in accordance with labels [11,16] and clinical guideline recommendations [17]. In line with these, JAKi was used at least as a second-line treatment pharmacological approach when csDMARDs alone failed in controlling RA disease. In this study, overall, 334 patients ($92.0\%$) had a history of previous use of DMARDs and the JAKi use occurred as the second, third, or fourth line of treatment. Only 29 patients ($9.0\%$) had JAKi as the first prescription. We considered that JAKi could have been used in these patients as a first therapeutic choice, but at the same time, we hypothesized that these are patients who have acquired csDMARDs in a private regime or in other regions. In our study, females represent the majority the JAKi users, and this distribution reflects the women/men ratio reported in the medical literature for RA, about 3:1 [21]. In addition, we observed a higher number of baricitinib users than tofacitinib ones. This is explained by the different years of approval of these drugs: baricitinib obtained approval earlier than tofacitinib for co-payment purposes in the Italian healthcare system [22,23]. In the first analysis, the overall costs slightly increase due to the costs associated with hospitalizations that almost doubled over the years, while the other resources show similar costs over the years, as well as for the mean direct cost per patient/year that increases from the fifth to the second year preceding the cohort entry, in this case owing to the cost of hospitalizations. Taking into account the healthcare facilities used from the 5th to the 2nd year before the first JAKi dispensation, we observed an increasing trend over the years, but in the year before the JAKi introduction, the ED accesses and the RA visits decreased with the exception of the hospitalizations that remained constant. We can therefore speculate that the JAKi were prescribed preferentially to patients who had better clinical conditions in the year preceding the cohort entry, hypothesizing a selective prescription of JAKi in the first period of their approval. This phenomenon is known as selective prescription [24,25,26,27], and it can occur when clinicians prescribe drugs of new market introduction in two different situations. In the first, they prescribe to patients with a low burden of diseases, and in the second, they prescribe to those with no response to previous treatments. An example of the first option in RA was reported by a study conducted by Frisell T. et al., 2017 [24]. In this study, the authors evaluated bDMARDs utilization and compared anti-TNF with MOA users to assess whether patient characteristics could drive the choice of bDMARD in clinical practice. They highlighted that the anti-TNFs were prescribed to patients who were in better clinical conditions. Indeed, rituximab (a MOA drug) initiators were more often seropositive, had a long illness history, and had a slightly higher erythrocyte sedimentation rate (ESR) than anti-TNF users. Tocilizumab (another MOA bDMARD) initiators had more active disease with higher ESR and C-reactive protein (CRP) than anti-TNF patients did. Finally, compared with those who started anti-TNF, rituximab and abatacept (MOA drugs) initiators depleted more healthcare resources before treatment started [24]. As regards the second option, to the best of our knowledge no evidence was found in RA, but the selective prescription can be observed in the first years of any drug approved, and as for JAKi, another example can be seen in diabetes. Compared to the traditional oral antidiabetic drugs, sitagliptin was prescribed to older patients with comorbidities and no responders to previous treatments [25,26,27]. When the total direct costs from the fifth to the second year before the first JAKi prescription were assessed, we observed an increasing trend over the years. As regards the hospitalizations, we found an increase in the related costs with a constant number of these events in the year before the cohort entry. This could be explained by the occurrence of serious events requiring hospitalization that had affected these costs [28]. Noteworthily, since drug and visit costs decreased in the year before the cohort entry, this observation can confirm the hypothesis of a selective prescription. Harnett J. and colleagues in the United Stated also performed a cost assessment in the 12 months before and after tofacitinib initiation in RA patients. They found that the trend of mean medical costs decreased from the pre to post-index period [29]. However, the population, the observation period, and the different healthcare systems make these data highly different from ours. Another study, evaluating healthcare resources in a cohort of Colombian RA patients exposed to bDMARDs or tofacitinib and using claims data and electronic medical records, showed that the majority ($97.2\%$) of the direct costs were related to drugs [30], as occurred in our study, highlighting that the cost of drugs involved about $84\%$ of the overall direct costs. In the results of the second analysis measuring the first 6 months of JAKi use, we observed that baricitinib was the most frequent JAKi prescribed as compared tofacitinib, and that women were the gender most frequently reported. These characteristics were also found in the first analysis and were in line with the literature [21]. As regards the utilization of RHS services, we found differences between genders in the time to ED access and hospitalization, being longer in females than males, and in the distribution of hospital admissions (both ED and hospitalizations) being more frequent in males than females. When the type of JAKi was considered, a similar distribution in hospitalization was observed both for baricitinib and tofacitinib, while baricitinib users had a shorter time to first hospitalization than tofacitinib ones. The most frequent causes of ED accesses and hospitalizations were in line with the natural history of the disease or with the safety profile of the JAKi class. Among the most relevant events, cardiovascular ones deserve discussion. Indeed, although cardiovascular problems are known to represent a complication of RA, adverse events such as venous thromboembolism and deep vein thrombosis have also been reported for tofacitinib [17,31]. On February 2019, a Drug Safety Communication of the Food and Drug Administration (FDA) confirmed the presence of the cardiovascular risk associated with the intake of tofacitinib to a dosage of 10 mg in RA patients, as shown by a post-marketing safety clinical trial (A3921133) [12]. This study, assessing the safety profile including cardiovascular, oncological, and infectious impairments associated with the 5 mg and 10 mg BID of tofacitinib as compared with the anti-TNF drugs, highlighted an increased risk of blood clots in the lungs and death in RA patients with the higher dosage [32]. The revision of this study by the EMA, which also included results from earlier studies and consultations with experts, led to the recommendation of using tofacitinib with caution in patients that were high risk for events such as blood clots [13,15]. Preliminary results from a safety clinical trial demonstrated an increased risk of serious heart-related diseases and cancer with tofacitinib compared to TNF inhibitors [33]. However, these alleged side effects, which have had to be evaluated in long-term studies, overlap with RA cardiovascular complications, representing one of the most frequently reported complications [34]. Indeed, in the RA population, cardiovascular events are 1.5–2 times more frequent than those in the general population [35]. Therefore, it is difficult to make a distinction between JAKi side effects and RA complications, especially because in most patients JAKi is used as a second, third, or fourth-line treatment when the disease history is advanced, and the patients are already affected by comorbidities. However, the label of tofacitinib was updated for the risk of major cardiovascular problems and cancer in light of the results of this safety review performed by EMA [14,15]. The costs obtained in the second analysis, both total direct and stratified for a single item, are not comparable with those observed in the first one due to differences in the two populations. In the first 6 months of the use of JAKi, we found that few patients (about $20\%$) showed RHS facility use. Since out of 220 patients, only 28 had at least one hospitalization and 54 had an ED admission, the use of JAKi did not have a significant impact on the disease burden as regards the safety profile of patients. This could be due to a good response to therapy or to our hypothesis of the occurrence of the selective prescription of JAKi. Nevertheless, further assessments will be needed to confirm our findings by designating ad hoc studies when a longer follow-up and population will be available and the prescriptive habit will be strengthened. This study has some limitations. First, the use of healthcare administrative data makes it difficult to assess the causality of the observed causes of RHS admissions, as well as an association with drugs. Second, the causes of hospitalizations and ED admissions were not stratified for single JAKi, and therefore no safety conclusions could be pointed out for tofacitinib or baricitinib separately. Third, the ethnicity of patients was not evaluated, since information was not collected in these kinds of databases. Finally, as a point of strength, this is a descriptive study of what really happened soon after the approval of JAKi in Tuscan clinical practice. It is thus a picture of their use, and the related RHS facilities were provided. ## 4.1. Study Design and Data Source The LEONARDO study, EUPAS35746 [36], is a descriptive, population-based retrospective cohort study. We retrieved data recorded in the administrative healthcare databases of Tuscany. The population of Tuscany, with about 3 million inhabitants, benefits from the universal regional public health system, with a single payer, for which the facilities provided to patients at the regional level are collected in a uniform process from several clinical centers that provide facilities. Each center collects data according to a single regional protocol throughout the territory. For this purpose, we linked four different repositories: hospital discharge records (reporting the cause of hospitalizations coded by the International Classification of Diseases, 9th revision (ICD-9 codes), hospital admission date, discharge date, hospital stay costs); ED accesses (including diagnoses, ICD-9 codes, causing ED admission, ED admission date, and discharge date); drug supplies (Anatomical Therapeutic Chemical Classification System (ATC codes), drug supply date, doses, drug costs); specialist encounters (RA visits, date, and cost of visits). Information was linked and analyzed through an anonymous unique patient code. ## 4.2. Study Population We identified two different study cohorts. We selected two different time intervals for the two analyses because, in the first analysis, we characterized patients based on drug and healthcare utilization history, while in the second analysis, we assessed the outcomes in the follow-up. In the first analysis, the cohort entry was defined by the first supply of a JAKi recorded from 1 January 2018 to 31 December 2019. In the second analysis, the first dispensation of a JAKi was selected from 1 January 2018 to 31 December 2019. We included patients only when at least six months of follow-up was available. The date of the first JAKi supply identified the index date. In both groups, we excluded patients with less than 10 years of history data preceding the index date (look-back period), diagnosis of cancer, or anti-neoplastic drugs used in the look-back period, and young (≤18 years old) patients at the index date. Furthermore, patient observation was censored at the end of the follow-up or death, whichever came first. ## 4.3. Data Analysis In the first analysis, we described the distribution of the incident JAKi users in the study period and the DMARD supply history. We investigated the drug class (csDMARD and bDMARD) and the single drug (Table S8). We estimated the mean time from the first-ever csDMARD and the first-ever bDMARD supply to the first JAKi dispensation. Direct healthcare costs for JAKi users over the five-years preceding the cohort entry were calculated. Overall direct healthcare costs and costs associated with the different healthcare services (dispensed DMARDs, hospitalizations, and RA visits) were evaluated. In the second analysis, the distribution of ED admissions, hospitalizations, and RA visits (both overall and stratified by drug) were described in the follow-up. We estimated patients with at least one access to ED, hospitalization, and RA visit. In these patients, the mean time to the first ED admission, to the first hospitalization, and to the first RA visit (overall and stratified by type of JAKi and gender) was assessed. Finally, the most frequently reported causes for ED accesses and hospitalizations (the first cause reported in the discharge records) were described. Direct healthcare costs of incident JAKi users in the follow-up were estimated and stratified for dispensed DMARD, hospitalizations, and RA visits. ## 5. Conclusions In conclusion, our findings showed that in the first period of their market authorization, in Tuscany, the JAKi were used in accordance with the RA clinical guidelines and the utilization of healthcare services was similar between the two drugs. Rheumatologists adopted a selective prescription of JAKi to patients with better clinical conditions in the first period of the availability of these drugs. This study provides a real-world picture of the use of innovative drugs on an Italian population and allows for hypothesizing preferential prescriptive paths that should be studied in future ad hoc studies. The costs of these treatments should be monitored in relation to clinical outcomes in the future to confirm that an optimal cost-effectiveness profile exists. ## References 1. 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--- title: Cytotoxicity and Biomineralization Potential of Flavonoids Incorporated into PNVCL Hydrogels authors: - Gabriela Pacheco de Almeida Braga - Karina Sampaio Caiaffa - Rafaela Laruzo Rabelo - Vanessa Rodrigues dos Santos - Amanda Caselato Andolfatto Souza - Lucas da Silva Ribeiro - Emerson Rodrigues de Camargo - Anuradha Prakki - Cristiane Duque journal: Journal of Functional Biomaterials year: 2023 pmcid: PMC10058549 doi: 10.3390/jfb14030139 license: CC BY 4.0 --- # Cytotoxicity and Biomineralization Potential of Flavonoids Incorporated into PNVCL Hydrogels ## Abstract This study aimed to evaluate the effects of flavonoids incorporated into poly(N-vinylcaprolactam) (PNVCL) hydrogel on cell viability and mineralization markers of odontoblast-like cells. MDPC-23 cells were exposed to ampelopsin (AMP), isoquercitrin (ISO), rutin (RUT) and control calcium hydroxide (CH) for evaluation of cell viability, total protein (TP) production, alkaline phosphatase (ALP) activity and mineralized nodule deposition by colorimetric assays. Based on an initial screening, AMP and CH were loaded into PNVCL hydrogels and had their cytotoxicity and effect on mineralization markers determined. Cell viability was above $70\%$ when MDPC-23 cells were treated with AMP, ISO and RUT. AMP showed the highest ALP activity and mineralized nodule deposition. Extracts of PNVCL+AMP and PNVCL+CH in culture medium (at the dilutions of $\frac{1}{16}$ and $\frac{1}{32}$) did not affect cell viability and stimulated ALP activity and mineralized nodules’ deposition, which were statistically higher than the control in osteogenic medium. In conclusion, AMP and AMP-loaded PNVCL hydrogels were cytocompatible and able to induce bio-mineralization markers in odontoblast-cells. ## 1. Introduction The physiological process of apexogenesis, which consists of normal root development and closure of the apex mainly through the deposition of dentin by odontoblasts, can be interrupted in young permanent teeth by the occurrence of trauma or pulp necrosis. These teeth generally are treated with a conventional apexification procedure that induces the formation of a mineralized barrier in the apical region, which is based on frequent exchanges of calcium hydroxide (CH) [1]. This procedure induces root weakening and increases the susceptibility to root fracture [1,2], in addition to providing little or no benefit to the continuity of apicigenesis [3]. Another material used for apexification is mineral trioxide aggregate (MTA). MTA has demonstrated in vivo osteoinductive properties by inducing dynamic biomineralization processes in surgical bone defects [4]. The apical plug created in the most apical portion of the immature root with MTA can seal the communication between the root canal and the extra-radicular region, showing a greater advantage over frequent exchanges of CH [5]. However, this technique depends on the crown/root ratio, and it does not promote complete root development, leaving a risk of further root fracturing [5]. Currently, the American Association of Endodontics (AAE) has also recommended the regenerative endodontic procedure (REP) for endodontic treatment of young permanent teeth as an alternative to apexification [6]. REP consists of two sessions: [1] careful disinfection the root canal with sodium hypochlorite at low concentrations, and insertion of an antimicrobial medication, such as antibiotic pastes or calcium hydroxide pastes, for 2–3 weeks; and [2] reopening, blood clot induction, MTA/CH plugging and restoration [6] Although satisfactory clinical and radiographic results were observed, with most of cases exhibiting complete root development [6], histological evaluations of REP have shown the apposition of a connective tissue associated with cementum or bone, and no evidence of dentin deposition suggesting a tissue repair, so not true regeneration. [ 7] Considering the limitations of REP, new cell-based and cell-free approaches for regeneration of the pulp–dentin complex have arisen. In cell-based methods, allogenic stem cells (derived from the host) are seeded in scaffolds and inserted into root canals. A cell-free approach uses biomolecules in an attempt to stimulate biomineralization by the remaining cells or induce differentiation of endogenous stem cells [8]. This technique is simpler, lower cost and requires less training by clinicians than cell-based methods; however, there is not enough knowledge about which biomolecules could be applied for endodontic regeneration [8]. Several biomolecules have been screened for their potential in inducing differentiation, proliferation and mineralization biomarkers in odontogenic/osteogenic cells [9]. Flavonoids are polyphenolic compounds widely found in various fruits, vegetables, barks, stems, tea plants and derivatives. They are largely used in various sectors ranging from nutritional and pharmaceutical to medicinal and cosmetics [10]. Flavonols and derivates, such as dihydroflavonols and glycosylated flavonols, are groups of flavonoids known for their strong antimicrobial and antioxidant activity, and thereby their multiple benefits to human health [11,12]. Ampelopsin (AMP), also called dihydromyricetin, is a flavonoid extracted mainly from the leaves of Ampelopsis grossendata. Some studies have shown its biological and pharmacological properties, such as anti-inflammatory, antioxidant, anti-tumor, hepatoprotective, cardioprotective, neuroprotective, dermoprotective, insulin and cholesterol regulating and antimicrobial activities [13,14,15]. AMP also had effects on bone mesenchymal stem cells’ osteogenesis: increasing ALP activity, osteoblast-specific gene expression and mineral deposition [16]. Isoquercitrin (quercetin-3-O-glucoside) is a flavonoid glucoside found in plants, fruits and vegetables that has antioxidant, anti-inflammatory [17], anti-cancer [18] and antiviral [19] properties. Furthermore, it has been demonstrated to enhance the mineralization capacity of osteoblastic cells and to promote alkaline phosphatase activity [20,21]. Rutin is another glycosylated flavonol found in teas; fruits such as apples and tomatoes; and legumes such as onions, among others [22]. Rutin has also demonstrated antioxidant, anti-inflammatory and anticancer activities in some recent studies [23,24]. Studies observed the effects of rutin on cell proliferation and reported that it enhanced osteogenic differentiation and mineralization and reduced oxidative stress [25,26]. To improve their solubility, bioavailability and biological properties in a controlled-release manner in an attempt to eliminate residual bacteria, inflammation and the reparative process, flavonoids have been incorporated into drug-delivery vehicles, such as hydrogels [27,28]. The poly(n-vinylcaprolactam) (PNVCL) hydrogel is a thermoreversible hydrogel capable of transitioning from the liquid state to a gel when subjected to a temperature near the physiological human body temperature. It becomes a gel at approximately 34 °C and returns to its liquid form at lower temperatures [29,30]. It has shown great potential in the field of biomedicine as a controlled drug delivery system by being easily injectable and biocompatible, and by not producing toxic compounds and increasing the availability of drugs [29,30,31,32,33,34]. In endodontics, the search for a medication that can remain inside the root canal for long periods of time, eliminate the residual microorganisms and stimulate the remaining odontoblastic cells or progenitor cells of the apical papilla to continue root development is still a challenge [3]. In a recent study published by our research group, AMP-loaded PNVLC hydrogels demonstrated low cytotoxicity and an antimicrobial effect against bacteria related to endodontic infections [34]. Considering these previous findings, the present study aimed to evaluate the effects of flavonoids (ampelopsin, isoquercitrin and rutin) and an AMP-loaded PNVCL hydrogel on the viability and biomineralization potential of odontoblast-like cells, in the search for a potential injectable delivery system with multifunctional activities for application as an endodontic medication. The null hypothesis of this study was that there are no differences [1] among flavonoids and [2] among PNVCL hydrogels containing a flavonoid or not, or CH (as control), in terms of their cytotoxicity and mineralization potential. ## 2.1. Preparation of Compounds and Controls Ampelopsin (AMP, #42866), isoquercitrin (ISO, #17793) and rutin (RUT, #R5143 were dissolved in dimethyl sulfoxide (DMSO, Sigma-Aldrich, St. Louis, MO, USA) at 30 mg/mL and stored at −70 °C. Calcium hydroxide was dissolved in water at 1 mg/mL and stored at 4 °C. All compounds were obtained from Sigma-Aldrich (St. Louis, MO, USA). Cell culture medium was used as a negative control in this study. All experiments were performed in triplicate in three independent experiments ($$n = 9$$). ## 2.2. Synthesis and Characterization of PNVCL Hydrogels Thermosensitive PNVCL hydrogels were synthesized and characterized beforehand by 1H NMR, FITR and ultrastructural images [29,30,31,32,33,34]. Briefly, N-vinylcaprolactam monomer (NVCL) was dissolved in dimethyl sulfoxide (DMSO) and heated to 70 °C under a N2 atmosphere. Afterward, azobisisobutyronitrile dissolved in DMSO was added to the system and kept under agitation for 4 h. Finally, PNVCL was purified by dialysis for 4 days, dried at 50 °C and stored at 4 °C. For subsequent assays, PNVCL hydrogel was loaded with AMP at 2.5 mg/mL (7.8 mM, PNVCL+AMP) and CH at 1 mg/mL (13.5 mM, PNVCL+CH) separately and incubated for 24 h at 5 °C for total solubilization and preparation of a polymeric gel as previously described [34]. Rheological analysis and determination of compounds (AMP and CH) released from PNVCL hydrogels were recently published [34]. ## 2.3. MDP-23 Cell Culture The immortalized odontoblast-like cells (MDPC-23—mouse dental papilla cell line) were obtained from Prof. Dr. Carlos Alberto de Souza Costa (FOAr-UNESP, Araraquara, Brazil). They were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM; high low glucose, L-glutamine, and sodium pyruvate; Gibco, Grand Island, NY, USA) supplemented with $10\%$ fetal bovine serum (FBS; Gibco) and containing 100 IU/mL penicillin, 100 µg/mL streptomycin, 100 µg/mL gentamicin and 0.25 µg/mL amphotericin (Gibco) in a humidified incubator with $5\%$ CO2 and $95\%$ air at 37 °C (Isotemp Fisher Scientific, Pittsburgh, PA, USA). Cells were sub-cultured every 2 days until $80\%$ confluence was reached [35]. ## 2.4. Study Design The experimental design of the study is presented in Figure 1. For the first part of this study (Figure 1A), the samples were solutions of the following compounds: ampelopsin (AMP), isoquercitrin (ISO), rutin (RUT) and calcium hydroxide (CH, gold standard as medication in endodontics) at concentrations of 100, 50 and 25 µM. The control group was DMEM medium (no treatment). MDPC-23 were seeded (5 × 103 cells/well) onto sterile 96-well plates (T0), which were maintained at 37 °C for 48 h. Then, cells were treated with the compounds (T1) for 24 h (T2) and 48 h (T3) for cell viability determination [34,35]. For alkaline phosphatase (ALP) and mineralized nodules (MN) deposition assays, cells were seeded in 48 well plates (3 × 102 cells/well) and treated for 48 h with the compounds (T3). After that, DMEM was replaced by osteogenic DMEM (DMEM with FBS, antibiotics and supplemented with 50 μg/mL ascorbic acid, 10 nmol/L sodium β-glycerophosphate and 1.8 nmol/L KH2PO4, which was refreshed every 48 h until completion of the experimental period for ALP (8 days—T4) and MN deposition (14 days—T5) assays (Figure 1A). For the second part of this study (Figure 1B), the samples were serial dilutions of the PNVCL hydrogel extracts (PNVCL, PNVCL+AMP and PNVC+CH). One milliliter of each PNVCL hydrogel at the liquid state was inserted in 24-well plates and incubated overnight at 37 °C to acquire the gel state [34]. Then, 1 mL of DMEM was added over the hydrogels (T0) and incubated for 48 h (T1) and 7 days (T3) to obtain the hydrogel extracts. Cells were seeded (T2) and evaluated for cytotoxicity at 48 h (T4), 8 days (T5) and 14 days (T6); for ALP at 8 days (T5); and for MN deposition at 14 days (T6) (Figure 1B). All assays were performed in triplicate in three independent experiments [36]. ## 2.5. Cell Viability Assay The cell viability was evaluated using resazurin colorimetric assays at 48 h, 8 days and 14 days after treatments, according to previous studies [34,35,36,37]. Briefly, cells were seeded into 96-well plates (5 × 103 cells/well) and incubated for 48 h. For flavonoid screening, culture medium was aspirated and cells were treated with AMP, ISO and RUT at 100, 50 and 25 µM for 48 h under standard cell culture conditions. After incubation, treatments were aspirated, and cells were maintained in osteogenic DMEM (changed every 48 h) until completing 8 and 14 days. For hydrogels evaluation, 48 h and 7 days extracts (diluted from $\frac{1}{2}$ to $\frac{1}{64}$) of PNVCL, PNVCL+AMP and PNVCL+CH were applied to the cells, and they were incubated for 48 h. For the subsequent assays, cells were treated with the PNVCL extracts diluted at $\frac{1}{16}$ and $\frac{1}{32}$ for 48 h, followed by osteogenic DMEM changes until completing 8 and 14 days. After all these periods, cells were washed with sodium phosphate buffer (PBS, 10 mM, pH 6.8) and stained with resazurin (#7017, Sigma Aldrich) for 4 h. Absorbance values were read at each time point at 570 and 600 nm in a spectrophotometer (Biotek, Winooski, VT, USA). These values were converted into percentages of cell viability considering DMEM medium as $100\%$ of growth [34,35,36,37]. ## 2.5.1. Determination of Total Protein and Alkaline Phosphatase Activity MDPC-23 at 3 × 102 cells/well in 48-wells plates were treated with flavonoids (from 25 to 100 μM) or the PNVCL extracts (diluted at $\frac{1}{16}$ and $\frac{1}{32}$) for 48 h with subsequent osteogenic DMEM changing until completing 8 days. Total protein (TP) quantification and alkaline phosphatase activity (ALP) assays were conducted according to previous studies [35,36,37]. Briefly, cells were washed after aspiration of cell culture, and $0.1\%$ sodium lauryl sulfate (Sigma-Aldrich) was added to each well for 10 min to lyse cells. For TP determination, Lowry reagent (Sigma-Aldrich) was added to 100 μL of the lysed cells. They were then incubated for 20 min, which was followed by adding Folin–Ciocalteu’s phenol reagent (Sigma-Aldrich) for 30 min. Afterward, samples were read in a spectrophotometer at 655 nm. A standard curve of bovine serum albumin (BSA, Sigma-Aldrich) was used to determine the total protein of each sample in μg/mL. The alkaline phosphatase (ALP) assay was performed following the instructions of the ALP kit manufacturer (Labtest Diagnóstico S.A., Lagoa Santa, MG, Brazil). The cell lysate was mixed with thymolphthalein monophosphate and incubated for 15 min at 37 °C. After that, 2 mL of color reagent was added to each sample, which was then homogenized and had its absorbance measured at 590 nm. ALP activity was calculated based on a standard curve with known enzyme concentrations. The final ALP data (percentages in relation to the osteogenic DMEM control) were divided by the values of total protein (percentages in relation to the osteogenic DMEM control) to normalize the ALP results [35,36,37]. ## 2.5.2. Mineralized Nodule Deposition Mineralized nodule deposition was determined by the alizarin red staining method according to previous studies [35,36,37]. Briefly, MDPC-23 at 2 × 103 cells/well were treated with the flavonoids or the PNVCL extracts (diluted at $\frac{1}{16}$ and $\frac{1}{32}$) for 48 h, and osteogenic DMEM was changed until 14 days were complete. After that, cells were washed with PBS and fixed in $70\%$ cold ethanol for 2 h. After that, 40 mmol/L Alizarin Red S (Sigma-Aldrich) was applied to the cells for 20 min under gentle agitation. Then, cells were washed twice with distilled water and allowed to dry. Stained cultures were photographed using an inverted microscope (Olympus BX51; Olympus, Miami, FL, USA). After capturing the images, $10\%$ of cetylpyridinium chloride solution was added to the wells and left under agitation for 15 min. One-hundred microliters of each well was transferred to a microplate reader, and the absorbance values were obtained at 562 nm. The results were converted into percentages, considering the osteogenic DMEM control as $100\%$. The final mineralization nodule deposition data (percentages in relation to the osteogenic DMEM control) were divided by the values of cell viability obtained by the resazurin method (percentages in relation to the osteogenic DMEM control to normalize the results [35,36,37]. ## 2.6. Statistical Analysis Data from cytotoxicity assays, ALP activity and mineralized nodule deposition are expressed as mean ± standard deviation. After validating the homogeneity and homoscedasticity using Shapiro–Wilk and Leve tests, data were submitted to parametrical statistical methods: ANOVA (one or two-way) and post-hoc Tukey (for comparison among the groups) or Dunnett (for comparison between groups and control) tests. SPSS 19.0 software (SPSS Inc., Chicago, IL, USA) was used to run the statistical analysis, considering $p \leq 0.05.$ ## 3.1.1. Cell Viability Figure 2 shows the percentages of cell viability obtained by resazurin colorimetric assays after exposure of MDPC-23 odontoblastic-like cells to AMP, ISO and RUT at three different time points, 48 h, 8 days and 14 days, normalized by the positive control (DMEM). At all-time points and concentrations tested, cell viability was above $70\%$ when cells were treated with AMP, ISO or RUT. At 48 h, cell viability was dose-dependent only for RUT groups (Figure 2A). On day 8, there was no difference among the concentrations, considering each flavonoid separately (Figure 2B). After 14 days, ISO at 100 and 50 μM stimulated cell growth of 109 and $104\%$, respectively, and the growth statistically differed from that of AMP at 25 μM and RUT at 50 and 25 μM (Figure 2C). ## 3.1.2. Alkaline Phosphatase Activity Figure 3 shows means and standard deviations of ALP activity when MDPC-23 were exposed to flavonoids for 48 h and evaluated after 8 days. Among the flavonoids tested, AMP at 100 μM stimulated the greatest ALP activity: 1.85-fold more than the control. The activity level was different from what was stimulated by AMP at 50 μM and 25 μM (1.37- and 1.25-fold, respectively). ISO at 50 μM and RUT at 100 μM increased ALP activity 1.36- and 1.34-fold in MDCP-23 cells, compared to the control. CH increased ALP activity by between 2.23 and 1.55 times superior to the control, showing the highest results in the study. ## 3.1.3. Mineralized Nodule Deposition Figure 4 presents the means and standard deviations of mineralized nodule (NM) deposition after 48 h of MDPC-23 exposure to flavonoids and evaluation at 14 days. Statistical difference from the control was observed for all concentrations of AMP, RUT and CH, which increased 1.54- to 2.13-fold, 1.58- to 1.78-fold, and 1.57- to 1.88-fold the NM deposition after treatments. ISO at 25 μM differed from the control, increasing the NM deposition 1.67-fold. Figure S1 shows representative microscopic images of alizarin staining for each group in this study. High levels of NM deposition can be seen for all groups at the lowest concentrations. ## 3.2. Hydrogels Extract Treatments In general, among the flavonoids tested, AMP showed superior ALP activity and mineralized nodule deposition, differing from the control at their highest concentrations. Therefore, AMP was chosen to be incorporated in PNVCL for cytotoxicity determination and determination of its effects on mineralization markers in comparison to PNVCL+CH. ## 3.2.1. Cell Viability Evaluation Figure 5, Figure 6 and Figure 7 show the percentages of cell viability after MDPC-23 exposure for 48 h and 7 days to hydrogel extracts, and evaluation at 48 h, 8 days and 14 days after treatments. The 48 h extracts of PNVCL+AMP and PNVCL+CH hydrogels did not affect cell viability. PNVCL was cytocompatible (more than $80\%$ cell viability) at a $\frac{1}{8}$ dilution (Figure 5A). Figure 5B shows the results after treatment with 7-day PNVCL extracts. PNVCL, PNVCL+AMP and PNVCL+CH were not cytotoxic at $\frac{1}{8}$ dilutions. After 8 days, cell viability remained above $90\%$ for all 48 h extracts (Figure 6A) and 7-day extracts at concentrations of $\frac{1}{16}$ and $\frac{1}{32}$ (Figure 6B). Figure 7A,B represent cell viability after 14 days. All 48 h and 7-day PNVCL extracts (PNVCL, PNVCL+AMP and PNVCL+CH at $\frac{1}{16}$ and $\frac{1}{32}$ dilutions) were not cytotoxic, since percentage values are over 70–$80\%$. ## 3.2.2. Alkaline Phosphatase Activity after Treatment with Hydrogel Extracts The alkaline phosphatase activity of MDPC-23 exposed to 48 h extracts and 7-day extracts of the hydrogels can be seen in Figure 8. For 48 h hydrogel extracts, there was an increase on ALP activity for both groups—PNVCL+AMP (1.30- to 1.34-fold) and PNVCL+CH (1.27- to1.43-fold), but there was difference between the dilutions ($\frac{1}{16}$ and $\frac{1}{32}$) (Figure 8A). For 7-day hydrogel extracts, both dilutions of the PNVCL+AMP group promoted an increase in ALP activity (1.35–1.39-fold), there being no difference between them. Both levels were statistically different from the control level. The highest ALP activity was observed for PNVCL+CH at the dilution of $\frac{1}{16}$ (2.1-fold), which was different from the $\frac{1}{32}$ dilution (1.37-fold) and all other groups of the study (Figure 8B). PNVCL alone did not differ from the control (osteogenic DMEM). ## 3.2.3. Mineralized Nodule Deposition of Extracts Figure 9 shows the effect of hydrogel extracts on mineralized nodule (MN) deposition by MDPC-23 cells. For 48 h hydrogel extracts, the $\frac{1}{32}$ dilution of PNVCL+AMP (2.6-fold) induced higher MN deposition than PNVCL+CH at both dilutions (1.97- to 2.23-fold) (Figure 9A). For 7-day hydrogel extracts, PNVCL+AMP at $\frac{1}{32}$ (2.9-fold) presented the highest values of NM deposition, which were not significantly different from those of the $\frac{1}{16}$ dilution (2.24-fold). PNVCL+CH at $\frac{1}{32}$ (1.78-fold) and at $\frac{1}{16}$ (1.47-fold) had similar results and differed statistically from the control (Figure 9B). PNVCL hydrogel did not influence NM deposition by cells. Figures S2 and S3 show representative microscopic images of alizarin staining for each group of hydrogel extracts. The greatest nodule deposition occurred in the PNVCL+AMP $\frac{1}{32}$ group and both dilutions of PNVCL+CH ($\frac{1}{16}$ and $\frac{1}{32}$). ## 4. Discussion The null hypothesis of this study was rejected, since the results obtained by AMP and AMP-loaded PNVCL hydrogel were different from the controls and other experimental groups. Considering the wide range of therapeutic properties of the flavonoids and the search for new biomolecules for regenerative endodontic applications, this study evaluated the cytotoxicity and effects of three flavonol derivatives—ampelopsin (AMP), or dihydromyricetin; and the glycosylated flavonols isoquercitrin (ISO) and rutin (RUT)—on mineralization markers of odontoblast-like cells. All flavonols were cytocompatible when applied to MDPC-23 at the concentrations tested (between 100 and 25 μM), keeping cell viability above $70\%$, independent on the timepoint evaluated. AMP has demonstrated cytoprotective effects on porcine intestinal columnar epithelial cells, IPEC-J2, at 20 and 40 μM, when these cells were exposed to the mycotoxin deoxynivalenol [38], and increased HaCaT cells’ viability and suppressed UVA-induced production of inflammatory cytokines [39]. ISO and RUT also acted as neuroprotective agents on pheochromocytoma PC12 cells exposed to 6-hydroxydopamine at concentrations between 10 and 100 μM [40,41]. Rutin has also been demonstrated to be a cytoprotective flavonoid capable of attenuating the inflammatory response in macrophage cells [42], keratocytes and fibroblasts [43]. Alkaline phosphatase (ALP) and mineralized nodule deposition are considered useful markers of biomineralization in osteoblast and odontoblast cells [44]. Alkaline phosphatase (ALP) activity is the initial phase of the dentin matrix biomineralization, and the formation of mineralization nodules is the final product of cell differentiation [45]. In our study, all flavonoids induced ALP activity and mineralized nodule formation, at specific concentrations. Among the flavonoids tested, AMP had the greatest effect on mineralization markers, which differed from the control levels after using AMP’s highest concentrations. AMP also exhibited no cytotoxic effect on human bone narrow mesenchymal stem cells (BMSCs) from 0.1 to 50 μM and increased ALP activity, osteoblast-specific gene expression and mineral deposition, revealing enhanced osteogenic differentiation [16]. In another study, RUT induced cell proliferation from 0.1 to 100 μM concentrations and protected periodontal ligament stem cells (PDLSCs) from the damages induced by LPS. However, differently from the present study, RUT at 10 μM had the greater effects on ALP activity and stimulated osteogenic differentiation of PDLSCs [25]. ISO, in this study, significantly increased ALP activity and NM deposition at 50 and 25 μM in MDPC-23 cells. Differently from this study, ISO demonstrated osteogenic differentiation and mineral deposition of MC3T3-E1 and BMSCs at concentrations between 0.1 and 10 μM [21,46]. Considering the results observed, AMP was chosen to be incorporated into PNVCL hydrogel (PNVCL+AMP) and evaluated for cytotoxicity and the effects of hydrogel extracts on mineralization markers in comparison to PNVCL+CH. The PNVCL hydrogel is a thermosensitive polymer capable of acting as a drug delivery system [47]. It has been considered biocompatible when exposed to different types of cells, such as human mesenchymal stem cells (MSCs), encapsulated bovine chondrocytes [30], Caco-2 and pulmonary Calu-3 cell lines [32]. In this study, 48 h and 7-day PNVCL hydrogel extracts with or without AMP or CH were applied for 48 h and evaluated at different time points—48 h, 8 days and 14 days. At low concentrations (dilutions $\frac{1}{8}$ to $\frac{1}{32}$), PNVCL+AMP and PNVCL+CH extracts were cytocompatible and induced mineralization markers (at dilutions $\frac{1}{16}$ and $\frac{1}{32}$). In agreement with our results, other studies have shown cytocompatibility of PNVCL hydrogels [30,33,48]. Injectable thermoresponsive hydroxypropyl guar-graft-poly(N-vinylcaprolactam), or HPG-g-PNVCL, was studied for sustainable release of ciprofloxacin and revealed biocompatibility for being used as a scaffold for osteogenic cell growth [33]. Chondrocytes and mesenchymal stem cells were encapsulated in PNVCL hydrogels and showed cell viability higher than $80\%$. In this same study, three-dimensional constructs of chondrocytes and PNVCL hydrogels demonstrated time-dependent increases in glycosaminoglycans and collagens in areas of implants in vivo [33]. PNVCL and itaconic acid at 0.2 to 1 mg/mL were synthesized and presented dual pH and temperature-sensitive properties and cytocompatibility in immortalized hepatic cell line Hep G2 [49]. This was the first study evaluating the potential of ampelopsin-loaded PNVCL hydrogels to stimulate biomineralization in odontoblastic cells. Some studies have demonstrated that the therapeutic effects of AMP were enhanced when it was incorporated into different hydrogels [49,50]. AMP (or dihydromyricetin) was incorporated in cationic nanocapsules for safe topical use in photoprotection against UV-induced DNA damage. This system showed $99.9\%$ protection against DNA lesion induction and cytocompatibility when applied to 3T3 mouse fibroblasts, human fibroblasts and HaCaT human epithelial cells (at 10 μg/mL) [49]. Recently, AMP was added to a self-microemulsion delivery system (d-α-tocopheryl polyethylene glycol 1000 succinate-quillaja saponin), and this system enhanced the absorptivity and ability of AMP to prevent hyperlipidemia in mice models [50]. Some limitations of this present study can be pointed out, such as the lack of microscopic analysis to evaluate cell viability; and live/dead staining and some cell adhesion and proliferation fluorescence assays instead of only resazurin-colorimetric assays. Although the release of AMP and CH from PNVLC hydrogels were determined in a previous study [34], the presence of other components of the PNVCL hydrogels and their concentrations in the hydrogel extracts should have been determined in this study. In view of the results presented, the flavonoid AMP, when incorporated into a PNVCL hydrogel, demonstrated potential for application in endodontic procedures and could overcome the deficiencies of the materials already used—preserving residual cells and increasing their biomineralization ability. For further studies, genetic analysis of specific dentin mineralization markers, such as dentin matrix protein-1 (DMP-1) and dentin sialo phosphoprotein (DSPP), and other osteogenic markers also related to dentinogenesis, such as runt-related transcription factor 2 (RUNX), osteocalcin (OCN) and osteopontin (OPN), will be evaluated. The potential of PNVCL hydrogels as scaffolds for regenerative purposes in endodontics should also be tested. In addition, in vivo studies are necessary to confirm their safety and efficacy for clinical applications. ## 5. Conclusions AMP was cytocompatible and induced the highest levels of mineralized markers in MDCP-23. 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--- title: Detection of Lymphatic Vessels in the Superficial Fascia of the Abdomen authors: - Giovanna Albertin - Laura Astolfi - Caterina Fede - Edi Simoni - Martina Contran - Lucia Petrelli - Cesare Tiengo - Diego Guidolin - Raffaele De Caro - Carla Stecco journal: Life year: 2023 pmcid: PMC10058564 doi: 10.3390/life13030836 license: CC BY 4.0 --- # Detection of Lymphatic Vessels in the Superficial Fascia of the Abdomen ## Abstract Recently, the superficial fascia has been recognized as a specific anatomical structure between the two adipose layers—the superficial adipose tissue (SAT) and the deep adipose tissue (DAT). The evaluation of specific characteristics of cells, fibers, blood circulation, and innervation has shown that the superficial fascia has a clear and distinct anatomical identity, but knowledge about lymphatic vessels in relation to the superficial fascia has not been described. The aim of this study was to evaluate the presence of lymphatic vessels in the hypodermis, with a specific focus on the superficial fascia and in relation to the layered subdivision of the subcutaneous tissue into SAT and DAT. Tissue specimens were harvested from three adult volunteer patients during abdominoplasty and stained with D2-40 antibody for the lymphatic endothelium. In the papillary dermis, a huge presence of lymphatic vessels was highlighted, parallel to the skin surface and embedded in the loose connective tissue. In the superficial adipose tissue, thin lymphatic vessels (mean diameter of 11.6 ± 7.71 µm) were found, close to the fibrous septa connecting the dermis to the deeper layers. The deep adipose tissue showed a comparable overall content of lymphatic vessels with respect to the superficial layer; they followed the blood vessel and had a larger diameter. In the superficial fascia, the lymphatic vessels showed higher density and a larger diameter, in both the longitudinal and transverse directions along the fibers, as well as vessels that intertwined with one another, forming a rich network of vessels. This study demonstrated a different distribution of the lymphatic vessels in the various subcutaneous layers, especially in the superficial fascia, and the demonstration of the variable gauge of the vessels leads us to believe that they play different functional roles in the collection and transport of interstitial fluid—important factors in various surgical and rehabilitation fields. ## 1. Introduction The lymphatic system is distributed throughout the entire human body, and the superficial lymphatic circulation consists of dermal lymphatic capillaries and subcutaneous lymph-collecting vessels. The main role of the lymphatic system is to return protein deposits and extra tissue fluid extravasated from the blood capillaries to the interstitial tissues, feeding into the blood circulation system to maintain fluid balance in the body. The initial lymphatic vessels (LVs) that form in the dermis are composed of a thin layer of endothelial cells that are physically tethered to the surrounding extracellular matrix, along with gradual collection vessels adapted to ensure transport of lymph formed in deep tissues [1]. Lymphedema [2,3,4] is a clinical manifestation caused by impaired lymphatic transport or by the chronic accumulation of interstitial fluid that leads to adipose deposition, fibrosis, or persistent inflammation in the subcutis [2]. Today, therapies for lymphedema—such as liposuction or lymph node transplantation—require a detailed understanding of the anatomy of the subcutaneous lymphatic system. The localization of the LVs and their organization in the subcutaneous layers can help in understanding their altered morphological development in this pathology, as the basis of the fluid accumulation process in interstitial spaces [3]. At the same time, the analysis of the LVs’ distribution can be useful to improve surgical procedures that can preserve the distribution of lymphatic vessels [4]. In the past, the hypodermis was considered to be a homogeneous structure filling the space between the skin and the muscles, but recently many studies have highlighted that it is divided into two layers—the superficial adipose tissue (SAT) and deep adipose tissue (DAT) [5,6,7]—by the superficial fascia (SF). The superficial fascia, recognized as a specific anatomical structure with a distinct anatomical identity, presents specific characteristics of cells and innervation; it is a continuous thin fibrous membrane that is rich in elastic fibers, with a mean thickness of 847.4 ± 295 μm [8,9]. The SAT [8] is a well-organized adipose layer, organized in polygonal–oval fat lobules with vertical fibrous septa, whilst in the DAT the fibrous septa are mostly obliquely/horizontally oriented and the fat cells are few and less organized. The DAT is lipolytically more active [10], with a higher ratio of saturated to monounsaturated fatty acids compared to the SAT [11]. Its function is to provide the autonomy of the SF with respect to the deep fascia, creating a gliding surface between the subcutaneous layer and the musculoskeletal system [12]. Cancello et al. [ 13] have shown that, in obese patients, the abdominal SAT and DAT subcompartments are different at both the molecular and morphological levels, with significant adipocyte hypertrophy in the SAT compared to the DAT. Adiponectin is preferentially expressed in the SAT, whereas inflammatory genes are overexpressed in the DAT. Consequently, the subcompartments have to be considered independently when investigating the subcutis biology and clinical complications of obesity [13]. Today, the exact localization of the LVs in the SAT and DAT, along with their relationships with the superficial fascia, is not well defined. Kubik and Manestar [14] reported that the LVs of the thigh formed three layers: a first layer immediately below the surface of the subcutaneous fat, a second layer between the first and third layers, and a third layer in the deep fascia; however, they did not clarify exactly where the second layer is located. According to Tourani et al. [ 15], in the abdomen, the collectors were found above Scarpa’s fascia immediately below the subdermal venules. They were thin-walled and translucent, and their diameter ranged between 0.2 and 0.8 mm. In the upper thigh, the same authors found two distinct groups of superficial collectors: one deeper, with thick walls measuring 0.6–1 mm in diameter; and one superficial, immediately below the subdermal venules, with thin walls measuring 0.3–0.5 mm. Moreover, Culligan et al. [ 16] demonstrated that small LVs exist within Toldt’s fascia, which separates all apposed portions of the mesocolon from the underlying retroperitoneum. They found a lymphatic network within the connective tissue of the mesenteric organs, and this specific knowledge is important for the decision as to whether the fascial tissues should be removed in oncological colorectal resections. Onder et al. [ 17] highlighted the interaction between mesenchymal cells and lymphatic endothelial cells in the space close to the deep fascia, suggesting that it could be crucial for the activation of lymph node development [17]. Furthermore, Hayashida et al. [ 18] evaluated a combined treatment of adipose-derived stem cells and vascularized lymph node transfer for decreasing edema volumes through accelerated lymphatic drainage. This layered organization of the subcutaneous tissue has recently attracted increasing interest in surgical procedures, such as flaps in plastic reconstructive surgery and fat removal techniques in aesthetic surgery (e.g., abdominoplasty procedures and liposuction). Recently, a new surgical technique for abdominoplasty has been developed, focused on the preservation of Scarpa’s fascia and the deep fat compartment, along with their lymphatic and blood vessels [19,20,21]. This enables a reduction in the incidence of seroma—the most frequent complication related to surgery in the lower abdomen [21]. The aim and the novelty of this research is to understand and describe the lymphatic vessels’ distribution, density, diameter, and organization layer by layer, from the dermis to the DAT, with a particular focus on the superficial fascia. ## 2.1. Sample Collection Tissue specimens were harvested from three adult volunteer patients (mean age 42 ± 4 years; 2 females, 1 male) during abdominoplastic surgery. All of the patients were obese (BMI 28–30), without any comorbidities reported (such as diabetes, cardiovascular disease, or cancer). The ethical regulations regarding research on human tissues were carefully followed in accordance with the rules described by Macchi and co-authors [22]. According to Italian law, the parts of the body removed for therapeutic purposes during surgery that would otherwise be destined for destruction can be used for research. For each patient, 3 samples, of ~1 cm2 were randomly collected from different areas of the abdominal region, at full thickness, from the epidermis to the DAT [23]. Moreover, from each subject, three additional samples of the superficial fascia were isolated from the surrounding adipose tissue. Next, the samples were fixed in $10\%$ buffered formaldehyde (pH 7.4), after which they were dehydrated in graded ethanol and xylene, and then embedded in paraffin. Five-micrometer sections were cut using a microtome for histological and immunohistochemical staining. ## 2.2. Histological and Immunohistochemical Staining First, the sections were stained with hematoxylin and eosin to evaluate the general morphology of the tissue. Secondly, the sections were additionally immunostained with the monoclonal antibody D2-40 (Biocare Medical, Cat.# CM 266 A, B, C, RRID: AB_2923154) against the transmembrane glycoprotein podoplanin, as a specific marker for the endothelial cells of the LV [24,25,26], according to the following protocol. Dewaxed sections were treated with $1\%$ hydrogen peroxide (Marco Viti Pharmaceutical, Sandrigo, Vicenza, Italy) to block endogenous peroxidases. Non-specific sites were then saturated with horse serum (S-2000, Vector Laboratories, Burlingame, CA, USA) (HS) and diluted 1:60 in triphosphate buffer solution + $0.1\%$ Tween 20 (Sigma-Aldrich, St. Louis, MI, USA) (TBST) for 1 h. Then, the sections were incubated with the murine monoclonal primary antibody D2-40 and diluted 1:100 in TBST + $1\%$ HS overnight at 4 °C. After repeated washing with TBST, the sections were incubated with a horse anti-mouse secondary antibody (BA-2000, Vector Laboratories) and diluted 1:500 in TBST for 30 min. Signal amplification was performed using the ABC-HRP Kit, Peroxidase (Standard) (PK-6100, Vector Laboratories), and the reaction was developed with 3,3′-diaminobenzidine (Liquid DAB + substrate Chromogen System (K346711-2, Agilent’s Dako, Santa Clara, CA, USA)) before being stopped with distilled water. Nuclei were counterstained with Mayer’s hematoxylin (Leica Microsystems, Milan, Italy). Skin samples on which the primary antibody was omitted were used as negative controls, and human tonsil samples were used as positive controls, to verify the specificity of the reaction. ## 2.3. Image Acquisition The images were acquired using Leica DMR microscope (Leica Microsystems, Wetzlar, Germany) operating at a primary magnification of 10×. To ensure systematic scanning of the tissue, one operator counted all of the fields, starting from the upper-left corner and moving horizontally from left to right, then one row down from right to left, and so on. The total number of acquired images was recorded, and the D2-40-positive fields were counted with respect to the total section and with respect to the various subcutaneous layers (D: epidermis and dermis; SAT: superficial adipose tissue; SF: superficial fascia; DAT: deep adipose tissue). A second image acquisition at 20× magnification was performed to acquire images on each positive field, with the aim of measuring the diameters of the vessels. The images were acquired in full color (RGB, 24-bit) and saved as TIFF files for further processing. ## 2.4. Image Analysis of Lymphatic Vessels Computer-assisted image analysis was performed on the obtained set of images to characterize D2-40 immunoreactivity in the subcutaneous layers of full-thickness samples. All analysis procedures were performed using ImageJ software, freely available at http://rsb.info.nih.gov/ij/ (accessed on 16 March 2023) [27]. Briefly, after shading correction and contrast enhancement, color thresholding was applied to discriminate immunoreactive structures, and the area occupied by immunoreactive structures in each layer (D, SAT, SF, and DAT) was then measured. From these primary data, two parameters were derived: The first describes the percentage of the tissue area in a layer occupied by immunoreactivity (Area%), which was estimated from the ratio between the total immunoreactive area measured in that layer and the total sampled area of the layer. The second provides information on the relative amount of immunoreactive structures in each layer (IR%), which was evaluated as the percentage ratio between the total immunoreactive area measured in that layer and the total immunoreactive area observed in the whole section. Finally, in each of the considered tissue layers, the mean diameter of D2-40-positive vessels was evaluated by interactively measuring this parameter on a sample ($$n = 30$$) of immunoreactive profiles. ## 2.5. Statistics For each layer, the obtained Area%, IR%, and diameter values were averaged across the 9 samples analyzed to provide representative values of the parameters for that layer. With the sample size being quite small, the normality of the datasets was first verified using the Kolmogorov–Smirnoff method. Differences between the four considered layers were then statistically tested by one-way analysis of variance, followed by Tukey’s test for multiple comparisons. The GraphPad Prism 3.0 statistical package (GraphPad Software Inc., San Diego CA, USA) was used for the analysis. Results are reported as the mean ± SEM, and $p \leq 0.05$ was considered as the limit for statistical significance. ## 3.1. Morphological Structure of the Samples The subcutaneous layers were clearly recognizable in all of the samples stained with hematoxylin and eosin (Figure 1). More specifically, from the surface going inward, the following layers could be identified: the skin (epidermis (E) and dermis (D)), the superficial adipose tissue (SAT), the superficial fascia (SF), and the deep adipose tissue (DAT). There were no identified differences between the specimens derived from different subjects. The staining of the dermis highlights the fibrillary component that then continues as fibrous septa (retinacula cutis superficialis) into the SAT. These septa appeared well defined, with a perpendicular orientation with respect to the surface; they encased the subcutaneous fat in large adipose lobes, as a honeycomb structure (Figure 1a). Below, the SF appeared as a thin fibrous layer (Figure 1b), with a membranous appearance and a multilayered structure of collagen bundles. The histological tangential section of the SF layer showed a net of irregularly arranged collagen fibers, interpenetrated by adipose clusters and crossed by a rich vascular pattern (Figure 1c), as already demonstrated and described in our previous works [23,28]. Beneath the SF, another layer of adipose tissue was visible—the DAT—with smaller, flatter, and less-defined adipose lobes than those of the SAT (Figure 1a). Furthermore, the network of collagen fibrous septa (retinacula cutis profunda) that was visible in this layer was more irregular. ## 3.2. Distribution of Lymphatic Vessels The positivity of the LV endothelium marker D2-40 enabled us to distinguish the LVs from the blood vessels. In the LVs, the endothelium appeared positive for the staining and was morphologically extremely flattened, with an empty lumen (Figure 2). The specificity of the staining was tested in a human tonsil tissue specimen, used as a positive control (Figure 2a). The D2-40 antibody strongly marked the vessels observed in the papillary dermis and embedded in the loose connective tissue (Figure 2b–d). LVs crossed the tissue vertically to reach the deeper dermis (Figure 2d), where LVs were also observed near the sebaceous glands, the hair follicles, and the sweat glands, with a coiled tubular structure (Figure 2e,f). The evaluation of the diameter of LVs in the dermis showed a mean value of 15.5 ± 3.42 µm (Figure 3). In the SAT, only thin LVs were visible; they were found close to the fibrous septa (retinacula cutis) connecting the dermis and the SAT, as well as around the blood vessels (Figure 4). The mean diameter of the LVs in the SAT area was equal to 11.6 ± 7.71 µm (Figure 3). In the superficial fascia layer, more LVs were evident, and with different orientations; they followed the fibers, and they were distributed in both the longitudinal and transverse directions (Figure 5). The mean diameter of these intrafascial LVs was 19.5 ± 5.77 µm (Figure 3). Lastly, the DAT presented clear and wide LVs close to the blood vessels (Figure 6). These LVs were less connected with the fibrous septa, and the mean diameter of the vessels in this region was 22.5 ± 12.77 µm (Figure 3). Multiple comparison analyses showed a significant difference in the vessel diameters between the SAT and the DAT ($$p \leq 0.038$$), and both the SAT and DAT diameters showed no significant difference with the SF (Figure 3). Figure 7a shows a full-thickness sample from the skin to the DAT, stained with D2-40; the immunoreactivity was visible only at greater magnification (as shown in the insets). Figure 7b summarizes and illustrates the organization of the LVs in relation to the superficial fascia. ## 3.3. Density Analysis of Lymphatic Vessels The density of the LVs was analyzed in each layer. The Area% shown in Figure 8a was estimated from the ratio between the total immunoreactive area measured in a specific layer and the total sampled area of the same layer. The results showed that the Area% in the dermis (D) (0.095 ± $0.018\%$) was significantly higher than in the SAT and DAT ($p \leq 0.01$), but it was not significantly different with respect to the SF layer (0.122 ± $0.029\%$; $p \leq 0.05$) (Figure 8a). The density of LVs in the DAT was not significantly different ($p \leq 0.05$) than in the SAT, with a mean Area% of 0.0059 ± $0.002\%$ (from 0.0018 to 0.013) and 0.0044 ± $0.001\%$ (from 0.0023 to 0.0084), respectively (Figure 8a). The SF layer was the second most reactive tissue, after the dermis, when evaluating the percentage ratio of LV positivity with respect to the total immunoreactive area observed in the whole section ($$p \leq 0.0008$$ between D and SF) (IR%, Figure 8b). In fact, the IR% was equal to 54.03 ± $13.8\%$ in the dermis, 31.2 ± $14.1\%$ in the SF, $6.67\%$ ± 3.9 in the SAT, and $8.07\%$ ± 9.6 in the DAT. ## 4. Discussion This study demonstrated for the first time the presence of lymphatic vessels inside the superficial fascia, and that the LVs have a different distribution in the various subcutaneous layers (Figure 8). We confirmed the presence of a lymphatic plexus extended into the dermal papillae, as already described by Ryan [29], but this study also highlighted for the first time a second plexus inside the superficial fascia. In the SF, a huge number of LVs (IR% equal to 31.2 ± $14.1\%$, with a mean diameter of 19.5 ± 5.77 µm) were clearly identifiable, with different spatial orientations, supporting the idea that they are organized in a sort of lymphatic plexus that then feeds into the LVs of the DAT. This description of a new lymphatic plexus inside the SF could explain why the preservation of the Scarpa and DAT layers during abdominal surgery can reduce the incidence of seroma [21]. Furthermore, the LVs in the SAT and DAT also showed peculiar characteristics and specific relationships with the surrounding structures. Indeed, in the SAT, the LVs had a vertical course and followed the retinacula cutis, whilst in the DAT they were close to the blood vessels and had a more oblique orientation. The analysis of IR% in the different areas showed that the SAT and DAT have comparable overall contents of LVs, albeit with significantly different diameters—smaller in the SAT (11.6 ± 7.7 µm) than in the DAT (22.5 ± 12.77 µm). The close relationship of the LVs with the SF has many clinical implications, especially if we consider that the thin lymph vessels need the support of the extracellular matrix to maintain their patency. It is well known that the lymphatic cells are closely connected to the surrounding tissues by fine strands of reticular fibers and elastic fibers [29,30], called anchoring filaments. When the interstitial pressure is low, the anchoring filaments are in a relaxed conformation, resulting in the closure of oak-leaf-shaped overlapping flaps. Consequently, it easy to suppose that any alteration of the SF can affect the anchoring filaments of the LVs, reducing their ability to drain the lymph. Additionally, in the SAT, a close relationship between LVs and the fibrous septa was highlighted, suggesting that the elasticity and organization of the fibrous matrix can also affect lymphatic transport from the dermal plexus to the deeper, larger lymphatic vessels, improving or worsening it [9]. Avraham et al. [ 31] showed that the inhibition of fibrosis by topical dressings can accelerate the lymphatic regeneration of normal capillary lymph vessels, so an altered structure of the SF and subcutaneous layers could probably compromise the lymphatic drainage. In the same way, damage to the superficial fascia during classic abdominoplasty procedures can lead to the interruption of lymphatic vessels of a certain caliber, causing a high incidence of seroma and postoperative complications. It has already been clinically demonstrated that the classic plane of dissection—on the top of the deep fascia—should be avoided in the lower abdomen to minimize wound-healing complications and seroma [32]. Indeed, this work demonstrates that the superficial fascia plane contains a lymphatic plexus, explaining how its preservation can reduce complications and lead to greater surgical success. Bassalobre et al. [ 33] showed that significant changes in the lymphatic drainage pathways occurred in the infraumbilical region after abdominoplasty, with the axillary drainage path predominating after the surgery, in contrast to the inguinal path observed in the preoperative period. Furthermore, our new results on the distribution of LVs may improve the comprehension of clinical manifestations of impaired lymphatic transport. Several authors have already revisited the anatomy of the lymphatic system, reliably identifying the lymphatic collectors and venules [34,35,36], but we think that the knowledge of the strong relationships between fibrous elements of the subcutaneous tissues [9,37] and LVs could better improve the clinical and ultrasound evaluation of lymphedema and, consequently, improve targeted therapies, as well as suggesting modifications of manual lymphatic drainage techniques in postoperative subjects. It is well known that lymphedema can induce complications such as inflammation [38], fat tissue hypertrophy, and fibrosis [4,10], and the subcutaneous alterations [39] can alter the environment around the LVs, increasing their collapsibility. In the near future, in the evaluation of lymphedema, it will be important to also consider the thickness, texture, and stiffness of the SF, SAT, and DAT, because they may directly influence the responses to the various therapeutic interventions. It is evident that lymphatic transport is not a mere passive and automatic process [40,41] but represents a highly sophisticated system in which endothelial and muscle cells, along with the collagen and elastic fibers around them, ensure proper lymphatic drainage and propulsion [9,42,43]. ## 5. Conclusions Immunohistological analysis of lymphatic vessels has led to increased knowledge of their anatomy in the subcutis. 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--- title: Survey of Edible Amanita in Northern Thailand and Their Nutritional Value, Total Phenolic Content, Antioxidant and α-Glucosidase Inhibitory Activities authors: - Jaturong Kumla - Nakarin Suwannarach - Yuan S. Liu - Keerati Tanruean - Saisamorn Lumyong journal: Journal of Fungi year: 2023 pmcid: PMC10058571 doi: 10.3390/jof9030343 license: CC BY 4.0 --- # Survey of Edible Amanita in Northern Thailand and Their Nutritional Value, Total Phenolic Content, Antioxidant and α-Glucosidase Inhibitory Activities ## Abstract Edible wild mushrooms are extremely popular among consumers and are highly valued for their potential economic benefits in northern Thailand. In this present study, a total of 19 specimens of edible Amanita were collected during investigations of wild edible mushrooms in northern Thailand during the period from 2019 to 2022. Their morphological characteristics and the phylogenetic analyses of the internal transcribed spacer (ITS) and partial large subunit (nrLSU) of ribosomal RNA, RNA polymerase II second-largest subunit (rpb2) and partial translation elongation factor 1-alpha (tef-1) indicated that the collected specimens belonged to A. hemibapha, A. pseudoprinceps, A. rubromarginata, A. subhemibapha, and Amanita section Caesareae. This is the first report of A. pseudoprinceps and A. subhemibapha from Thailand. Full descriptions, illustrations and a phylogenetic placement of all specimens collected in this study are provided. Subsequently, the nutritional composition and total phenolic content, as well as the antioxidant and α-glucosidase inhibitory activities, of each species were investigated. The results indicate that the protein contents in both A. pseudoprinceps and A. subhemibapha were significantly higher than in A. hemibapha and A. rubromarginata. The highest total phenolic content was found in the extract of A. pseudoprinceps. In terms of antioxidant properties, the extract of A. pseudoprinceps also exhibited significantly high antioxidant activity by 2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS), 2,2-diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) assays. However, the extract of A. rubromarginata had the lowest total phenolic content and level of antioxidant activity. Additionally, α-glucosidase inhibitory activity varied for different Amanita species and the highest level of α-glucosidase inhibitory activity was found in the extract of A. pseudoprinceps. This study provides valuable information on the nutrient content, phenolic content and the antioxidant and α-glucosidase inhibitory potential of edible Amanita species found in northern Thailand. ## 1. Introduction The genus Amanita Pers. was first introduced in 1797 by Persoon [1] with A. muscaria (L.) Lam. as the type species. This genus is one of several large genera with approximately 650 species distributed throughout tropical, subtropical and temperate regions around the world [2,3,4,5,6]. Amanita is a member of the family Amanitaceae, order Agaricales [3,4,5,6]. Generally, Amanita is characterized by agaricoid basidiomata having free lamellae, white spore prints, hyaline and smooth basidiospores, as well as the presence of volval remnants (universal veil) and the presence of annulus (partial veil) on the stem [1,7,8,9]. Currently, taxonomic studies have divided this genus into three subgenera (Amanita subg. Amanita, Amanitina, and Lepidella) and eleven sections based on multi-gene phylogenetic analyses [4,10,11]. Most of the Amanita species are known to be ectomycorrhizal fungi that form mutualistic symbioses with more than ten families of plants (including Betulaceae, Caesalpiniaceae, Casuarinaceae, Dipterocarpaceae, Fabaceae, Myrtaceae, Pinaceae, and Salicaceae) and are known to grow on the ground in forests [3,4,9,12]. However, the Amanita species in Amanita sect. Lepidella have been reported as saprobes that grow in grasslands [4,9,13,14,15]. Notably, Amanita contains both edible and lethal species. The most toxic species are in Amanita sect. Phalloideae [e.g., A. exitialis Zhu L. Yang & T.H. Li, A. phalloides (Vaill. ex Fr.) Link, A. verna Bull. ex Lam. and A. virosa Bertill.], while most of the edible species belong to Amanita sect. Caesareae [2,4,16,17,18]. The most famous edible Amanita species are A. caesarea (Scop.) Pers., A. chepangiana Tulloss & Bhandary, A. flammeola Pegler & Piearce, A. franchetii (Boud.) Fayod, A. fulva Fr., A. hemibapha (Berk. & Broome) Sacc., A. jacksonii Pomerl., A. manginiana Har. & Pat., A. loosii Beeli, A. pseudoporphyria Hongo, A. princeps Corner & Bas, A. rubescens Pers., A. tuza Guzmán, A. vaginata (Bull.) Lam., and A. zambiana Pegler & Piearce [3,4,5,6,17,18,19,20]. Several edible wild mushrooms are known to be a good source of essential dietary minerals, nutrients, and vitamins, which makes them an important source of food for humans [17,20,21]. These mushrooms have also been recognized as a source of many bioactive compounds (e.g., immunomodulatory compounds, phenolic compounds, polysaccharides, terpenoids and tocopherols) that exhibit various beneficial biological activities including anticancer, antidiabetic, anti-inflammatory, antimicrobial, antioxidant, cholesterol-reducing, immunomodulatory and neuroprotective properties [22,23]. Additionally, ethnomycologists have recorded vital information on the relevant consumption patterns and applications of wild edible mushrooms for medicinal purposes [24,25]. Thailand, a Southeast Asian country, has many species of edible wild mushroom that are particularly abundant during the rainy season (mid-May to October) each year. Generally, wild edible mushrooms are collected by local farmers for consumption and sale in local, roadside or city markets (Figure 1). Preliminary investigations of edible wild mushrooms in northern Thailand have revealed the existence of many genera, e.g., Amanita, Astraeus, Boletus, Cantharellus, Lactarius, Phlebopus, Russula, and Termitomyces [26,27,28]. Edible Amanita species are the most popular variety of edible wild mushrooms in northern Thailand because of their palatable texture and flavor. However, the number of lethal and edible Amanita species that have been found in Thailand has remained a controversial issue due to the absence of comprehensive herbarium reference material, accurate descriptions and available molecular data [29]. During our ongoing studies of edible wild mushrooms in northern Thailand, we have collected specimens of edible Amanita species from natural forests, roadsides and local markets. Therefore, the present study aimed to identify the collected specimens based on their morphological characteristics and multi-gene phylogeny using the sequence data of ITS, nrLSU, rpb2, and tef-1. A full description, color photographs, illustrations and a phylogenetic tree of the collected specimens are provided. Moreover, the nutritional composition, total phenolic content, and antioxidant and α-glucosidase inhibitory activities of collected edible Amanita were investigated. ## 2.1. Sample Collection The edible Amanita were surveyed and collected from natural forests, roadsides and local markets in Chiang Mai and Lamphun Provinces in northern Thailand during the rainy seasons of the years 2019 to 2022. Basidiomata were kept in plastic boxes and taken to the laboratory. Specimens were dried in a hot air oven at 45 °C until they were completely dry. After that, the dried specimens were kept in a plastic Ziplock bag and deposited in the Herbarium of Sustainable Development of Biological Resources (SDBR-CMU), Faculty of Science, Chiang Mai University, Thailand. ## 2.2.1. Morphological Observations Fresh specimens were used to describe macromorphological data. Color names and codes were followed by Kornerup and Wanscher [30]. The dried specimens were examined for micromorphological data. Dried specimens were mounted in $5\%$ aqueous KOH, Melzer’s reagent, or $1\%$ aqueous Congo red solution. A light microscope (Nikon Eclipse Ni U, Tokyo, Japan) was used to examine micromorphological features. Each microscopic structure’s size data were derived from at least 50 measurements using the Tarosoft (R) Imaging Frame Work program. The terminology for microscopic features followed Largent et al. [ 31] and Bas [32]. Basidiospore statistics are expressed as (a–) b–c (–d), where ‘a’ and ‘d’ are the extreme values and ‘b–c’ is the range comprising $90\%$ of all values. The Q value represents ratio of the length divided by the width of each basidiospore and Qm is the average Q of all specimens ± standard deviation. ## 2.2.2. DNA Extraction, Amplification, Sequencing, and Phylogenetic Analyses A Genomic DNA Extraction Mini-Kit (FAVORGEN, Ping-Tung, Taiwan) was used to extract DNA from fresh tissue of each specimen. The ITS, nrLSU, rpb2, and tef-1 regions were amplified by polymerase chain reaction (PCR) using ITS5/ITS4 [33], LR0R/LR5 [34], Am6F/Am7R [35], and EF1-983F/EF1-1567R [36] primers, respectively. The PCR for these four domains was performed in separate PCR reactions on a peqSTAR thermal cycler (PEQLAB Ltd., Fareham, UK). The PCR programs of ITS, nrLSU, rpb2, and tef-1 genes were established by following the methods employed by Liu et al. [ 15] and Cai et al. [ 36]. PCR products were directly sequenced by the Sanger sequencing method at 1st Base Company (Kembangan, Malaysia). Sequence analysis was performed by a similarity search using the BLAST program available at NCBI (http://blast.ncbi.nlm.nih.gov, accessed on 12 November 2022). Sequences from this study, previous studies, and the GenBank database were selected and listed in Table 1. The combined dataset of ITS, nrLSU, rpb2, and tef-1 was used for the phylogenetic analysis. MUSCLE [37] was used to perform multiple sequence alignments, and BioEdit v. 6.0.7 [38] was used to make any necessary improvements. Maximum likelihood (ML) and Bayesian inference (BI) methods were used to construct phylogenetic trees. The best substitution models were GTR+I+G for ITS, nrLSU and tef-1 and HKY+I+G for rpb2 from the Akaike Information Criterion (AIC) in jModeltest 2.1.10 [39]. The GTRCAT model with 25 categories was subjected to ML analysis using RAxML v7.0.3 and 1000 bootstrap replications [40,41]. MrBayes v3.2.6 [42] was used for the BI analysis, which evaluated the posterior probabilities (PP) using Markov chain Monte Carlo sampling (MCMC). Six simultaneous Markov chains were run from random trees for one million generations and trees were sampled every 100th generation. The first $25\%$ of trees were discarded and the remaining trees were used for calculating PP value in the majority rule consensus tree. FigTree v1.4.0 [43] was used to visualize the tree topologies. ## 2.3. Nutritional Analysis A total of six samples of edible Amanita (SDBR-CMUNK0775, SDBR-CMUNK0776, SDBR-CMUNK0780, SDBR-CMUNK0853, SDBR-CMUNK0855, and SDBR-CMUNK0857) obtained in this study were used in the analyses of nutrition, antioxidant, and α-glucosidase inhibitory activities because their dry weights were sufficient for testing. A Waring blender (New Hartford, CT, USA) was used to grind each dried sample. The nutritional composition (including ash, carbohydrate, fat, fiber, and protein) of each dried sample was determined using a method developed by the Association of Official Analytical Chemists (AOAC) [44] at the Central Laboratory Company Limited (Chiang Mai, Thailand). ## 2.4. Preparation of Mushroom Extracts Ten grams (10 g) of each ground mushroom sample was extracted with 100 mL of absolute ethanol at 25 °C and 150 rpm for 24 h, as described by Kaewnarin et al. [ 45]. After that, each extract was placed in an ultrasonic bath (Elma Transsonic Digital, Singen, Germany) at 60 °C for 3 h. Whatman’s No. 1 filter paper was used to filter the samples. The residue was then re-extracted twice with absolute ethanol as mentioned above. The ethanolic extract was then dried using rotary evaporation at 40 °C. The extract was dissolved in 100 mL absolute ethanol and kept at 4 °C until further determination. ## 2.5. Determination of Total Phenolic Content The method of Thitilertdecha et al. [ 46] was modified slightly to determine the total phenolic content. Folin-Ciocalteu reagent at 0.5 mL was mixed with 2.5 mL deionized water and 0.25 mL mushroom extract. After 5 min, 0.5 mL of Na2CO3 ($20\%$ w/v) was added. The mixture was incubated for 1 h in the dark at 25 °C. Measurements of absorbance at 760 nm were used to investigate the total phenolic content. The total phenolic content of the samples was calculated using a standard curve of gallic acid. Results were expressed as milligrams of gallic acid equivalents per gram of dry weight (mg GAE/g dw). Each sample extract was analyzed in five replicates. ## 2.6.1. ABTS Scavenging Assay The procedure of Re et al. [ 47] with slight modifications was used to determine the 2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging activity. The stock solution of ABTS cation chromophore was prepared by facilitating a reaction between 100 mL of 2.45 mM K2S2O8 and 100 mL of 7.0 mM ABTS solution. The solution was kept for 16 h in a dark place at room temperature. The ABTS solution was diluted with phosphate buffer (50 mM, pH 7.4) before use to yield an absorbance value of 0.70 ± 0.2 at 734 nm. A quantity of 2.9 mL of ABTS solution was mixed with 0.1 mL of each sample extract. The mixtures were incubated in the dark for 30 min at room temperature. A mixture of absolute ethanol and ABTS solution was used as the control. After incubation, the absorbance of each mixture was measured spectrophotometrically at 734 nm. Trolox was used as a reference compound. The ABTS scavenging activity was expressed as the Trolox equivalent antioxidant capacity per gram of dry weight (TE/g dw). Each sample extract was subjected to five replications. ## 2.6.2. DPPH Scavenging Assay The method developed by Gülçin et al. [ 48] was used to determine the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity. Initially, 1.5 mL of the 0.1 mM DPPH solution in methanol was combined with 0.5 mL of the sample extract. The mixtures were incubated at room temperature in the dark for 30 min. Then, the absorbance of each mixture was determined using spectrophotometry at 517 nm. Trolox was used as a reference compound. The DPPH scavenging activity was expressed as the TE/g dw. Five replicates were performed for each sample extract. ## 2.6.3. FRAP Assay The method developed by Li et al. [ 49] was used to determine the ferric reducing antioxidant power (FRAP) activity. The FRAP reagent was prepared using a mixture containing 20 mL of 20 mM ferric (III) chloride, 10 mM 2,4,6-tripyridyl-s-triazine solution in 20 mL of 40 mM HCl, and 5 mL of 300 mM acetate buffer (pH 3.6). A quantity of 1.5 mL of FRAP reagent and 1.4 mL of acetate buffer (300 mM, pH 3.6) were mixed with 0.1 mL of each sample extract. Then, the mixture was incubated in the dark for 30 min at room temperature. Trolox was used as a reference compound. A mixture of absolute ethanol and FRAP solution was used as the control. After incubation, the absorbance of each mixture was measured spectrophotometrically at 593 nm. Trolox was used as a reference compound and the FRAP value was expressed as the TE/g dw. Five replicates were performed for each sample extract. ## 2.7. Determination of α-Glucosidase Inhibitory Activity The procedure of Oki et al. [ 50] was modified to prepare the α-glucosidase solution from rat intestinal acetone powder. A quantity of 3 mL of $0.9\%$ NaCl solution was mixed with 100 mg of intestinal acetone powder (Sigma-Aldrich Chemical Co., Saint Louis, MO, USA), homogenized by sonication, and stored in an ice bath. The enzyme mixture was centrifuged at 4 °C for 30 min at 8000 rpm. The supernatant was maintained in an ice bath and directly subjected to inhibitory assay. The α-glucosidase inhibitory assay was followed the procedure of Tanruean et al. [ 51] with some modifications. Each extracted sample (10 μL) was mixed with α-glucosidase solution (30 μL) and incubated at 37 °C for 15 min. Later, 70 μL of 37 mM D-maltose was then added and incubated at 37 °C for 15 min. The reaction was stopped after 10 min in boiling water. A glucose oxidase assay was used to determine the released glucose concentration of the reaction mixture. The peroxidase-glucose oxidase (PGO) reagent (900 µL) containing 1 capsule of PGO enzymes to 100 mL of water and 1.6 mL of o-dianisidine solution was added to the reaction mixture and it was then mixed for 30 min at 37 °C in a water bath. The absorbance of α-glucosidase activity was measured at 450 nm. The percentage of inhibition was calculated according to the formula: Percentage of inhibition = (Ao−As/Ao) × 100, where Ao is the absorbance of the control and As is the absorbance of the mixture containing the test compound. Acarbose (a standard synthetic inhibitor of α-glucosidase) was used for standard compound. Each sample extract was analyzed in five replicates. ## 2.8. Statistical Analysis Statistical differences between treatments were assessed using one-way analysis of variance (ANOVA) with the SPSS program version 16.0 for Microsoft Windows. Significant differences at the $p \leq 0.05$ level were determined using Tukey’s test. The Pearson correlation coefficients (r) of the total phenolic content with antioxidant and α-glucosidase inhibitory activities of extract samples were analyzed using the SPSS program at a significance level of $p \leq 0.05.$ ## 3.1. Sample Collection and Morphological Observations In this study, a total of 19 edible Amanita specimens were obtained (Table 2). These specimens were initially classified into four Amanita species, namely A. hemibapha (4 specimens), A. pseudoprinceps (7 specimens), A. rubromarginata (4 specimens), and A. subhemibapha (4 specimens), based on their morphological characteristics. Subsequently, multi-gene phylogenetic analysis further confirmed their identification. ## 3.2. Phylogenetic Analyses The aligned dataset of the combined ITS, nrLSU, rpb2, and tef-1 sequences consisted of 2831 characters including gaps (ITS: 1–903, nrLSU: 904–1676, rpb2: 1677–2316, and tef-1: 2317–2831). The matrix had 1192 different alignment patterns and $23.41\%$ gaps or undetermined characters. A final ML Optimization Likelihood value of −15972.8506 was the best-scoring RAxML tree. For BI analysis, the final average standard deviation value of the split frequencies at the end of the total MCMC generations was calculated as 0.00723. The topology of the phylogenetic trees from the ML and BI analyses were similar. A phylogenetic tree obtained from the ML analysis is represented in Figure 2. Our phylogenetic tree was constructed with the aim of having similar outcomes to previous phylogenetic studies [4,52,53,54]. The phylogenetic tree consisted of 62 specimens of Amanita sect. Caesareae and two specimens of Amanita sect. Vaginatae (the outgroup). The phylogenetic tree clearly separated the 19 specimens obtained in this study into four species clades, namely A. hemibapha (4 specimens), A. pseudoprinceps (7 specimens), A. rubromarginata (4 specimens), and A. subhemibapha (4 specimens) in Amanita sect. Caesareae with high supported values (BS = $100\%$ and PP = 1.0). ## 3.3.1. Amanita hemibapha (Berk. & Broome) Sacc., Syll. Fung. (Abellini) 5: 13 (1887) (Figure 3) Basidioma medium-sized. Pileus 6–12 cm diam., plano-convex with the center slightly depressed, orange-red (6A6–8) to lemon yellow (3B8) at center, and becoming vivid yellow (3A7–8) to pale yellow (3A3–4) towards the margin; universal veil on pileus white patch; margin striate (0.3 R), non-appendiculate; context 5 mm wide, white (1A1) to yellowish white (2A2), unchanging. Lamellae free, crowded, cream white (1A1–2); lamellulae truncate. Stipe 7–10.5 × 0.5–1.5 cm, cylindrical, covered by light yellow to vivid yellow (2A5–8) fibrous squamules; context broadly fistulose, white (1A1). Bulb absent. Universal veil on stipe base saccate, membranous, up to 4 cm high, white (1A1). Partial veil subapical, fragile, vivid yellow (3A7–8). Figure 3: Amanita hemibapha SDBR-CMUNK0776 (a), SDBR-CMUSTO-2019-477 (b), SDBR-CMUNK0857 (c) and SDBR-CMUNK0819 (d). Basidiomata (a–d). Basidiospores (e). Basidia (f). Scale bars: (a,c,d) = 5 cm; (b) = 1 cm; (e) = 10 μm; (f) = 15 μm. Lamellar trama bilateral, divergent; mediostratum 25–40 μm wide, filamentous hyphae abundant, 2–8 μm wide; clavate to ellipsoidal inflated cells 70–98 × 20–23 μm; vascular hyphae scarce. Subhymenium 20–35 μm thick in 2–3 layers, with subglobose to ellipsoidal or irregular cells, 6–25 × 5–15 μm. Basidia 32–50 × 8–12 μm, clavate, 4-spored with sterigmata 3–5 μm long; clamps present at base. Basidiospores (7.0–) 7.5–11.0 (–12.0) × 5.5–7.0 μm, $Q = 1.23$–1.64 (–1.71) μm, Qm = 1.44 ± 0.13, broadly ellipsoid to ellipsoid, sometimes elongate, inamyloid, hyaline, thin-walled, smooth; apiculus small. Lamellar edge sterile; filamentous hyphae 1–5 μm wide, hyaline, thin-walled; inflated cells, with subglobose, ovoid to ellipsoidal, 14–40 × 12–30 μm, single and terminal or in chains of 2–3, hyaline, thin-walled. Pileipellis 60–110 μm thick; 2-layered, upper layer 15–35 μm thick, filamentous hyphae 1–5 μm wide, weakly gelatinized, branching, thin-walled, hyaline; lower layer 50–85 μm thick, filamentous hyphae 2–7 μm wide, branching, thin-walled, hyaline to light yellow; vascular hyphae rare. Inner surface of universal veil on stipe base filamentous hyphae dominant 1–9 μm wide, hyaline to light yellow, thin-walled, branching; inflated cells, with subglobose, pyriform to clavate, 30–85 × 20–54 μm, hyaline, thin-walled; vascular hyphae rare. Outer surface of universal veil on stipe base similar to structure of inner part, but presenting more abundant inflated cells. Stipe trama longitudinally acrophysalidic; filamentous, undifferentiated hyphae 1–12 μm wide, thin-walled, frequently branching; acrophysalides 65–190 × 25–65 μm, thin-walled; vascular hyphae rare. Partial veil filamentous hyphae very abundant, 2–9 μm wide, hyaline, thin-walled; inflated cells scarce to locally abundant, globose, subglobose to clavate, 22–70 × 9–25 μm, hyaline to light yellow, thin-walled; vascular hyphae rare. Clamp connections present in all tissues of basidioma. Habitat: Solitary to scattered on soil in tropical deciduous forests dominated by Dipterocarpus and Shorea. Distribution: known from China [3,4,8,10], India [55,56], Sri Lanka [57], and Thailand [5], this study. Specimens examined: Thailand, Chiang Mai Province, Mae Taeng District, 19°07′45″ N 98°45′51″ E, alt. 1421 m, 9 August 2019, Yuan S.L., STO-2019-477 (SDBR-CMUSTO-2019-477); Doi Saket District, 18°53′2″ N 99°9′17″ E, alt. 343 m, 26 July 2020, Kumla J. and Suwannarach N., CMUNK0819 (SDBR-CMUNK0819), 11 August 2020, Kumla J. and Suwannarach N., CMUNK0857 (SDBR-CMUNK0857); Lumphun Province, Mueang District, Chiang Mai University Haripunchai Campus, 18°30′10″ N 99°8′25″ E, alt. 400 m, 25 July 2020, Suwannarach N., CMUNK0776 (SDBR-CMUNK0776). Remarks: The remarkable features of A. hemibapha include the fact that this species has a reddish yellow or orange-red tone in the center of its pileus that becomes vivid yellow or pale yellow towards the edges. This species is also known to have a yellow annulus. Amanita hemibapha was firstly reported from Sri Lanka, and then found in China, India and Thailand [3,4,5,8,10,55,56,57]. Morphologically, A. hemibapha is easily confused with A. caesareoides Lj. N. Vassiljeva, A. kitamagotake N. Endo & A. Yamada, A. rubroflava Y.Y. Cui, Q. Cai & Zhu L. Yang and A. subhemibapha Zhu L. Yang, Y.Y. Cui & Q. Cai. However, A. caesareoides, A. kitamagotake, and A. rubroflava differ from A. hemibapha by having a distinctly umbonate pileus, a much darker and reddish tone in the pileus center and relatively broader basidiospores [3,4,58]. Amanita subhemibapha, originally reported from China, differs from A. hemibapha by having a lighter yellowish tone pileus and relatively broader basidiospores (8.0–11.0 × 6.0–8.0 μm) [4]. According to illustrations of the Thai specimens (Figure 3), most of them are orange-red to lemon yellow at the center of the pileus. This feature was different from the original description of A. hemibapha due to the presence of red to orange-red in the center of the pileus. This may be influenced by the phenotypic variability that exists across a wide geographic range. However, the sizes of basidiomata, other macroscopic and microscopic features of the Thai specimens agree well with descriptions of previous studies [3,4,5,10,55,56,57]. Hence, we identify our specimens as A. hemibapha using a combination of morphological and molecular data. ## 3.3.2. Amanita pseudoprinceps Y.Y. Cui, Q. Cai & Zhu L. Yang, Fungal Divers. 91: 59 (2018) (Figure 4) Basidioma medium-sized to very large. Pileus 8.5–16 cm diam., hemispherical, convex to applanate with age, light yellow (4A5–6) to greyish orange (5B3–4) or sometime golden yellow (5B7–8) at center, and becoming yellow white (4A2–3) to white (4A1) towards the margin; universal veil on pileus absent; margin striate (0.1–0.3 R), non-appendiculate; context 9.5–13.5 mm wide, white (1A1), unchanging. Lamellae free, crowded, white to cream white (1A1–2); lamellulae truncate. Stipe 11.5–17.2 × 1.1–1.9 cm, subcylindrical with slightly tapering upwards and apex slightly expanded, white, covered by minute, white (1A1) fibrous squamules; context fistulose to broadly fistulose, white (1A1), Bulb absent. Universal veil on stipe base saccate, membranous, up to 7 cm high, white (1A1). Partial veil apical, membranous, white (1A1), becoming fragile or disappear with age. Figure 4: Amanita pseudoprinceps SDBR-CMUSTO-2019-472 (a), SDBR-CMUNK0775 (b), SDBR-CMUNK0853 (c) and SDBR-CMUNK0783 (d). Basidiomata (a–d). Basidiospores (e). Basidia (f). Scale bars: (a–d) = 5 cm; (e) = 10 μm; (f) = 15 μm. Lamellar trama bilateral, divergent; mediostratum 40–75 μm wide, filamentous hyphae abundant, 2–12 μm wide; fusiform to ellipsoidal inflated cells 85–213 × 12–26 μm; vascular hyphae scarce to locally abundant. Subhymenium 30–50 μm thick in 2–3 layers, with subglobose to ellipsoidal or irregular cells, 12–33 × 10–26 μm. Basidia 36–53 × 12–18 μm, clavate, 4-spored with sterigmata 3–6 μm long; clamps present at base. Basidiospores (9.0–) 9.5–12.5 (–13.0) × (8.0–) 8.5–12.0 (–12.5) μm, $Q = 1.00$–1.20 (1.22) μm, Qm = 1.10 ± 0.06, globose to subglobose, sometimes broadly ellipsoid, inamyloid, hyaline, thin-walled, smooth; apiculus small. Lamellar edge sterile; filamentous hyphae 2–6 μm wide, hyaline, thin-walled; inflated cells, with subglobose to ellipsoidal, 12–35 × 8–34 μm, single and terminal or in chains of 2–3, hyaline, thin-walled. Pileipellis 85–160 μm thick; 2-layered, upper layer 45–80 μm thick, filamentous hyphae 2–5 μm wide, gelatinized, branching, thin-walled, hyaline; lower layer 40–80 μm thick, filamentous hyphae 2–8 (–15) μm wide, branching, thin-walled, hyaline to light yellow; vascular hyphae rare. Inner surface of universal veil on stipe base filamentous hyphae dominant 1–8 μm wide, hyaline to light yellow, thin-walled, branching; inflated cells, with subglobose, fusiform to clavate, 50–93 × 15–52 μm, hyaline, thin-walled, mostly terminal or sometimes in chains of 2–3; vascular hyphae rare. Outer surface of universal veil on stipe base similar to structure of inner part, but presenting more abundant inflated cells. Stipe trama longitudinally acrophysalidic; filamentous, undifferentiated hyphae 2–7 μm wide, thin-walled, frequently branching; acrophysalides 100–233 × 23–45 μm, thin-walled; vascular hyphae rare. Partial veil filamentous hyphae very abundant, 1–7 μm wide, hyaline, thin-walled; inflated cells scarce to locally anundant, globose, subglobose to ellipsoidal, 12–70 × 12–35 μm, hyaline to light yellow, thin-walled; vascular hyphae rare. Clamp connections present in all tissues of basidioma. Habitat: Solitary to scattered on soil in tropical deciduous forests dominated by Dipterocarpus and Shorea. Distribution: known from China [4] and Thailand (this study). Specimens examined: Thailand, Chiang Mai Province, Mae Taeng District, 19°05′38.2″ N 98°52′44.4″ E, alt. 1105 m, 7 August 2019, Yuan S.L., STO-2019-395 (SDBR-CMUSTO-2019-395); Yuan S.L., STO-2019-397 (SDBR-CMUSTO-2019-397); 19°07′45.0″ N 98°45′51.0″ E, alt. 1421 m, 9 August 2019, Yuan S.L., STO-2019-470 (SDBR-CMUSTO-2019-470); Yuan S.L., STO-2019-472 (SDBR-CMUSTO-2019-472). Doi Saket District, 18°53′2″ N 99°9′17″ E, alt. 343 m, 26 July 2020, Kumla J. and. Suwannarach N., CMUNK0783 (SDBR-CMUNK0783), 2 August 2022, Kumla J. and. Suwannarach N., CMUNK0853 (SDBR-CMUNK0853); Lumphun Province, Mae Tha District, 18°27′41″ N 99°10′30″ E, alt. 427 m, 25 July 2020, Kumla J. and. Suwannarach N., CMUNK0775 (SDBR-CMUNK0775). Remarks: Morphologically, A. pseudoprinceps resembles A. princeps Corner & Bas by having a similar yellowish-brown pileus and margin striates (about 0.2–0.3 R). However, A. princeps presents the larger basidiomata, as well as an outer layer of volval remnants on the stipe cracks and peels in pale buff thin patches [4,54,59]. According to the phylogenetic analysis, our seven samples cluster together with three other samples of A. pseudoprinceps and form a well-supported clade that presents a sister clade with A. aporema Boedijn. Meanwhile, these two species possess a similar brown tone pileus. However, A. aporema has a smaller (6–10 cm) but much darker pileus, as well as obviously longer margin striates (0.5–0.6 R) [4,54,60]. ## 3.3.3. Amanita rubromarginata Har. Takah., Mycoscience 45: 372 (2004) (Figure 5) Basidioma medium-sized to large. Pileus 6.0–10.0 cm diam., convex to plano-convex with the center depressed, reddish orange (7B7) over disk, or sometime orange red (8B7–8) at center and becoming light orange (5A4–5) towards the margin; universal veil on pileus absent; margin striate (0.4–0.5 R), non-appendiculate; context 4.5–8.0 mm wide, yellowish white (3A2), unchanging. Lamellae free, crowded, pale yellow to light yellow (4A3–4), with lamellar edges reddish orange (7B7–8); lamellulae truncate. Stipe 13.7–20.0 × 1.0–1.8 cm, subcylindrical with slightly tapering upwards, yellow (3A6–7), densely covered by reddish yellow to deep yellow (4A7–8) squamules; context broadly fistulose, yellowish white (3A2) to white (3A1). Bulb absent. Universal veil on stipe base saccate, membranous, up to 5 cm high, white (1A1). Partial veil subapical to apical, membranous, dark orange (5A7–8) to orange (6A6–7). Figure 5: Amanita rubromarginata SDBR-CMUSTO-2019-451 (a), SDBR-CMUSTO-2019-452 (b), SDBR-CMUNK0780 (c) and SDBR-CMUNK0854 (d). Basidiomata (a–d). Basidiospores (e). Basidia (f). Scale bars: (a–d) = 5 cm; (e) = 5 μm; (f) = 15 μm. Lamellar trama bilateral, divergent; mediostratum 20–25 μm wide, filamentous hyphae abundant, 2–11 μm wide; fusiform to ellipsoidal inflated cells 60–153 × 15–27 μm; vascular hyphae scarce. Subhymenium 25–30 μm thick in 1–3 layers, with subglobose to ellipsoidal or irregular cells, 8–18 × 5–13 μm. Basidia 32–46 × 8–13 μm, clavate, 4-spored with sterigmata 3–4 μm long; clamps present at base. Basidiospores 7.0–9.5 (–10.0) × 6.0–7.0 (–8.0) μm, Q = (1.08–) 1.13–1.50 μm, Qm = 1.28 ± 0.11, subglobose to broadly ellipsoid or ellipsoid, inamyloid, hyaline, thin-walled, smooth; apiculus small. Lamellar edge sterile; filamentous hyphae 3–7 μm wide, hyaline, thin-walled; inflated cells, with globose, pyriform to clavate, 15–46 × 12–27 μm, hyaline, thin-walled. Pileipellis 80–130 μm thick; 2-layered, upper layer 25–40 μm thick, filamentous hyphae 1–6 μm wide, gelatinized, branching, thin-walled, hyaline; lower layer 50–100 μm thick, filamentous hyphae 3–8 μm wide, branching, thin-walled, hyaline to light yellow; vascular hyphae rare. Inner part of universal veil on stipe base filamentous hyphae dominant 2–11 μm wide, hyaline to light yellow, thin-walled, branching; inflated cells, with subglobose, ovoid to clavate, 30–72 × 10–70 μm, hyaline, thin-walled; vascular hyphae rare. Outer surface of universal veil on stipe base similar to structure of inner part, but presenting more abundant inflated cells. Stipe trama longitudinally acrophysalidic; filamentous, undifferentiated hyphae 1–6 μm wide, thin-walled, frequently branching; acrophysalides 150–295 × 33–53 μm, thin-walled; vascular hyphae rare. Partial veil filamentous hyphae very abundant, 2–11 μm wide, hyaline, thin-walled; inflated cells scarce to locally abundant, ellipsoidal to clavate, 45–110 × 10–16 μm, hyaline to light yellow, thin-walled; vascular hyphae rare. Clamp connections present in all tissues of basidioma. Habitat: Solitary to scattered on soil in tropical deciduous forests dominated by Dipterocarpus and Shorea. Distribution: known from China [4], Japan [61,62], and Thailand [52], this study. Specimens examined: Thailand, Chiang Mai Province, Mae Taeng District, 19°06′53.3″ N 98°44′22.7″ E, alt. 1718 m, 8 August 2019, Yuan S. Liu, STO-2019-451 (SDBR-CMUSTO-2019-451); STO-2019-452 (SDBR-CMUSTO-2019-452); Doi Saket District, 18°53′2″ N 99°9′17″ E, alt. 343 m, 2 August 2022, Kumla J. and Suwannarach N., CMUNK0854 (SDBR-CMUNK0854); Lumphun Province, Mae Tha District, 18°27′41″ N 99°10′30″ E, alt. 427 m, 25 July 2020, Kumla J. and Suwannarach N., CMUNK0780 (SDBR-CMUNK0780). Remarks: Morphologically, A. rubroflava is easily confused with A. rubromarginata. However, A. rubroflava differs from A. rubromarginata by having a distinctly umbonate pileus and larger basidiospores (8.0–10.0 × 6.5–8.0 μm) [4]. Phylogenetically, Amanita javanica (Corner & Bas) Oda, Tanaka & Tsuda is closely related to A. rubromarginata. Meanwhile, both these two species share similar characteristics, such as an orange-red tone pileus and reddish yellow squamules covering their stipes. However, A. javanica has a distinctly umbonate pileus, while A. rubromarginata does not appear to display this characteristic [4,54,59,62]. ## 3.3.4. Amanita subhemibapha Zhu L. Yang, Y.Y. Cui & Q. Cai, Fungal Divers. 91: 65 (2018) (Figure 6) Basidioma medium-sized to large. Pileus 6.0–10.0 cm diam., convex to plano-convex, lacking an umbo at center, purely orange (5B5–8) when young, but becoming orange (5B5–8) at center and yellow (4A6–8) to yellowish (3A3–6) at margin when mature; universal veil on pileus absent; margin striate (0.25–0.3 R), non-appendiculate; context 4.5–5.0 mm wide, yellow (4A6–8) to yellowish (3A3–6), unchanging. Lamellae free, crowded, white (1A1) to cream (1A4–6), with lamellar edges yellow (4A6–8); lamellulae truncate. Stipe 5–15 × 0.7–1.5 cm, subcylindrical with slightly tapering upwards, with apex slightly expanded, yellow (4A6–8) to orange (5B5–8), with its surface covered with concolorous, snakeskin-shaped squamules; context white (1A1), hollow in center. Bulb absent. Universal veil on stipe base saccate, membranous, up to 5 cm high 3, white (1A1). Partial veil apical to subapical, yellow (4A6–8) to orange (5B5–8). Figure 6: Amanita subhemibapha SDBR-CMU0781 (a) and SDBR-CMU0855 (b). Basidiomata (a,b). Basidiospores (c). Basidia (d). Scale bars: (a,d) = 5 cm; (c) = 10 μm; (d) = 15 μm. Lamellar trama bilateral, divergent; mediostratum 25–70 μm wide, filamentous hyphae abundant, 2–7 μm wide; ellipsoid, fusiform to clavate inflated cells 30–80 × 10–27 μm; vascular hyphae scarce. Subhymenium 30–50 μm thick in 2–3 layers, with subglobose to ellipsoid cells, 10–25 × 8–20 μm. Basidia 40–50 × 9–12 μm, clavate, 4-spored with sterigmata 3–5 μm long; clamps present at base. Basidiospores (7.0–) 8.0–11.0 × 6.5–8.5 (–9.0) μm, $Q = 1.15$–1.53 (–1.65), Qm = 1.34 ± 0.08, broadly ellipsoid to ellipsoid, inamyloid, hyaline, thin-walled, smooth; apiculus small. Lamellar edge sterile; filamentous hyphae 2–4 μm wide, hyaline, thin-walled; inflated cells, with subglobose to ellipsoid or sphaeropedunculate, 8–45 × 8–20 μm, single and terminal or in chains of 2–3, hyaline, thin-walled. Pileipellis 90–170 μm thick; 2-layered, upper layer 30–145 μm thick, filamentous hyphae 2–5 μm wide, gelatinized, branching, thin-walled, hyaline; lower layer 30–55 μm thick, filamentous hyphae 3–8 (–10) μm wide, branching, thin-walled, hyaline to light yellow; vascular hyphae scarce. Inner surface of universal veil on stipe base filamentous hyphae dominant 2–10 μm wide, hyaline to light yellow, thin-walled, branching; inflated cells, with subglobose, fusiform to ellipsoid, 55–100 × 20–70 μm, hyaline, thin-walled, mostly terminal or sometimes in chains of 2–3; vascular hyphae rare. Outer surface of universal veil on stipe base similar to structure of inner part, but presenting more abundant inflated cells. Stipe trama longitudinally acrophysalidic; filamentous, undifferentiated hyphae 2–10 (–15) μm wide, thin-walled, frequently branching; acrophysalides 60–260 × 25–65 μm, thin-walled; vascular hyphae rare. Partial veil filamentous hyphae very abundant, 2–10 μm wide, hyaline, thin-walled; inflated cells scarce to locally abundant, subglobose, fusiform to clavate, 20–100 × 10–35 μm, hyaline to light yellow, thin-walled; vascular hyphae rare. Clamp connections present in all tissues of basidioma. Habitat: Solitary to scattered on soil in subtropical broad-leaved or mixed forests with Dipterocarpaceae, Fagaceae, and Pinaceae. Distribution: known from China [4] and Thailand (this study). Specimens examined: Thailand, Chiang Mai Province, Doi Saket District, 18°53′2″ N 99°9′17″ E, alt. 343 m, 26 July 2021, Kumla J. and Suwannarach N., CMUNK0804 (SDBR-CMUNK0804); 18°53′2″ N 99°9′17″ E, alt. 343 m, 2 August 2022, Kumla J. and Suwannarach N., CMUNK0855 (SDBR-CMUNK0855); Lumphun Province, Mueang District, Chiang Mai University Haripunchai Campus, 18°32′34″ N 99°9′231″ E, alt. 450 m, 25, July, 2020, Suwannarach N., CMUNK0781 (SDBR-CMUNK0781); Mae Tha District, 18°27′41″ N 99°10′30″ E, alt. 427 m, 27 August 2020, Kumla J. and Suwannarach N., CMUNK0735 (SDBR-CMUNK0735). Remarks: Morphologically, A. subhemibapha is easily confused with A. hemibapha, A. javanica and A. kitamagotake. Morphological comparisons of A. hemibapha and A. subhemibapha have been included in our remarks pertaining to A. hemibapha. Amanita javanica differs from A. subhemibapha by having a broadly umbonate and much darker yellow tone in the center of the pileus, longer tuberculate striates (0.4–0.5 R) on the margins and smaller basidiospores (7.5–9.0 × 5.8–7.0 μm) [54]. Alternatively, A. kitamagotake differs from A. subhemibapha by having an umbonate pileus and narrower basidiospores (9.0–13.5 × 6.5–8.5 μm) [58]. Based on multigene phylogeny, A. subhemibapha forms a sister clade with A. fuscoflava Zhu L. Yang, Y.Y. Cui & Q. Cai. However, A. fuscoflava has a dark brown tone in the pileus center, much longer margin striates (0.5–0.7 R) and relatively narrower basidiospores (8.5–10.5 × 6.0–7.0 μm) [4]. Traditionally, morphological characteristics have been the primary basis for the identification of Amanita species [7,8,11,32]. However, identification can be difficult due to the high phenotypic variability that is influenced by differing environmental conditions and geographic distributions. Therefore, it is crucial to identify the Amanita species using DNA-based methods. The current classification of the genus Amanita is based on combined data on their morphological characteristics and molecular data. Moreover, multi-gene molecular phylogeny has provided researchers with a powerful tool for the identification of the Amanita species [4,14,36,52,53,54,58]. In this present study, specimens of the edible Amanita species collected in northern Thailand were identified as A. hemibapha, A. pseudoprinceps, A. rubromarginata, and A. subhemibapha based on morphological characteristics and multi-gene phylogenetic analyses. The results of morphological comparisons of four edible Amanita species in this study are presented in Table 3. Morphologically, the color of the pileus and the larger spore size found in A. pseudoprinceps clearly differentiate it from those other three species. Additionally, the yellow annulus and narrow spores in A. hemibapha clearly distinguish it from A. rubromarginata and A. subhemibapha. Remarkably, A. rubromarginata has a redder and more of an orange-red-shaded pileus and annulus than A. subhemibapha. The multi-gene phylogenetic analysis also supports the determination that A. hemibapha, A. pseudoprinceps, A. rubromarginata, and A. subhemibapha are different species. Four Amanita species obtained from natural forests, roadsides, and local markets in this study belonged to the Amanita section Caesareae. This section is a highly regarded edible mushroom in the genus Amanita [4,16,17,18,19]. Prior to this study, the toxicological analysis of A. hemibapha showed that no amatoxins and phallotoxins had been discovered and that it should be regarded as an edible species [63]. However, further research is required to fully understand the edibility and safety of A. pseudoprinceps, A. rubromarginata, and A. subhemibapha based on their toxicological studies. As a result, our study should be considerably important and highly valuable in terms of stimulating deeper investigations of edible macrofungi in Thailand. It will also help researchers in understanding the distribution and ecology of Amanita. ## 3.4. Nutritional Analysis A total of six samples of four edible Amanita species (namely A. hemibapha, A. pseudoprinceps, A. rubromarginata, and A. subhemibapha) obtained in this study have been included in the experiments. In this study, the fruiting bodies of edible Amanita were analyzed for their nutritional composition, which included ash, carbohydrate, protein, fat and fiber. The results are presented in Table 4. The results indicate that the protein contents in A. pseudoprinceps and A. subhemibapha were significantly higher than A. hemibapha and A. rubromarginata. The highest content of fiber was found in A. pseudoprinceps. It was determined that A. rubromarginata had the highest ash content. In addition, the carbohydrate content in A. hemibapha was significantly higher than the other Amanita species. The highest fat content was obtained in A. rubromarginata, but this value was not found to be significantly different from the fat content of A. hemibapha. These results were consistent with previous studies, which reported that edible wild mushrooms to be natural sources of nutrients for human diets (high-protein and low-fat contents), while the nutritional composition of each mushroom is dependent upon the mushroom species [20,22,64,65]. The amounts of ash, carbohydrate, protein, fat, and fiber of the four edible Amanita species in this study were within the ranges mentioned in previous reports of edible Amanita. Accordingly, the ash (0.11–$11.82\%$ dry weight), carbohydrate (22.16–$61.70\%$ dry weight), protein (10.11–$45.65\%$ dry weight), fat (0.17–$17.52\%$ dry weight) and fiber (1.18–$30.30\%$ dry weight) contents were found in various edible Amanita species, namely A. caesarea, A. calyptroderma, A. fulva, A. hemibapha, A. princeps, A. rubescens, and A. zambiana [66,67,68,69,70,71,72,73,74,75]. When compared to the findings of other previously published reports, the protein content of the Amanita species obtained in this study was relatively higher than those of A. calyptroderma [75] and A. loosei [69]. With regard to the outcomes of this study, this is the first comprehensive report on the nutritional composition of A. pseudoprinceps, A. rubromarginata, and A. subhemibapha. ## 3.5. Determination of Total Phenolic Content The total phenolic content of each extract of Amanita in this study is presented in Table 5. It was found that the total phenolic contents ranged from 0.94–1.62 mg GAE/g dw. The highest value of total phenolic content was found in the extract of A. pseudoprinceps, followed by the extracts of A. subhemibapha and A. hemibapha. The lowest value of total phenolic content was found in the extract of A. rubromarginata. Previous findings support the results of this study in that the amount of phenolic contents of edible wild mushrooms varied within different ranges and was dependent upon the various mushroom species [45,76,77,78]. According to our results, the amounts of total phenolic content obtained in this study were within the previously reported ranges of phenolic content found in edible wild mushrooms and varied from 0.39–38.44 mg GAE/g dw [76,77,78,79]. The total phenolic contents in the methanolic extracts of A. caesarea [79], A. fulva [74], A. hemibapha [80], A. javanica [81], A. ovoidea [82], A. princeps [80,81], and A. zambiana [73] were reported as 0.64, 0.39, 8.5, 18.01, 0.50, 14.29–16.80 and 8.76 mg GAE/g dw, respectively. Additionally, the total phenolic contents in the ethanolic extracts of A. javanica and A. princeps were 12.79 and 16.52 mg GAE/g dw, respectively [81]. When compared to the results of previously published reports, the phenolic contents of the ethanolic extracts of A. hemibapha, A. pseudoprinceps, A. rubromarginata, and A. subhemibapha obtained in this study have been found to be relatively higher than those of methanolic extracts of A. caesarea, A. fulva and A. ovoidea [74,79,82], while they were relatively lower than extracts of A. javanica, A. princeps and A. zambiana [73,81]. However, the phenolic content of A. hemibapha obtained in this study was lower than that of the previous report of Butkhup et al. [ 80]. It can be concluded from our experiments that, similarly to the results of previous studies, the total content of phenolic can be influenced by different phenolic compounds found in mushroom extracts, along with the extractability of the different solvents used in the preparation process [45,81,83,84]. According to several previous studies, catechin, р-coumaric acid, gallic acid, hydroxycinnamic acid, quercetin, protocatechuic acid, rosmarinic acid, and syringic acid were found to be the major phenolic components in the ethanolic extracts of edible wild mushrooms [45,85,86,87]. Some previous investigations revealed that the Folin–Ciocalteu assay, a method typically used for detection and quantification of total phenolic content, might be unsuited for total phenolic content measurement in complex biological samples due to high interference from various reducing compounds contained in samples [88,89,90]. The effectiveness of the Folin–Ciocalteu assay is also hampered by its limited suitability for some phenolic compounds [89,90]. Therefore, the measurement of total phenolic content in this study will still be assessed using other techniques such as high-performance liquid chromatography (HPLC) or liquid chromatography–mass spectrometer mass spectrometry (LC-MS) for further studies to characterize and identify the phenolic compounds contained in mushroom extracts. ## 3.6. Antioxidant Assay A single method cannot fully determine the antioxidant activity of mushroom extracts. Thus, in this study, three methods, namely ABTS, DPPH, and FRAP assays, were used to determine the antioxidant activity of the ethanolic extracts of different samples of edible Amanita species. The ABTS and DPPH values were determined by evaluating the scavenging abilities of ABTS and DPPH radicals, respectively (by measuring the decrease in ABTS and DPPH radical absorption after exposure to radical scavengers) [91,92]. The FRAP assay was used to measure the conversion of the ferric form (Fe3+) to the ferrous form (Fe2+) [92]. In this study, the highest values of DPPH activity were observed in the extract of the A. pseudoprinceps, followed by the extracts of A. hemibapha and A. subhemibapha (Table 5). The lowest value of DPPH activity was observed in the extract of A. rubromarginata. Furthermore, the results indicated that all extracts exhibited positive results in terms of the ABTS and FRAP assays, while the ABTS values varied from 0.56 to 1.00 mg TE/g dw (Table 5). The highest ABTS value was observed in the extract of A. pseudoprinceps, followed by the extracts of A. hemibapha, A. subhemibapha, and A. rubromarginata. In the FRAP system, the extract of A. pseudoprinceps had significantly higher FRAP values than the extracts from the other samples (Table 5). The results from the ABTS, DPPH, and FRAP assays were similar and demonstrated that the extract of A. pseudoprinceps exhibited significantly high antioxidant activity. The lowest level of antioxidant activity was found in the extract of A. rubromarginata. According to Pearson correlation ($p \leq 0.05$), the total phenolic content of mushroom extract samples showed a significant strong positive correlation with DPPH ($r = 0.975$) and FRAP ($r = 0.948$) activities (Table 6). However, the positive correlation between the total phenolic content and ABTS activity ($r = 0.762$) was not statistically significant. All extracts of the four edible Amanita species exhibited antioxidant activities. These results are consistent with those of previous studies which reported that the extracts of wild mushrooms (e.g., genera Amanita, Boletus, Cantharellus, Lactarius, and Russula) exhibited antioxidant activities that varied according to the mushroom species [45,66,78,80,81,82,83]. Furthermore, recent research has indicated that wild mushrooms contain dietary ingredients that are alternative sources of natural antioxidants [45,77,93]. In this study, A. pseudoprinceps exhibited the highest level of antioxidant activity due to the fact that it possesses high total polyphenol content. This determination is supported by the results of previous studies, which reported that high phenolic content is responsible for the high antioxidant activity [45,83,94]. Prior to this present study, the antioxidant activities of A. caesarea, A. calyptroderma, A. hemibapha, A. javanica, A. loosei, A. ovidea, and A. princeps have been reported from a variety of assays employing different mechanisms including lipid peroxidation, metal chelation, reducing power and scavenging activity, among others [69,75,79,80,81]. However, variations in the assays themselves, and the results they express, make it difficult to compare the outcomes obtained in this study with those of previous studies. ## 3.7. Determination of α-Glucosidase Inhibitory Activity Importantly, α-glucosidase is one of the key enzymes related to hyperglycemia by leading to an increase in blood glucose levels [95,96]. Therefore, inhibition of the function of this enzyme can reduce and control the risk of hyperglycemia. In this study, the α-glucosidase inhibition activity of the extracts of each edible Amanita species was investigated in terms of the inhibition percentage. The results were then compared with those of acarbose (anti-diabetic drug). The results then revealed that all extract samples exhibited α-glucosidase inhibition activity, while the value of the inhibition percentage varied according to the differences in the extract samples (Table 5). The value of α-glucosidase inhibition activity in the extract samples varied from $19.26\%$ to $31.44\%$ inhibition. However, all mushroom extracts were found to be less effective than acarbose, a synthetic standard Inhibitor of α-glucosidase ($44.06\%$ inhibition at concentration of 1 mg/mL). These results are supported by those of previous studies, which reported that the extracts of certain edible wild mushrooms (e.g., Amanita, Astraeus, Boletus, Lactarius, Phlebopus, Russula, Suillus, and Tylopilus) have potential as natural α-glucosidase inhibitors. Accordingly, the α-glucosidase inhibition activity varied from 9.72–$78.75\%$ for each different mushroom species [45,97,98]. In this study, the amounts of α-glucosidase inhibitory activity obtained in this study were within the ranges reported from previous studies. Compared with the outcomes of a report conducted by Pongkunakorn et al. [ 97], the α-glucosidase inhibitory activity of the methanolic extracts of A. hemibapha (19.26 and $20.37\%$) and A. rubromarginata ($20.28\%$) obtained in this study were lower than the α-glucosidase inhibitory activity of the water extracts of A. hemibapha and A. princeps, which were reported at $22.66\%$ and $25.54\%$, respectively. Interestingly, the α-glucosidase inhibitory activity of the methanolic extracts of A. pseudoprinceps obtained in this study was higher than the α-glucosidase inhibitory activity of the water extracts of both A. hemibapha and A. princeps [97]. Several previous studies have reported that the use of different solvents resulted in different patterns of active compounds in mushroom extracts, which were related to biological activities including α-glucosidase inhibitory activity [83,84,97,98]. Importantly, this study is the first report on the α-glucosidase inhibition activities of A. pseudoprinceps, A. rubromarginata, and A. subhemibapha. This study found that the extracts of A. pseudoprinceps displayed a high level of α-glucosidase inhibition activity over the other extracts, which could be related to their high total phenolic content. Additionally, the total phenolic content of all mushroom extracts and α-glucosidase inhibitory activity were shown to be significantly correlated by Pearson correlation ($p \leq 0.05$) (Table 6). These results were similar to those of previous studies [45,99,100], which revealed that the α-glucosidase inhibitory activity of natural substances is strongly correlated with the phenolic compound content. ## 4. Conclusions The edible Amanita specimens collected in northern Thailand were identified as A. hemibapha, A. pseudoprinceps, A. rubromarginata, and A. subhemibapha based on the relevant morphological characteristics and multi-gene phylogenetic analyses. These four Amanita species were selected for further experiments, wherein their nutritional composition, total phenolic content, antioxidant activities, and α-glucosidase inhibitory activities were evaluated. All Amanita species were high in protein and carbohydrate but low in fat content. Additionally, the methanolic extracts of these four Amanita species contained varied amounts of total phenolic content and exhibited varied results in terms of their antioxidant and α-glucosidase inhibitory activities. The highest levels of antioxidant and α-glucosidase inhibitory activities were found in the methanolic extract of A. pseudoprinceps. The findings of this investigation provide valuable information on the nutrient content, total phenolic content, and the antioxidant and α-glucosidase inhibitory potential of the edible Amanita species found in northern Thailand. Therefore, our results suggest that these four edible Amanita species can be representative of an alternative food source. These species are also a good source of natural antioxidants and exhibit potential to naturally inhibit α-glucosidase for human health benefits. However, future studies should be implemented to conduct a comprehensive mineral analysis and to identify the phenolic profiles present in each edible Amanita species. ## References 1. Persoon C.H.. Tentamen Dispositionis Methodicae Fungorum (1797.0) 2. Bresinsky A., Besl H.. 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--- title: Comparative Genomics of Halobacterium salinarum Strains Isolated from Salted Foods Reveals Protechnological Genes for Food Applications authors: - Alessandra Fontana - Irene Falasconi - Paolo Bellassi - Elisabetta Fanfoni - Edoardo Puglisi - Lorenzo Morelli journal: Microorganisms year: 2023 pmcid: PMC10058572 doi: 10.3390/microorganisms11030587 license: CC BY 4.0 --- # Comparative Genomics of Halobacterium salinarum Strains Isolated from Salted Foods Reveals Protechnological Genes for Food Applications ## Abstract Archaeal cell factories are becoming of great interest given their ability to produce a broad range of value-added compounds. Moreover, the Archaea domain often includes extremophilic microorganisms, facilitating their cultivation at the industrial level under nonsterile conditions. Halophilic archaea are studied for their ability to grow in environments with high NaCl concentrations. In this study, nine strains of Halobacterium salinarum were isolated from three different types of salted food, sausage casings, salted codfish, and bacon, and their genomes were sequenced along with the genome of the collection strain CECT 395. A comparative genomic analysis was performed on these newly sequenced genomes and the publicly available ones for a total of 19 H. salinarum strains. We elucidated the presence of unique gene clusters of the species in relation to the different ecological niches of isolation (salted foods, animal hides, and solar saltern sediments). Moreover, genome mining at the single-strain level highlighted the metabolic potential of H. salinarum UC4242, which revealed the presence of different protechnological genes (vitamins and myo-inositol biosynthetic pathways, aroma- and texture-related features, and antimicrobial compounds). Despite the presence of genes of potential concern (e.g., those involved in biogenic amine production), all the food isolates presented archaeocin-related genes (halocin-C8 and sactipeptides). ## 1. Introduction Halophilic archaea are studied for their ability to grow in environments with high NaCl concentrations. In particular, the class Halobacteria comprises microorganisms that require a NaCl concentration of at least 1.5 M for proliferation and that show optimal growth at 3.5–4.5 M [1]. Its members are ubiquitous in environments containing NaCl concentrations up to saturation, such as solar salterns and soda lakes [2,3,4], but can also live in marine environments and in salted food products [5,6,7,8]. The vast majority of the known microorganisms cannot proliferate at water activity (aw) values below 0.90 [9]. However, the most extremophilic species can undergo cell division at aw down to 0.61; indeed, some xerophilic fungi can grow and/or germinate within a aw range of 0.755–0.605 [10]. The ability of extreme halophiles to grow at aw values such as that of saturated NaCl relies on different adaptation strategies to balance cellular osmotic stress [11,12]. For instance, halophilic archaea counteract the external low aw by accumulating K+ and, in some cases, Na+ ions [13]. Moreover, the enzymes of these halophiles can work at high NaCl concentrations since their proteins include a high content of acidic amino acids (i.e., glutamate and aspartate). To this extent, the first sequenced genome Halobacterium sp. NRC-1 allowed researchers to explore more in depth the mechanisms behind its ecological adaptation to hypersaline brine. Genotypic characterization indeed revealed that most of the predicted proteins were highly acidic and that the negatively charged residues were mostly located at the protein surface. This feature was associated with the function of increasing their solubility and stability in high-salt-concentration environments, making halophile enzymes active at aw values equal to or below 0.755 [11,14,15,16]. The neutron spectroscopy of the proteome of Halobacterium salinarum showed that protein structure is strongly affected by high NaCl since K+ concentrations below 2.2 M induce their misfolding and precipitation [17]. Haloarchaea are mostly aerobes, but a few species can grow anaerobically by using arginine and nitrate as terminal electron acceptors [1]. Halophilic members were initially found to be spoilage microorganisms in salted products, such as salted codfish and brine-cured hides in the leather industry. However, they have also been utilized in food processing as ameliorating microorganisms; for instance, they have been exploited to accelerate fish sauce fermentation [18] and to improve the safety and quality of salted anchovies [19]. Indeed, it has been highlighted that salted anchovies inoculated with halophiles showed lower loads of naturally present staphylococci, Enterobacteriaceae, and lactic acid bacteria. Moreover, a decrease in the histamine content and an improvement in the organoleptic characteristics have also been evidenced [19]. Other than this, several studies have been carried out to assess how halophilic archaea could play a key role in the fermentation process of fish products, showing that this last role is promoted by specific enzymes, such as serine proteases, that can be active even in environments characterized by high NaCl concentrations [20]. The most well-studied member of the class Halobacteria is Halobacterium salinarum, which is the type species of the genus Halobacterium, and it was first isolated from salted codfish [21,22]. Since their discovery, halophilic archaea have attracted great scientific interest mainly due to their extraordinary ability to grow at high salinity levels, prompting many studies focusing on these microorganisms’ proteins, lipids, and enzymes [16]. Indeed, most of their proteins and enzymes maintain functionality even under the presence of 10–$35\%$ NaCl and under temperatures up to 100 °C at which most bacterial proteins become denatured and/or nonfunctional [23]. To reveal the molecular mechanisms behind the physiological response of Halobacteria in extreme environments, H. salinarum NRC-1 has represented a model microorganism used to elucidate evolutionary adaptation to such conditions (high salinity and low water activity). Indeed, the poor characterization of extreme halophiles can be bypassed with the exploitation of the increasing presence of genome sequences to develop system-level models able to predict regulatory and functional connections between genes and key abiotic factors in hypersaline environments [24]. Currently, archaeal cell factories are becoming of high interest given their abilities in producing a large variety of value-added compounds; moreover, the fact that their members are often extremophilic microorganisms facilitates their cultivation at the industrial level under nonsterile conditions using inexpensive feedstocks [25]. Up to date, commercially available archaeal products are all derived from halophiles and are bacteriorhodopsin, bacterioruberin, diether/tetraether lipids, and squalene [25]. However, other archaeal applications are under investigation at different technology readiness levels (TRLs), such as for the production of carotenoids, polyhydroxyalkanoates, methane, and biohydrogen [25]. Halotolerant microorganisms specifically play an important role in food biotechnology for the production of fermented foods and food supplements. Indeed, they produce different compounds that characterize the food product in terms of aroma, flavor, and appearance as well as in terms of nutritional value (vitamins and derivatives) [25,26]. Furthermore, their capability to produce antimicrobial peptides (i.e., archaeocins) has also been assessed [27]. It is also important to highlight that the tolerance of haloarchaea to environments with low water activity is not only an advantage in the food sector, but it can also be exploited in arid soils used for crop production by mediating the plant–microbe and plant–insect interactions [12]. In this study, we investigated 19 H. salinarum strains isolated from different ecological niches (i.e., salted foods, animal hides, and solar saltern sediments) to highlight the specific genetic signatures of adaptation to the different environments. In addition, the genome mining of salted food isolates was further deepened to evaluate the presence of functional and protechnological genes as well as genes of health concern for their possible exploitation as natural starters in salted food products. ## 2.1. Isolation and Molecular Fingerprinting of Halophilic Archaea from Salted Foods Halophilic archaea were isolated from three different types of salted food: sausage casings, salted codfish, and bacon. A total of 10 grams of each sample were mixed with 90 mL of saline water (NaCl concentration of 200 g/L) and were homogenized for 1.5 min at 260 rpm using a Stomacher machine (400 Circulator; International PBI, Milan, Italy). A 1 mL aliquot of this homogenate was serially diluted in 9 mL of Halobacteria medium (DSM 372; Deutsche Sammlung von Mikroorganismen und Zellkulture GmbH, DSMZ) and was used for microbiological analyses. Sample suspension aliquots of 100 µL were plated on duplicate agar plates made with DSM 372 medium (yeast extract 5 g/L, casamino acids 5 g/L, Na-glutamate 1 g/L, KCl2 g/L, Na3-citrate 3 g/L, MgSO4 × 7 H2O 20 g/L, NaCl 200 g/L, FeCl2 × 4 H2O 0.036 g/L, MnCl2 × 4 H2O 0.00036 g/L, and agar 20 g/L). The plates were incubated at 37 °C for 2 weeks. Representative colonies were selected depending on color, size, and morphology. DNA was extracted from isolated purified colonies using microLYSIS®-Plus (MicroZone Limited) following the manufacturer’s protocol. To identify unique isolates, randomly amplified polymorphic DNA polymerase chain reaction (RAPD-PCR) was performed using GTG-5 (5′-GTGGTGGTGGTGGTG-3′) primer [28]. The PCR fragment profiles were analyzed using Fingerprinting II software (Bio-Rad Laboratories, Hercules, CA, USA). Similarities between band profiles were determined by calculating the Pearson correlation coefficient, and cluster analyses were performed using the provided unweighted pair group method with arithmetic mean (UPGMA). A correlation coefficient of $85\%$ was selected to distinguish the clusters. One representative isolate from each cluster was amplified for 16S rRNA gene using the primers 7F (5′-TTCCGGTTGATCCYGCCRG-3′) and 1492R (5′-TACGGYTACCTTGTTACGACTT-3′) for archaea [29]. Amplified 16S rRNA genes were Sanger sequenced and identified through alignment against the NCBI database. ## 2.2. Whole-Genome Sequencing and Comparative Genomics of Selected Halobacterium salinarum Strains Nine identified H. salinarum unique isolates (three per type of salted food considered) were selected for whole-genome sequencing along with the collection strain CECT 395. Genomic DNA was extracted with the MasterPure™ Gram Positive DNA Purification Kit (Lucigen Corporation, Middleton, WI, USA) according to the provided protocol. The quality of the extracted DNA was then checked by means of agarose gel electrophoresis ($0.8\%$), and the quantity was determined using Qubit fluorometer (Life Technologies, Carlsbad, CA, USA). Whole-genome sequencing was then performed with the Illumina MiSeq platform using the TruSeq Nano Kit (Illumina Inc., San Diego, CA, USA) for library preparation (2 × 150 bp). Quality filtering and adaptor removal were carried out using Trimmomatic software (v0.39) [30]. De novo genome assembling was performed with Unicycler in BV-BRC (v3.27.7) [31]. The quality of the assembled genomes was evaluated with QUAST (v4.6.0) [32], whereas the completeness and contamination levels were estimated with CheckM (v1.2.2) [33]. The taxonomic identification of the genome assemblies was further verified through dDDH calculation using the Type Strain Genome Server [34]. Annotation of the genome assemblies was then carried out with Prokka (1.14.6) [35]. Pangenome analysis was performed using Roary (3.13.0) [36] as previously described [37,38] on the 10 sequenced strains along with the 9 publicly available genomes of H. salinarum from the NCBI database (accessed on 30 November 2022) for a total of 19 genome sequences (Table 1). The core gene alignment resulting from Roary was then used in RAxML (8.2.12) to build a maximum likelihood phylogenetic tree. The effect of the isolation source on the genomic content of the strains was evaluated in Past3 (3.26) [39] using a principal coordinates analysis (PCoA) based on Bray–Curtis dissimilarity metrics of the gene presence/absence matrix generated from Roary. Metabolic pathways were analyzed using KEGG annotation within the Comparative Pathway tool in BV-BRC. Bacteriocin-like antimicrobial substances (i.e., archaeocins) were evaluated using BAGEL4 [40]. Antibiotic resistance genes (ARGs) were investigated with the Resistance Gene Identifier (RGI) tool based on CARD Database [41], whereas virulence factor (VF) genes were searched with the Abricate tool (v1.0.1) based on Virulence Factor Database (VFDB) [42]. ## 3.1. Molecular Fingerprinting of Halophilic Archaea Isolates A total of 65 representative colonies were isolated from the 3 types of salted food investigated. Specifically, 46 isolates were obtained from sausage casings, 10 isolates were obtained from salted codfish, and 9 isolates were obtained from bacon. RAPD-PCR fingerprinting allowed us to distinguish 33 different profiles having a maximum similarity index of $85\%$ as determined through UPGMA clustering (Figure S1). The 33 unique strains were subjected to 16S rRNA gene sequencing, revealing their belonging to the H. salinarum species (Table S1). From the RAPD-PCR profiles, it was also shown that a clusterization of the isolates originated from the sausage casings, whereas the bacon and salted codfish isolates did not evidence a distinct separation (Figure S1). From the fingerprinting results, three representative unique strains of each isolation source were selected for an in-depth characterization of the strains at the genome level. ## 3.2. Comparative Genomic Analysis of H. salinarum Strains Considering the general genomic features, based on the isolation source (Table S2), the food strains showed an average genome length of 2.7 Mbp with a $65\%$ GC content, whereas the animal and environmental strains exhibited a slightly shorter genome (2.5 and 2.3 Mbp) and a higher GC ($66.1\%$ and $66.2\%$). The belonging of the genomes to the H. salinarum species was additionally confirmed through dDDH (%dDDH > $70\%$) against the Type Strain Genome Server (Table S3). A comparative genomic analysis on the 19 H. salinarum strains revealed a pangenome of 8430 genes. Specifically, 1101 genes belonged to the core genome (i.e., genes shared between $99\%$ and $100\%$ of the strains); no “soft core” genes (shared between $95\%$ and $98\%$) were detected, whereas “shell” genes (shared between $15\%$ and $94\%$) and “cloud” genes (included in less than $15\%$ of the strains) totaled 2285 and 5044 genes, respectively (Table S4). A previous analysis at the class level on the Halobacteria pangenome was carried out on 111 genomes belonging to different halobacterial species [43]. The study revealed a core genome of 300 genes, thus being almost 4 times smaller than the pangenome identified for the H. salinarum species investigated in this study. This finding could mainly be due to the fact that the class taxonomic level represents a wide range of different species which likely share less genes between each other than strains belonging to a single species. Despite this, the higher number of core genes in the H. salinarum species compared to other prokaryotes species [44,45] could be mainly due to the limited availability of public H. salinarum genomes and, thus, could be due to the limited “biodiversity” considered. This concept was also confirmed by our results, showing that the H. salinarum pangenome is still open since an average of 300 new genes were added for each additional genome included in the analysis (Figure S2). Indeed, it has been previously pointed out that the accuracy of the pangenome definition of a given species strongly depends on sampling the broadest genome diversity possible to best define the core genes and phylogenetic relationships between the genomes analyzed [46]. The percentage of shared and niche-specific genes within the pangenome of H. salinarum was also evaluated (Figure 1a). The Venn diagram shows that approximately $27\%$ of the overall gene content was shared among the three ecological niches from which the strains were isolated. The higher percentage of genes specifically present within the food-isolated genomes could mainly be addressed to the higher number of food strains considered in the analysis (10 out of 19). However, it seemed that the food and animal isolates shared more genes than the latter shared with the environmental isolates. A statistical PCoA based on the pangenome and the isolation source of the strains additionally evidenced the dissimilarity between the genetic contents of the isolates considered (Figure 1b). Indeed, it was shown that the environmental, animal, and food isolates split into different clusters within the two coordinates, revealing the presence of genes specifically related to the ecological niche. Based on the presence/absence of core and accessory genes, the Roary matrix highlighted the presence of unique gene clusters in each considered genome (Figure 2). Regarding the food-niche isolates, a total of 2752 unique genes were evidenced. Excluding hypothetical proteins, the categories that had more genes were related to the DNA modification/replication/transcription regulations and to the mobile genetic elements (i.e., transposases, site-specific integrases, recombinases, and insertion sequences) (Figure 3, Table S5). Among the transcriptional regulators, the MarR and PadR families were the most represented; these families often include transcriptional regulators related to the catabolism of aromatic compounds, such as phenolic acids, and, thus, are involved in cell detoxification mechanisms [47]. The high fraction of unique genes represented by a mobilome may reflect the niche adaptation of the different strains that occurred by acquiring or losing specific metabolic abilities based on the nutritive sources and conditions of the surrounding environment. A previous computational analysis on H. salinarum NRC-1 (isolated from salted animal hides) also revealed its enrichment in IS-elements, highlighting their involvement in the metabolic and regulatory evolution of this halophilic prokaryote [15]. Indeed, other important categories in terms of gene abundance within the food isolates were related to sugar transferases and transporter coding genes (Figure 3, Table S5). Concerning the first category, the highest number of genes encoded a D-inositol-3-phosphate glycosyltransferase (mshA, 16 genes) and a glycosyltransferase family 4 protein (15 genes), whereas the transporters category was mainly represented by the AAA family ATPase and ABC transporter ATP-binding proteins. Other abundant genes belonged to the proteases and peptidases category (Figure 3, Table S5), where metalloproteases and aminopeptidases were particularly evidenced. Microbial aminopeptidase enzymes are of great industrial interest both for food and pharmaceutical applications. For instance, they have been widely used as debittering agents and for protein hydrolysate preparation in the food industry [48]. Moreover, their importance has also been reported in the processing of dry-salted fish [49], indicating that halophilic starter cultures can be exploited to increase the free amino acid content, improving the aroma characteristics [50]. A high number of genes was also evidenced in relation to the reductase and dehydrogenase categories, showing SDR family oxidoreductases (17 genes) and sugar-related dehydrogenases in particular (17 genes) (Figure 3, Table S5). Concerning the unique genes held by the animal-niche isolates, a total of 604 genes were evidenced among which 499 encoded hypothetical proteins (Table S5). Most of the identified genes were related to the DNA modification/replication/transcription regulations category along with sugar transferases and structural proteins (e.g., flagellin and gas vesicles) (Figure 3, Table S5). Gas vesicles are protein-based buoyancy organelles naturally present in photosynthetic and mesophilic bacteria but also in halophilic archaea. Among the latter, H. salinarum gas vesicles are the ones that have been largely investigated for biotechnological applications, mostly related to vaccine development and medical diagnostics [25]. The other abundant genes belonged to the transporter and hydrolase categories, specifically revealing the presence of the sulfur carrier protein TusA (four genes) and the hydroxyacylglutathione hydrolase (glyoxalase II, gloB, eight genes) (Figure 3, Table S5). The latter genes are involved in the cell glyco-oxidative stress response since glyoxalase II participates in removing cytotoxic strong electrophiles such as methylglyoxal, an isomer of dihydroxyacetone phosphate that can be formed from the glycolytic pathway [51]. In relation to the environmental-niche isolates, a total of 420 genes were shown among which 344 encoded hypothetical proteins (Table S5). As for the other two ecological niches, most of the identified unique genes were related to the DNA modification/replication/transcription regulations category (sixteen genes) (Figure 3, Table S5). The second most abundant category was then represented by transporters (eight genes), showing amino acid permeases, inorganic phosphate, and HlyC/CorC family transporters in particular (Figure 3, Table S5). This last family of transporters includes prokaryotic Mg2+ transporters that, together with Pi uptake, can be used by Halobacteria such as H. salinarum to form insoluble magnesium phosphate in case of Pi-limited environments [52]. This indicates a key role of some prokaryotes in phosphorus circulation within a specific ecological niche. ## 3.2.1. Functional and Protechnological Genes in H. salinarum Food Strains Specific metabolic pathways were investigated in more depth with the Comparative Pathway tool in BV-BRC to highlight the putative single-strain capabilities among the food isolates. In particular, the putative ability to produce functional and protechnological compounds was evaluated, and the main outcomes are presented in Table 2. The different strains showed complete pathways for the production of vitamins and cofactors. Specifically, H. salinarum UC4243, isolated from sausage casings, was the only strain including a GTP cyclohydrolase 1 coding gene (EC 3.5.4.16), and it was included in multiple copies (five). This gene converts GTP to 7,8-dihydroneopterin 3′-triphosphate, and it is included in the folate (B9 vitamin) biosynthesis pathway for which the strain was enriched in three other important genes: 6-carboxy-5,6,7,8-tetrahydropterin synthase (EC 4.1.2.50), 7-carboxy-7-deazaguanine synthase (EC 4.3.99.3), and 7-cyano-7-deazaguanine synthase (EC 6.3.4.20). Folate has a key role in different metabolic reactions, such as DNA/RNA biosynthesis and amino acid interconversion. Moreover, this compound has antioxidant properties [53]. Folic acid derivatives (e.g., polyglutamates) are naturally occurring in foods, whereas folic acid is the chemically synthesized form generally used for food fortification and nutritional supplements [54]. Therefore, the selection of food-grade folate-producing microorganisms adapted to high salt levels could be of great interest for increasing the natural food presence of folate in salted food products. H. salinarum UC4242, also isolated from sausage casings, presented genes, which were present in multiple copies, coding for ketol-acid reductoisomerase (NADP(+)) (EC 1.1.1.86), acetolactate synthase (EC 2.2.1.6), and dihydroxy-acid dehydratase (EC 4.2.1.9). These genes are included in pantothenate (B5 vitamin) and CoA biosynthesis. Moreover, five out of ten food strains (UC4243, UC4241, UC4236, UC4238, and UC4239) presented a complete pathway for the production of the K2 vitamin menaquinone (menABCDEFG gene cluster) (Table 2). Interestingly, five strains (UC4243, UC4241, UC4242, UC4237, and UC4238) showed an almost complete pathway for vitamin B12 coenzyme production (Figure 4). The lack of a few genes (indicated in red in Figure 4) involved in precorrin’s conversion to cobyrinate, based on the general porphyrin KEGG pathway, could be due to the partial genotypic knowledge on this biosynthetic pathway in Haloarchaea. However, the presence of a salvage pathway for cobinamide acquisition and de novo B12 coenzyme production has been previously evidenced in H. salinarum NRC-1 [55,56,57]. To this extent, H. salinarum strains that are naturally present in salted food can be exploited as starters for the production of fortified food products. Indeed, vitamin-fortified food with food-grade bacteria has been largely investigated to improve foods’ nutritional value and, thus, diet vitamin intake in a cost-effective scenario [53,54,58,59,60]. Considering aroma-related compounds, acetolactate synthase (EC 2.2.1.6) was only present in H. salinarum UC4242 and in four copies. Within the butanoate metabolism, 2-acetolactate is the precursor of 2-acetoin, an important flavoring agent responsible for the buttery taste of various fermented milk products [61]. The same strain also had a GDP-L-fucose synthetase (EC 1.1.1.271) that converts GDP-4-oxo-6-deoxy-D-mannose to GDP-L-fucose within the fructose and mannose metabolism. L-fucose (6-deoxy-L-galactose) is a rare monosaccharide in nature, but its considerable physiological functions (i.e., anticancer, antiallergic, anticoagulant, and antiaging) have increased interest in the food, cosmetic, and pharmaceutical sectors [62]. Fucose-containing polysaccharides (FCPs) and fucose-containing oligosaccharides (FCOs) can be produced through the fermentation of specific bacterial strains, allowing the exploitation of the different structures of fucose-containing exopolysaccharides (FcEPS). Halophilic bacteria have been previously utilized for the production of FcEPS, and evidence on EPS production and biofilm formation among Haloarchaea has also been shown [25,63,64]. EPS have many applications in the food industry since they can be exploited as thickeners, emulsifiers, and stabilizers to improve the texture, rheological properties, taste, and appearance of food products [63,65,66]. H. salinarum UC4242 also exclusively included a gene coding for the inositol-1-monophosphatase (EC 3.1.3.25) responsible for myo-inositol (MI) production. Additionally, this compound is of great interest to the food sector as a nutritional supplement besides cosmetic and pharmaceutical industry applications. Indeed, MI is a polyol that is naturally present in animal and plant cells, and different foods are rich in this compound, such as cereals, legumes, nuts, seeds, and oil [67]. In eukaryotic cells, MI participates in the transduction of several endocrine signals, including follicle stimulating hormone (FSH), thyroid stimulating hormone (TSH), and insulin. Thus, its important role in hyperinsulinemia reduction and ovarian function restoration has been suggested [68,69]. Regarding antimicrobial agents, archaeocins were found in all the strains investigated. Particularly, halocin-C8 and sactipeptides were highlighted. Halocin-C8 belongs to the archaeocins whose activity is not growth-associated, also remaining constant during the cell stationary phase [27]. This halocin is salt-independent, thermostable (up to 100 °C), and trypsin- and organic-solvent-resistant, and its desalted form at −20 °C maintains its activity for more than 1 year [70,71]. Despite halocins generally targeting producers’ closely related haloarchaea species, the inhibition of different species or even of domains has been highlighted [27]. Sactipeptides (sulfur-to-alpha carbon thioether cross-linked peptides) belong to the ribosomally synthesized and posttranslationally modified peptide (RiPP) class of antimicrobial compounds that are found in all three domains of life and that exhibit a huge variety of structures and activities [72]. Besides their antimicrobial effect, these peptides are involved in biofilm formation by improving the adhesion and protection of the producer [73,74,75]. Their involvement in the ability of extremophilic archaea to survive in hypersaline or high-temperature environments has also been suggested [76]. ## 3.2.2. Genes of Concern in H. salinarum Food Strains To consider any possible application of the strains investigated, an evaluation of the presence of potential genes of concern had to be carried out. The main outcomes are presented in Table 3. The high presence of annotated hypothetical proteins within the archaeal genomes indicates, on one hand, that the knowledge of these microorganisms has yet to be explored and, on the other hand, that most of the curated database for the evaluation of such genes are based on the Bacteria and Eukarya domains [77]. However, partial genome annotations of the H. salinarum strains can provide useful insights into the possible presence of genes of concern in relation to the salted foods under study. Genome mining for putative biogenic amine production was performed on the ten food isolates. All the strains (except UC4236) included pyruvoyl-dependent arginine decarboxylase (EC 4.1.1.19) and agmatinase (EC 3.5.3.11) coding genes responsible for putrescine production from arginine (Table S5). The presence of these two genes in haloarchaeal genomes has already been evidenced, suggesting their requirement for archaeal nucleosome maintenance in high-temperature niches [78,79]. In addition, all the strains had an L-tyrosine decarboxylase (EC 4.1.1.25) involved in tyramine production (Table S5). However, up to date, no phenotypic evidence of H. salinarum biogenic amine production in food has been highlighted. On the contrary, a previous study detected a reduced or unaltered histamine content during the fermentation of salted anchovies and fish sauce inoculated with H. salinarum, suggesting a microbial competition of the species with other histamine-producing microorganisms [50,80]. Regarding ARGs, the interrogation of the CARD database revealed the presence of only one “strict hit” potentially involved in antibiotic resistance in all the strains (except CECT 395). Specifically, the qacG gene coding for a small multidrug resistance (SMR) antibiotic efflux pump was found. This efflux pump is specifically involved in prokaryotes’ excretion of quaternary ammonium compounds used as disinfecting agents and antiseptics. The presence of a small multidrug resistance gene in H. salinarum has been previously highlighted (hsmR), also indicating its location on the chromosome [81]. With regards to VFs, in silico screening conducted with the Abricate tool did not detect significant homologies. The sequence similarity analysis was based on the EFSA cutoff values when evaluating the presence of genes of concern in microorganisms intentionally used in the food chain [82]. However, an additional search of genes putatively related to VFs was carried out with Prokka annotation (Table S5). For instance, genes coding for flagella and pili components were evidenced. Specifically, the flgA1 and flgA2 genes (encoding for the production of flagellin) and the flagellar proteins E and G were found. These proteins play a central role in the formation of the flagellar structure [83]. In addition, several genes were found encoding proteins involved in pili formation, such as prepilin peptidase and type IV pilin [84]. Within the Bacteria domain, flagella and pili are usually recognized as virulence factors since they improve the capability of the microorganism to migrate and anchor to biotic or abiotic surfaces [85]. Moreover, the presence of a gene coding for the IucA/IucC family siderophore biosynthesis protein was highlighted. The production of siderophores is a mechanism that microorganisms, including halophilic archaea, adopt to ensure a constant supply of iron [86]. Nevertheless, pathogenic bacteria and some fungi exploit siderophores to sequester iron and outcompete host uptake during infection [87,88,89]. However, a previous work based on phenotypic tests showed that halophilic archaea belonging to H. salinarum do not produce siderophores [90]. ## 4. Conclusions This study elucidated the presence of unique gene clusters of H. salinarum strains related to the different ecological niches of isolation (salted foods, animal hides, and solar saltern sediments). The genome mining of the food strains revealed that H. salinarum UC4242, isolated from sausage casings, was the strain with the most food-related protechnological genes (putative biosynthesis of nutritional value compounds, such as B vitamins and myo-inositol, aroma- and texture-related features, and antimicrobial compounds). Moreover, all the food isolates investigated presented archaeocins coding genes for halocin-C8 and sactipeptides. A few genes of concern potentially involved in biogenic amine production (putrescine and tyramine), one gene coding for antibiotic resistance (small multidrug resistance efflux pump), and flagellar/pili protein coding genes were evidenced. Further phenotypic assessments will be needed to prove both the beneficial and harmful gene capabilities. 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--- title: Development of Novel Fluorinated Polyphenols as Selective Inhibitors of DYRK1A/B Kinase for Treatment of Neuroinflammatory Diseases including Parkinson’s Disease authors: - Gian Luca Araldi - Yu-Wen Hwang journal: Pharmaceuticals year: 2023 pmcid: PMC10058583 doi: 10.3390/ph16030443 license: CC BY 4.0 --- # Development of Novel Fluorinated Polyphenols as Selective Inhibitors of DYRK1A/B Kinase for Treatment of Neuroinflammatory Diseases including Parkinson’s Disease ## Abstract Natural polyphenol derivatives such as those found in green tea have been known for a long time for their useful therapeutic activity. Starting from EGCG, we have discovered a new fluorinated polyphenol derivative (1c) characterized by improved inhibitory activity against DYRK1A/B enzymes and by considerably improved bioavailability and selectivity. DYRK1A is an enzyme that has been implicated as an important drug target in various therapeutic areas, including neurological disorders (Down syndrome and Alzheimer’s disease), oncology, and type 2 diabetes (pancreatic β-cell expansion). Systematic structure–activity relationship (SAR) on trans-GCG led to the discovery that the introduction of a fluoro atom in the D ring and methylation of the hydroxy group from para to the fluoro atom provide a molecule (1c) with more desirable drug-like properties. Owing to its good ADMET properties, compound 1c showed excellent activity in two in vivo models, namely the lipopolysaccharide (LPS)-induced inflammation model and the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) animal model for Parkinson’s disease. ## 1. Introduction We seek to develop a potent and selective negative allosteric modulator of “Dual-specificity tyrosine-(Y)-phosphorylation Regulated Kinase-1A” (DYRK1A) to treat neuroinflammatory and neurodegenerative diseases such as Parkinson’s disease (PD). PD is the second most common neurodegenerative disorder, affecting $1\%$ of the global population above the age of 60 [1]. PD is identified as the fastest-growing neurological disease in terms of prevalence, disability, and deaths [2], and the number of PD patients is expected to double in the next 30 years. Hallmarks of PD include the appearance of Lewy bodies (LB), aggregates of misfolded protein, and dopaminergic neuronal loss in the substantia nigra pars compacta, which lead to characteristic motor symptoms [3]. DYRK1A is a ubiquitous enzyme that is overexpressed in Down syndrome patients through gene-dosage effects of trisomy chromosome 21 [4]. DYRK1A inhibition offers an attractive approach for the treatment of PD pathologies because of its specific enzymatic activity and broad involvement in anti-inflammatory pathways. Several pieces of evidence point to a role for DYRK1A in PD pathogenesis. Genome-wide association studies have revealed that DYRK1A is a risk factor for PD [5]. The DYRK1A rs8126696 T allele was associated with early onset in a cohort of 297 Chinese patients with PD [6]. An additional study in the Chinese Han population identified the TT genotype derived from SNP rs8126696 of the DYRK1A gene as a possible risk factor for developing sporadic PD, especially for men [7]. DYRK1A may influence the behavior of parkin, the protein product of the first gene known to cause autosomal recessive familial PD [8]. DYRK1A directly phosphorylates parkin at Ser131 in vitro, which inhibits parkin’s E3 ubiquitin ligase activity and, consequently, its neuroprotective function in dopaminergic SHSY5Y cells exposed to 6-hydroxydopamine [9]. In PD, α-synuclein aggregates often contain and sequester septin 4 (SEPTIN4), a polymerizing scaffold protein. Septin 4 was identified as a DYRK1A-binding partner in a yeast two-hybrid screen, which colocalizes with DYRK1A in mouse neurons. DYRK1A phosphorylation of septin 4 is inhibited by harmine [10], suggesting a role for DYRK1A in the health of dopaminergic neurons [11]. Further evidence suggests that DYRK1A expression is increased in PD and Pick disease [12]. DYRK1A inhibitors can also reduce inflammation by targeting pathways including GFAP, STAT, Treg/Th17 differentiation [13], and NF-κB [14]. DYRK1A apparently controls the branch point of CD4 Treg and Th17 cell differentiation. Inhibition of DYRK1A could tilt the balance to Treg, leading to a reduction in inflammation. Likewise, inhibition of DYRK1A could diminish neuroinflammation elicited by LPS, probably through suppression of the TLR4/NF-κB pathway [15]. It has been shown that DYRK1A phosphorylates cyclin D1, leading to a decrease in p21 in the cells and, ultimately, to reduced expression of Nrf2, a transcription factor that induces the expression of genes involved in antioxidant pathways, which reduce ROS levels. DYRK1A inhibitors can potentiate the neuroprotective p21-Nrf2 pathway and contribute to neuronal survival by lessening proinflammatory cytokine production caused by neuroinflammation [16]. Taken together, because of DYRK1A’s interactions with several factors involved in PD and its multiple positions in regulating inflammation, we intend to test the therapeutic hypothesis that by reducing DYRK1A activity, it is possible to intervene in PD pathogenesis and to slow or stop disease progression. DYRK kinases, which are activated by autophosphorylation of tyrosine residues present in a sequence of the activation loop, phosphorylate serine/threonine residues in the substrate [17]. In mammals, five subtypes, i.e., DYRK1A, 1B, 2, 3, and 4, have been identified. These subtypes are divided into two groups: class I, which includes DYRK1A and DYRK1B, and class II, comprising DYRK2, DYRK3, and DYRK4. DYRKs in the same class have high sequence homology and, therefore, may show similar affinity toward inhibitors [18]. To date, most emphases have been placed on developing ATP-competitive DYRK1A inhibitors such as harmine, a β-carboline alkaloid, and many others (Figure 1) [19]. Most of these compounds inhibit both 1A and 1B with the same strength, and few selective derivatives have been discovered to date, such as AZ-191, a selective DYRK1B inhibitor [20]. An alternate attractive DYRK1A inhibitor is the natural product epigallocatechin gallate (EGCG), which combines activity against DYRK1A with antioxidant activity thanks to its polyphenolic groups. The advantage of this class of DYRK1A inhibitors vs. current therapies is the multiple mechanisms of action of such inhibitors, with a potentially superior safety profile. EGCG has been shown to function as a DYRK1A allosteric inhibitor with an in vitro IC50 of around 300–400 nM [21,22]. Previous studies have reported that EGCG prevented MPTP-induced loss of dopaminergic neurons in the substantia nigra, which was concomitant with a depletion in striatal dopamine and tyrosine hydroxylase (TH) protein levels. Another study demonstrated that the protective effects of EGCG in the MPTP mouse model of PD were realized via inhibition of neuronal nitric oxide synthase in the substantia nigra [23]. Moreover, EGCG has immunomodulatory effects in many disease models, including nervous system disease. Zhou et al. [ 2018] recently demonstrated that EGCG has neuroprotective effects in an MPTP-induced PD mice model, which may be exerted by modulating the peripheral immune response [24]. Earlier in the project, we observed that trans-catechin derivatives are about twofold more potent than the corresponding cis derivatives in inhibiting DYRK1A [25]. To our surprise, introducing one or two fluoros in the ortho position of the B or D rings led to a dramatic increase in anti-DYRK1A activity. For example, 1b (Table 1, GCG-2”,6”diF) showed about an eightfold improvement in activity compared to EGCG and is one of the most potent DYRK1A inhibitors discovered to date [26]. Despite its promising activity, the development of EGCG has been hampered by its poor pharmacokinetic profile. Similarly, pharmacokinetic (PK) studies performed in mice using GCG monofluoro or difluoro derivatives showed poor bioavailability profiles similar to that of EGCG (compound 1b, Table 2). It is well known that catechin methylation leads to a molecule such as natural EGCG-3”OMe, which is highly abundant in Benifuuki tea and characterized by much-improved bioavailability [27], although usually with reduced biological activity. Here, we describe the effects of alkylating the hydroxyl group in the meta position of the D ring of our fluorinated GCG derivatives. These molecules were designed with the aim of combining high activity against DYRK1A and good bioavailability. ## 2.1. Synthesis of Compounds As previously described [26], we developed a robust four-step process for synthesizing D-ring derivatives from readily available natural epigallocatechin (EGC) (Scheme 1, as adapted from [26]). This procedure was used to prepare a series of D-ring derivatives with modifications on the metahydroxy group, together with ortho and/or fluoro atom(s) (compounds 1a–h in Table 1) for the current study. Briefly, EGC was first isomerized to yield gallocatechin (GC), which was then converted to alcohol intermediate 2 by selective benzylation of the phenolic groups. Intermediate 2 was esterified using benzylic acid derivatives 3a–h to produce ester 4a–h, followed by catalytic hydrogenation to provide the desired derivatives (1a–h). The detailed procedures for each step and for the preparation of various acids (3a–h) are described in the Section 4. ## 2.2. Overview of Activities and SAR We previously observed that having only one OH or capping the para OH in the D ring reduces activity. However, the introduction of fluorine in ortho resulted in a marked increase in activity. Because methylation of metaphenolic alcohol generates derivatives characterized by considerably improved pharmacokinetic properties, we studied the introduction of substituents on the metahydroxy group, together with fluoro atom(s) in the ortho position. The activity of the new compounds, together with their selectivity against other DYRK subtypes, is reported in Table 1. As expected, methylation of the metaphenol (GCG-3”OMe) reduced the activity of parent GCG by half. However, fluorination in position 2” yielded compound 1c, which is actually more potent than GCG (73 nM vs. 121 nM). The introduction of fluorine in ortho to the methoxy group (compound 1d) or two fluorine atoms (compound 1e) did not improve activity. Replacement of the methyl group with a difluoro methyl (compounds 1f and 1g) or isopropyl (compound 1h) is deleterious for the overall activity. The best compounds were tested for their selectivity against the closely related DYRK1B and DYRK2. As described in Table 1, these molecules showed little or no selectivity vs. DYRK1B and were about four to five times more selective than DYRK2. Systemic exploration of the various combinations led to the discovery of compound 1c (GCG-2”F,5”OMe), which has methoxy and fluorine groups para to each other. This compound was found to be the most potent methoxy derivative in our functional assay, with an IC50 of 73 nM. The inhibitory potency of 1c was subsequently examined with varying concentrations of ATP as previously described [28]. Like its parent compound, EGCG, the inhibitory activity was minimally affected by ATP up to 0.8 mM. Thus, we conclude that 1c is a non-ATP-competitive inhibitor. ## 2.3. Pharmacokinetic Studies To overcome the generally poor PK profile of catechins, we developed a proprietary formulation that allows for the delivery of these drugs in high concentrations for oral (PO) or intranasal (IN) use [25]. Our liquid formulation is based on the solubilizer and penetration enhancer (2-hydroxypropyl)-β-cyclodextrin (HP-β-CD), PEG-400, and water. This vehicle allows us to achieve high drug concentration in dosing solution (up to $20\%$ w/w) when needed. PK studies were conducted for 1c in adult male and female C57BL/6 mice ($$n = 3$$/sex/time point) using [1] a single IV dose (5 mg/kg), [2] an IN dose (60 mg/kg, 5 µL of a clear solution/nostril/twice), and [3] a single PO dose (100 mg/kg). We analyzed the concentration of the drug in several tissues, including the brain, lungs, liver, and plasma. We observed that this class of molecules is stable in circulation; however, when the tissues are harvested for bioanalytical work, the drug undergoes rapid degradation, probably because of the direct contact with oxygen and metals, which catalyzes its rapid degradation/oxidation. We were able to stabilize the drug in blood by the immediate addition of ascorbic acid and TCEP [29]; however, the same was not possible with solid organs such as the brain and liver, which need to be collected through surgery and homogenized before any stabilizing agent can be added. Therefore, tissue PK data tend to vary. Taking into consideration the above observations, when 1c was delivered via PO, its absolute bioavailability in plasma was about $16\%$, while via IN, it was completely bioavailable ($100\%$). Direct comparison with EGCG using oral dosing (100 mg/kg) shows that 1c is characterized by a much-improved oral bioavailability (F1c = 16 vs. FEGCG = 2, Table 2). Using the PO route, we also achieved a high and stable exposure in all the analyzed tissues, including the brain (Table 2), which allows us to achieve a theoretical cellular exposure of about 3 times the IC50 of inhibiting DYRK1A. Interestingly, despite a higher plasma exposure, IN seems to deliver a lower amount of drug into tissues such as the brain and liver. Despite the high variability, as previously discussed, this lower exposure when using the IN route compared to PO dosing seems to be consistent and was also confirmed by the drug efficacy in animal models, as shown below. Since when dosing PO, we observed a higher concentration in conjugated drugs (preliminary observation not shown), we hypothesized that this is the form that might be responsible for the increased bioavailability in tissues. Evidence from recent publications shows that polyphenols and flavonoids can generally be conjugated at the intestinal level and delivered to the tissues of interest, where they are freed-up from the conjugate moiety and able to exert their pharmacological action. Tu et al. showed that the disposition of many oral phenolics is mediated by intestinal glucuronidation and hepatic recycling in a new disposition mechanism called ‘Hepatoenteric Recycling (HER)”, where the intestine is the metabolic organ and the liver is the recycling organ [30]. In their report, Perez-Vizcaino et al. indicated that “glucuronidated derivatives transport quercetin and its methylated form, and deliver to the tissues the free aglycone, which is the final effector” [31]. A similar scenario can be envisioned here in which compound 1c, when administered via the PO route, is conjugated at the intestinal level and transported as glucuronide to the brain through the action of specific transport proteins of the blood–brain barrier (BBB) such as OATP1B; then, in the brain, the glucuronide is removed thanks to the action of selected glucuronidase enzymes. The same would not be possible when the drug is delivered IN, since it would bypass the intestinal tract, which is the main conjugation site. Studies are currently being undertaken to validate this hypothesis. Finally, we tested the PK profile of our best in vitro inhibitor, 1b. Unfortunately, in this case, the bioavailability was much lower than that of 1c. These results confirmed what was already reported in the literature, in which catechin without the methyl group in the D ring showed a much lower bioavailability. Overall, based on the in vitro and in vivo data, we chose compound 1c for our proof-of-concept efficacy animal studies reported below. To further confirm the PK results, we selected both PO and IN routes for the efficacy studies. ## 2.4. Pharmacological Studies Neuroinflammation is a common feature shared by several neurodegenerative disorders and is implicated in the advancement of neurodegeneration. Dysregulated microglial activation causes neuroinflammation and has long been considered a treatment target in therapeutic strategies [32]. As outlined in the Introduction, DYRK1A regulates multiple inflammatory signaling pathways. DYRK1A inhibitors have been shown to suppress neurodegeneration caused by central and peripheral inflammation; thus, they may be broadly applicable for the treatment of various inflammatory conditions. Based on the above findings, we studied the efficacy of 1c in the LPS-induced inflammation model and the MPTP PD model. ## 2.4.1. LPS-Induced Inflammation Studies Neuroinflammation is an important factor contributing to cognitive impairment and neurodegenerative diseases such as PD, and the administration of LPS is frequently used to study neuroinflammation-associated diseases in mice [33]. A recent study showed that DYRK1A inhibition reduced neuroinflammation, decreased microglial activation, and attenuated inflammation-induced neuronal damage in an LPS-induced neuroinflammatory model. Inhibition of DYRK1A attenuated neuroinflammation stimulated by LPS by suppressing the TLR4/NF-κB p65 signaling pathway both in vitro and in vivo [15]. Collectively, these data suggest that DYRK1A is a potentially viable target for the treatment of neurodegenerative diseases involving a neuroinflammatory component, such as in PD. This recent finding rationalizes the use of the LPS model for our PK/PD study. In this model, 1c showed a strong overall anti-inflammatory effect (Figure 2) when 1c was administered to C57BL/6 mice via the PO route (30 mg/kg, BID) starting 3 days before LPS treatment (i.p., 750 µg/kg BW, for 5 days), significantly ($p \leq 0.05$) decreasing TNFα accumulation in plasma and in the brain. Finally, we observed that 1c reduced tau phosphorylation in the hippocampus (Figure 2C). Because tau is the direct downstream target phosphorylated by DYRK1A, we used the measure of p-tau as a proxy of drug efficacy in tissues. This result suggests that the observed biological activity is due to the inhibition of our target enzyme. When the drug is administered via the IN route, we observed a significant drug level in plasma but a lower level in the brain, which was further confirmed by the lack of efficacy in inhibiting tau phosphorylation. These findings agree with results for other DYRK1A inhibitors [34], as well as with the PK profile of the drug, confirming that 1c administered via the IN route has better peripheral efficacy; however, when administered via the PO route, it achieved better exposure and efficacy in the brain. Dexamethasone, our selected positive control, shows a profile that is similar to that of 1c administered via the IN route. Like 1c, dexamethasone achieves high efficacy in plasma but very low efficacy in the brain due to its poor BBB penetration. Overall, 1c is a potent DYRK1A inhibitor and quite effective in reducing chronic inflammation both systemically and in the brain and could be helpful in the treatment of neuroinflammatory processes such as PD. ## 2.4.2. MPTP Model Compound 1c also demonstrated significant efficacy in the MPTP model for PD (Figure 3). We tested the behavioral effect of 1c in the MPTP model for PD using both IN and PO delivery (both 25 mg/kg, BID). This is a common neurodegenerative disorder model characterized by a progressive loss of dopaminergic (DA) neurons in the striatum [24]. Several studies have shown that oxidative stress, neuroinflammation, and microglial activation play a pivotal role, at least in the progression of PD [35]. The results shown in Figure 3 reveal that the 1c treatment completely restored the movement behavior of the mice impaired by MPTP in two different behavioral tests, namely the pole test (Figure 3A,B) and the rotarod test (Figure 3C). In these behavioral tests, we did not observe any difference between the two routes of administration. Interestingly, as reported in Figure 3D, tyrosine-hydroxylase-positive cells in the substantia nigra pars compacta region were only protected from MPTP toxicity in the 1c PO treatment group, while the IN treatment group failed to show any histological difference. As in the LPS model, the PO group showed superior efficacy compared to the IN group, probably because of the better brain/plasma ratio. ## 3. Discussion DYRK1A is a ubiquitous enzyme that is overexpressed in Down syndrome patients through gene-dosage effects of trisomy chromosome 21 [4]. DYRK1A inhibition offers an attractive approach for the treatment of PD pathologies because of the broad involvement of this kinase in anti-inflammatory pathways (Figure 4). Dementia is recognized as a common component of advanced Parkinson’s disease (PD-D). The combination of LBs, neuroinflammation, AD-type pathologies such as intraneuronal neurofibrillary tangles (NFTs) [36], and extraneuronal neuritic plaques of amyloid β-42 (Aβ42) [37,38,39,40,41] is considered to achieve a strong pathological association with PD-D. With the expected increase in global life expectancy and the increasing prevalence of PD, associated dementia is likely to become a prevailing problem. The development of drugs that can target both PD and PD-D is a major unmet need. DYRK1A is a proline-directed serine/threonine kinase for which many proteins have been shown as substrates [11]. DYRK1A activity may be involved in PD and PD-D pathogenesis because [1] it is robustly expressed in CNS neurons [42]; [2] it increase the clearance of neurotoxic protein aggregates by directly phosphorylating parkin and septin 4 [9,10]; [3] it directly attenuates inflammation by targeting Nrf2, GFAP, and TLR4/NF-κB p65 [15,16,43]; [4] it directly phosphorylates the key protein APP and increases the secretase-mediated cleavage of APP into Aβ peptides [44]; [5] Aβ peptides stimulate DYRK1A expression in a positive feedback loop [45]; [6] DYRK1A is a kinase for which tau serves as a substrate [46]; and [7] its presence is associated with increased phosphorylation of tau [47]. These findings support our hypothesis that the inhibition of DYRK1A activity has a disease-modifying effect and can significantly impact the lives of those with PD and PD-D. We now report the discovery of novel and potent DYRK1A allosteric inhibitors in our ongoing medicinal chemistry effort [48]. Our lead compound in terms of potency, safety, and pharmacological activity is 1c. This compound inhibits DYRK1A, with an IC50 of 73 nM, and is characterized by a remarkably clean safety/selectivity profile and improved permeability/bioavailability. The extensive in vitro and in vivo safety studies performed to date have not reveled any concerns. In the PK study, we obtained good bioavailability combined with a good brain/plasma ratio and stable level throughout the 24 h period, making this drug a once-a-day candidate. Owing to its good ADMET properties, 1c showed excellent activity in several inflammation models. In particular, compound 1c was found to be efficacious in treating acute inflammation in the LPS model and Parkinson’s symptoms induced by MPTP. These findings indicate that 1c may exert three complementary actions: (i) mitigation of the actions of proteins responsible for neurodegeneration through inhibition of DYRK1A; (ii) direct inflammation attenuation; and (iii) although not directly addressed in the current study, owing to its similarity to EGCG, compound 1c may be able to increase the clearance of neurotoxic protein aggregates [49]. Therefore, 1c treatment could simultaneously address several of the predominant underlying pathophysiological aspects of neurodegenerative disorders such as PD and PD-D. All proposed PD drugs based on the inhibition of protein aggregation alone have failed in clinical trials to date. Compound 1c offers a promising alternative therapeutic strategy. A plan to test this compound in chronic PD models is underway. ## 4.1. Chemistry General: All solvents and reagents were obtained from commercial suppliers and were used directly without further purification. The reaction progress was monitored on a TLC plate (Merck, silica gel 60 F254, Darmstadt, Germany). 1H, 13C, and 19F NMR spectra were recorded on a Bruker Advance 400 MHz spectrometer using deuterated chloroform or dimethyl sulfoxide (DMSO). Chemical shifts (δ) are reported in parts per million (ppm) up-field from tetramethylsilane (TMS) as an internal standard, and s, d, t, and m are presented as singlet, doublet, triplet, and multiplet, respectively. Coupling constants (J) are reported in hertz (Hz). Liquid chromatography-mass spectra (LC-MS) were recorded on an Agilent (single quad) or Thermo Scientific ion trap. Abbreviations: AA: ascorbic acid; ACN: acetonitrile; DBU: 1,8-diazabicyclo[5.4.0]undec-7-ene; DCM: dichloromethane; DMAP: dimethylamino pyridine; DMF: dimethylformamide; EtOAc: ethyl acetate; MeOH: methanol; PE: petroleum ether; TCEP: tris[2-carboxyethyl]phosphine hydrochloride; TEA: triethyl amine; THF: tetrahydrofuran; TLC: thin-layer chromatography. ## 4.1.1. Synthesis of (2S,3R)-2-(3,4,5-trihydroxyphenyl)-3,5,7-chromantriol ((−)-gallocatechin, GC) (2R,3R)-2-(3,4,5-trihydroxyphenyl)-3,4-dihydro-2H-chromene-3,5,7-triol (EGC) (50 g) was treated with phosphate buffer (pH 7.2, 0.1 M, 140 mL). The solution was refluxed for 2 h, and after cooling, a white precipitate of gallocatechin was obtained. After filtration, the solid was crystallized with water (500 mL) which afford the desired GC as a white solid in good yield with good purity (20 g, $40\%$ yield). ## 4.1.2. Synthesis of (2S,3R)-5,7-bis(benzyloxy)-2-(3,4,5-tris(benzyloxy)phenyl)chroman-3-ol (2) K2CO3 (11.30 g, 81.63 mmol, 5.0 eq.) was added to a stirred solution of GC (5.0 g, 16.33 mmol, 1 eq.) in dry DMF (30 mL) and stirred at RT for 0.5 h. Benzyl bromide (9.2 mL, 81.63 mmol, 5.0 eq.) was added dropwise to this mixture at −20 °C. The suspension was slowly warmed to RT and stirred for 24 h. After complete consumption of the starting material, the reaction mixture was filtered through a pad of celite to remove K2CO3. The celite pad was washed with EtOAc (100 mL). The combined organic phase was washed with cold H2O (2 × 50 mL), dried over Na2SO4, filtered, and concentrated. The obtained residue was purified by flash-column chromatography with EtOAc:Hexane (6:1) to afford the desired intermediate [2] (4.5 g, $36\%$ yield) as a white solid. Analytical data: 1H NMR (400 MHz, CDCl3): δ 7.48 -7.20 (m, 25H), 6.82 (s, 2H), 6.34 (s, 1H), 6.13 (s, 1H), 5.07 (s, 8H), 5.04 (s, 1H), 4.91 (s, 2H), 4.64 (d, $J = 7.2$ Hz, 1H), 4.03 (bs, 1H), 2.78 (dd, $J = 16.0$ Hz, 4.8 Hz, 1H), 2.46 (dd, $J = 16.4$ Hz, 4.8 Hz, 1H). ## 4.1.3. Synthesis of 3,4,5-tris(benzyloxy)-2-fluorobenzoic acid (3a) H2SO4 (11.5 mL, 117.564 mmol, 2 eq.) was added to a solution of methyl 3,4,5-trihydroxybenzoate (20 g, 117.564 mmol, 1 eq.) in 200 mL MeOH at 0 °Cm and the reaction mixture was stirred at 80 °C for 22 h. Reaction progress was monitored by TLC. Then, the reaction mixture was concentrated under reduced pressure; the crude residue was diluted with cold water to allow the ester intermediate to precipitate out. The solid was filtered and washed with water, and the wet cake was dried in vacuo to yield the methyl 3,4,5-trihydroxybenzoate as a white solid (20 g, $92\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 9.29 (s, 3H), 6.92 (s, 2H), 3.72 (s, 3H). K2CO3 (71.304 g, 515.591 mmol, 5 eq.) was added to a suspension of abovementioned intermediate (19 g, 103.182 mmol, 1eq.) in DMF (200 mL), followed by benzyl bromide (61 mL, 515.591 mmol, 5 eq.) at 0 °C. The mixture was heated to 80 °C for 16 h. After this time, ice was added to the reaction solution to precipitate out the desired product as a solid. The solid was filtered, washed with water, and dried to yield methyl 3,4,5-tris(benzyloxy)benzoate as a white solid (30 g, $64\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 7.43–7.26 (m, 17H), 5.33 (s, 2H), 5.16 (s, 2H), 5.01 (s, 2H), 3.83 (s, 3H). Selectfluor (46.7 g, 132.013 mmol, 2 eq.) was added to a solution of the abovementioned intermediate (30 g, 66.006 mmol, 1 eq.) in 200 mL of ACN at 0 °C and stirred at RT for 96 h. Reaction progress was monitored by TLC. After this time, the reaction mixture was quenched with a saturated solution of NaHCO3, and the product was extracted with EtOAc (3 × 100 mL). The organic layer was washed with brine, dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure to yield the crude compound. Purification by flash-column chromatography using $10\%$ EtOAc in hexane afforded the intermediate methyl 3,4,5-tris(benzyloxy)-2-fluorobenzoate as a pale brown solid (7 g, $22\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 7.42–7.28 (m, 16H), 5.33 (s, 2H), 5.16 (s, 2H), 5.14 (s, 2H), 3.81 (s, 3H), 19F NMR (400 MHz, DMSO-d6) δ-134.52. NaOH (5.9 g, 148.145 mmol, 10 eq.) was added to a solution of the abovementioned intermediate (7 g, 14.814 mmol, 1 eq.) in THF:H2O (3:1) (50 mL) and stirred at 80 °C for 6 h. The reaction mixture was concentrated under reduced pressure, the obtained residue was diluted with H2O (30 mL), and the product was extracted with EtOAc (2 × 80 mL). The aqueous phase pH was adjusted to <3 with 1N HCl. Then, the mixture was filtered, and the filter cake was dried. The crude compound was purified by flash-column chromatography using $10\%$ MeOH in DCM to obtain the title intermediate (3a) as a white solid (3.8 g, $60\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6): δ 13.22 (s, 1H), 7.42 (d, $J = 1.2$ Hz, 2H), 7.44–7.26 (m, 10H), 5.14 (s, 2H), 5.12 (s, 2H), 3.81 (s, 3H). ## 4.1.4. Synthesis of 3,4,5-tris(benzyloxy)-2,6-difluorobenzoic acid (3b) Selectfluor (77 g, 220.264 mmol, 2 eq.) was added to a solution of methyl 3,4,5-tris(benzyloxy)benzoate (50 g, 110.132 mmol, 1 eq.) in ACN (60 mL) at 0 °C, and the reaction mixture was stirred at RT for 48 h. Reaction progress was monitor by TLC. After this time, the reaction mixture was quenched with cold water, extracted with EtOAc (3 × 100 mL), washed with brine, dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure. The obtained crude compound was purified by flash-column chromatography using $5\%$ EtOAc in hexane as an eluent to afford methyl 3,4,5-tris(benzyloxy)-2,6-difluorobenzoate as a yellow solid (0.6 g, $1\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 7.38–7.34 (m, 15H), 5.27 (s, 2H), 5.02 (s, 4H), 3.85 (s, 3H). 19F NMR (400 MHz, DMSO-d6) δ-133.38. LiOH·H2O (0.513 g, 12.240 mmol, 10 eq.) was added to a solution of the abovementioned intermediate (0.6 g, 1.224 mmol, 1 eq.) in THF:H2O (3:1) (12 mL) and stirred at RT for 16 h. The reaction mixture was concentrated, and the obtained crude material was diluted with H2O (30 mL) and extracted with EtOAc (10 mL). The aqueous phase pH was adjusted to <3 with 1N HCl. The obtained solid was filtered and dried to obtain 3b as a yellow solid (0.352 g, $60\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 13.85 (s, 1H), 7.35–7.33 (m, 15H), 5.15 (s, 2H), 5.02 (s, 4H); 19F NMR (400 MHz, DMSO-d6) δ-134.14. ## 4.1.5. Synthesis of 3, 4-bis(benzyloxy)-2-fluoro-5-methoxybenzoic acid (3c) DBU (1.26 Lit, 8.47 mol, 3.0 eq.) was added to a suspension of methyl 3,4,5-trihydroxybenzoate (520 g, 2.82 mol, 1.0 eq.) in DMF (5.2 L), followed by benzyl bromide (671 mL, 5.65 mol, 2.0 eq.), at 0 °C. The reaction solution was allowed to stir at RT for 48 h. After this time, the reaction mixture was diluted with EtOAc (15.6 L), washed with water (2 × 10.4 L) and brine (10 L), dried over anhydrous Na2SO4, filtered, and concentrated. The obtained crude compound was purified by column chromatography using DCM in hexane as eluent to yield methyl 3,4-bis(benzyloxy)-5-hydroxybenzoate as a white solid (185 g, $17.9\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 9.77 (s, 1H), 7.46–7.33 (m, 7H), 7.29–7.26 (m, 3H), 7.15 (d, $J = 1.6$ Hz, 2H), 5.12 (s, 2H), 5.02 (s, 2H), 3.79 (s, 3H). Selectfluor (170.19 g, 480.76 mmol, 2.5 eq.) was added to a solution of the abovementioned intermediate (70 g, 192.30 mmol, 1.0 eq.) in 700 mL of ethanol at RT and stirred at 80 °C for 30 h. Reaction progress was monitored by TLC. After this time, the reaction mixture was concentrated under reduced pressure, and the obtained crude material was diluted with water (350 mL) and extracted with EtOAc (2 × 700 mL). The combined organic layer was washed with brine (350 mL), dried over anhydrous Na2SO4, filtered, and concentrated. The obtained crude was purified by column chromatography and eluted with $10\%$ EtOAc in hexane to afford pure methyl 3,4-bis(benzyloxy)-5-hydroxy fluoro derivative as a white solid (15.2 g, $20.69\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 9.94 (s, 1H), 7.48–7.31 (m, 10H), 7.13 (d, $J = 6.8$ Hz, 1H), 5.14 (s, 2H), 5.00 (s, 2H), 3.80 (s, 3H); 19F NMR (400 MHz, DMSO-d6) δ-136.66. K2CO3 (36.180 g, 261.78 mmol, 2.5 eq.) was added to a suspension of methyl 3,4-bis(benzyloxy)-5-hydroxy fluoro benzoate (40.0 g, 104.71 mmol, 1.0 eq.) in DMF (400 mL), followed by methyl iodide (13.0 mL, 209.42 mmol, 2.0 eq.), at 0 °C. The mixture was stirred at RT for 3 h. After this time, the reaction mass was diluted with water (800 mL) and EtOAc (400 mL). The organic layer was separated, washed with water (500 mL) and brine (300 mL), dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure. The obtained crude compound was triturated with $5\%$ DCM:hexane for 1 h, then filtered. Purification by column chromatography using EtOAc and hexane yielded the desired compound, methyl 3,4-bis(benzyloxy)-2-fluoro-5-methoxybenzoate, as a colorless liquid (18.0 g, $43.4\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 7.47–7.30 (m, 10H), 7.18 (d, $J = 6.4$ Hz, 1H), 5.11 (s, 2H), 5.03 (s, 2H), 5.01 (s, 2H), 3.84 (s, 6H); 19F NMR (400 MHz, DMSO-d6) δ-134.086. LiOH·H2O (12.196 g, 290.40 mmol, 5.0 eq.) was added to a solution of methyl 3,4-bis(benzyloxy)-2-fluoro-5-methoxybenzoate (23.0 g, 58.08 mmol, 1.0 eq.) in THF:MeOH:H2O (1:1:1) (240 mL) at 0 °C and stirred at RT for 4 h. After the complete consumption of the starting material on TLC, the solvent was evaporated from the reaction mixture. The obtained residue was diluted with H2O (150 mL) and washed with diethyl ether (50 mL). The aqueous layer was acidified with 1N HCl (pH = 3–4), and the formed precipitate was filtered, washed with n-pentane (2 × 50 mL), and dried under vacuum to yield 3,4-bis(benzyloxy)-2-fluoro-5-methoxybenzoic acid 3c (20.6 g, $92.9\%$ yield) as a white solid. Analytical data: 1H NMR (400 MHz, DMSO-d6): δ 13.25 (s, 1H), 7.50–7.30 (m, 10H), 7.19 (d, $J = 6.4$ Hz, 1H), 5.11 (s, 2H), 5.04 (s, 2H), 3.85 (s, 3H); 19F NMR (400 MHz, DMSO-d6) δ-134.263. ## 4.1.6. Synthesis of benzyl 4,5-bis(benzyloxy)-2-fluoro-3-methoxybenzoate (3d) K2CO3 (22.4 g, 162.950 mmol, 6 eq.) was added to a solution of 3,4-dihydroxy-5-methoxybenzoic acid (5 g, 27.159 mmol) in DMF (50 mL), followed by benzyl bromide (16 mL, 1135.79 mmol, 5 eq.), at 0 °C. The mixture was heated to 80 °C for 16 h until TLC showed that the reaction was completed. The reaction mixture was diluted with water and extracted with EtOAc. The organic layer was concentrated under vacuum to yield the crude product and purified by flash chromatography using $15\%$ EtOAc in hexane as eluent to yield benzyl 3,4-bis(benzyloxy)-5-methoxybenzoate as a yellow liquid (10.1 g, $82\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 7.43–7.26 (m, 17H), 5.33 (s, 2H), 5.14 (s, 2H), 5.01 (s, 2H), 3.83 (s, 3H). Selectfluor (17.1 g, 4.400 mmol, 2 eq.) was added to a solution of the abovementioned intermediate (11 g, 24.240 mmol, 1 eq.) in ACN (100 mL) at 0 °C, and the reaction mixture was stirred at RT for 48 h. Reaction progress was monitored by TLC. After this time, the reaction mixture was quenched with cold water and extracted with EtOAc (3 × 100 mL). The organic layer was washed with brine solution, dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure. The crude compound was purified by flash-column chromatography using $10\%$ EtOAc in hexane as eluent to yield benzyl 4,5-bis(benzyloxy)-2-fluoro-3-methoxybenzoate as a yellow solid (1.1 g, $9\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6): δ 7.42–7.28 (m, 16H), 5.33 (s, 2H), 5.16 (s, 2H), 5.14 (s, 2H), 3.81 (s, 3H); 19F NMR (400 MHz, DMSO-d6) δ-134.52. LiOH·H2O (0.88 g, 21.186 mmol, 10.0 eq.) was added to a solution of the abovementioned intermediate (1 g, 2.118 mmol, 1.0 eq.) in THF:H2O (3:1) (20 mL). The solution was stirred at RT for 16 h. The reaction mixture was concentrated, and the obtained crude was diluted with H2O (30 mL) and extracted with EtOAc (2 × 80 mL). The aqueous phase pH was adjusted to <3 with 1N HCl. The obtained solid was filtered, and the cake was dried. The crude compound was purified by flash-column chromatography using $10\%$ EtOAc in hexane as eluent to obtain 3d as a white solid (0.502 g, $62\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6): δ 13.22 (s, 1H), 7.42 (d, $J = 1.2$ Hz, 2H), 7.44–7.26 (m, 10H), 5.14 (s, 2H), 5.12 (s, 2H), 3.81 (s, 3H). ## 4.1.7. Synthesis of 3,4-bis(benzyloxy)-2,6-difluoro-5-methoxybenzoic acid (3e) Selectfluor (77 g, 220.264 mmol, 2 eq.) was added to a solution of methyl 3,4,5-tris(benzyloxy)benzoate (50 g, 110.132 mmol, 1 eq.) in ACN (60 mL) at 0 °C, and the reaction mixture was stirred at RT for 48 h. Reaction progress was monitored by TLC. After this time, the reaction mixture was quenched with cold water, extracted with EtOAc (3 × 100 mL), washed with brine, dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure to yield a crude compound. The obtained crude compound was purified by flash-column chromatography and eluted with $5\%$ EtOAc in hexane to obtain methyl 3,4,5-tris(benzyloxy)-2,6-difluorobenzoate as a yellow solid (0.6 g, $1\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 7.38–7.34 (m, 15H), 5.27 (s, 2H), 5.02 (s, 4H), 3.85 (s, 3H); 19F NMR (400 MHz, DMSO-d6) δ-133.38. LiOH.H2O (0.31 g, 7.50 mmol, 3.0 eq.) was added to a mixture of the abovementioned intermediate (1 g, 2.50 mmol, 1.0 eq.) in THF:H2O (1:1) (20 mL). The solution was stirred at RT for 16 h. The reaction mixture was concentrated to remove THF. Then, the mixture was diluted with H2O (30 mL) and extracted with EtAOc (2 × 80 mL). The aqueous phase pH was adjusted to < 3 with 1 N HCl. The obtained solid was filtered, and the filter cake was dried to yield compound 3e as a white solid (0.85 g, $85\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 13.82 (s, 1H), 7.42 (d, $J = 1.2$ Hz, 2H), 7.37–7.29 (m, 8H), 5.17 (s, 2H), 5.01 (s, 2H), 3.81 (s, 3H); 19F NMR (400 MHz, DMSO-d6) δ-134.65, -135.57. ## 4.1.8. Synthesis of 3,4-bis(benzyloxy)-5-(difluoromethoxy)benzoic acid (3f) LiOH·H2O (0.25 g, 12.070 mmol, 5.0 eq.) was added to a mixture of methyl 3,4-bis(benzyloxy)-5-(difluoromethoxy)benzoate (1 g, 2.415 mmol, 1.0 eq.) in THF:H2O (1:1) (20 mL). The solution was stirred at RT for 16 h. The reaction mixture was concentrated to remove THF. Then, the mixture was diluted with H2O (25 mL) and extracted with EtOAc (2 × 30 mL). The aqueous phase pH was adjusted to < 3 with 1N HCl. The obtained solid was filtered, and the filtered cake was dried to yield the compound 3,4-bis(benzyloxy)-5-(difluoromethoxy)benzoic acid as a white solid (0.7 g, $72\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 7.64 (d, $J = 1.2$ Hz, 1H), 7.46 (d, $J = 6$ Hz, 3H), 7.39–7.34 (m, 5H), 7.30 (t, $J = 2.4$ Hz, 3H), 7.11 (s, 1H), 5.15 (s, 2H), 5.01 (s, 2H); 19F NMR (400 MHz, DMSO-d6) δ 80.92, 80.72. ## 4.1.9. Synthesis of 3,4-bis(benzyloxy)-5-(difluoromethoxy)-2-fluorobenzoic acid (3g) KOH (0.92 g, 16.48 mmol, 5.0 eq.) was added to a solution of methyl 3,4-bis(benzyloxy)-5-hydroxybenzoate (1.2 g, 3.29 mmol, 1.0 eq.) in ACN:H2O (6:4) (10 mL) at room temperature and stirred for 20 min. Then, the mixture was cooled to −78 °C, and diethyl (bromodifluoromethyl)phosphonate was added (2.64 g, 9.89 mmol, 3.0 eq). Then, the mixture was allowed to warm up to RT and stirred for 4 h. Finally, the reaction mixture was diluted with H2O (50 mL), neutralized with 1N HCl, and extracted with EtOAc (2 × 100 mL). The combined organic layers were washed with brine (50 mL), dried over Na2SO4, filtered, and concentrated. The residue was purified by flash-column chromatography using petroleum ether (PE)/EtOAc, $\frac{9}{1}$ as eluent to yield methyl 3, 4-bis(benzyloxy)-5-(difluoromethoxy)benzoate (0.48 g, $35\%$ yield) as a yellow solid. Analytical data: 1H NMR (400 MHz, DMSO-d6): δ 7.60 (d, $J = 2.0$ Hz, 1H), 7.52–7.47 (m, 2H), 7.45–7.30 (m, 9H), 7.20 (t, $J = 73.6$ Hz, 1H), 5.26 (s, 2H), 5.09 (s, 2H), 3.85 (s, 3H). Selectfluor (6.15 g, 17.39 mmol, 6.0 eq.) was added to a mixture of the abovementioned intermediate (1.2 g, 2.89 mmol, 1.0 eq.) in ACN (12 mL) at 0 °C and stirred at RT for 1 h. Then, the reaction mixture was warmed to 50 °C and stirred for another 16 h. After completion of the reaction, the reaction mass was cooled to RT, diluted with H2O (50 mL), and extracted with EtOAc (2 × 100 mL). The combined organic layers were washed with brine (50 mL), dried over Na2SO4, filtered, and concentrated. The residue was purified by flash-column chromatography using PE/EtOAc ($\frac{9}{1}$) as eluent to yield methyl 3,4-bis(benzyloxy)-5-(difluoromethoxy)-2-fluorobenzoate (0.051 g, $4\%$ yield) as a pale yellow solid. Analytical data: 1H NMR (400 MHz, CDCl3): δ 7.50 (d, $J = 6.4$ Hz, 1H), 7.45–7.32 (m, 9H), 6.38 (t, $J = 74.0$ Hz, 1H), 5.15 (s, 2H), 5.11 (s, 2H), 3.92 (s, 3H). LiOH (0.07 g, 2.89 mmol, 5.0 eq.) was added to a solution of the abovementioned intermediate (0.25 g, 0.57 mmol, 1.0 eq.) in MeOH:THF:H2O (1:1:1) (6 mL) at 0 °C and stirred at RT for 4 h. After completion of the reaction, the solvent was evaporated under reduced pressure. The obtained solid was diluted with H2O (20 mL), acidified with 1N HCl (to pH 2–3), and extracted with EtOAc (3 × 50 mL). The combined organic layers were dried over anhydrous Na2SO4 and evaporated under reduced pressure to yield 3g (0.215 g, $89\%$ yield) as a white solid. Analytical data: 1H NMR (400 MHz, DMSO-d6): 7.45–7.32 (m, 9H), 7.16 (t, $J = 73.2$ Hz, 1H), 5.15 (s, 2H), 5.10 (s, 2H). ## 4.1.10. Synthesis of 3,4-bis(benzyloxy)-2,6-difluoro-5-isopropoxybenzoic acid (3h) K2CO3 (5.73 g, 41.20 mmol, 1.2 eq.) was added to a suspension of methyl 3,4-bis(benzyloxy)-5-hydroxybenzoate (10.0 g, 27.470 mmol) in DMF (100 mL), followed by 2-bromopropane (5.08 g, 41.20 mmol, 1.2 eq.), at 0 °C. The reaction mixture was heated to 60 °C for 12 h. After this time, the reaction mass was diluted with water and extracted with EtOAc. The organic layer was evaporated, and the residue was purified by flash chromatography eluted with $25\%$ EtOAc in hexane to yield methyl 3,4-bis(benzyloxy)-5-isopropoxybenzoate as a white solid (8.2 g, $73\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 7.47 (d, $J = 1.2$ Hz, 1H), 7.45–7.35 (m, 4H), 7.34–7.30 (m, 5H), 7.23 (d, $J = 2.0$ Hz, 2H), 5.16 (s, 2H), 5.02 (s, 2H), 4.66–4.60 (m, 1H), 3.82 (s, 3H), 1.27 (s, 3H), 1.28 (s, 3H). Selectfluor (42.7 g, 120.743 mmol, 4 eq.) was added to a solution of the abovementioned intermediate (12.2 g, 30.185 mmol, 1 eq.) in 60 mL ACN at 0 °C, and the reaction mixture was stirred at 60 °C for 32 h. Reaction progress was monitored by TLC. After this time, the reaction mixture was quenched with cold water and extracted with EtOAc (3 × 100 mL). The combined organic layer was washed with brine, dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure to obtain a crude compound. The crude compound was purified by flash-column chromatography to yield methyl 3,4-bis(benzyloxy)-2,6-difluoro-5-isopropoxybenzoate as a green solid (1.1 g, $8\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 7.43–7.30 (m, 10H), 5.18 (s, 2H), 5.04 (s, 2H), 4.43–4.28 (m, 1H), 3.56 (s, 3H), 1.24 (s, 3H), 1.16 (s, 3H). LiOH·H2O (0.284 g, 11.300 mmol, 5.0 eq.) was added to a mixture of methyl 3,4-bis(benzyloxy)-2,6-difluoro-5-isopropoxybenzoate (1 g, 2.260 mmol, 1.0 eq.) in THF:H2O (1:1) (20 mL). The solution was stirred at RT for 2 h. The reaction mixture was concentrated to remove THF. Then, the mixture was diluted with H2O (30 mL) and extracted with EtOAc (20 mL). The aqueous phase pH was adjusted to <3 with 1N HCl. The obtained solid was filtered, and the solid was dried to yield 3h as a white solid (0.91 g, $94\%$ yield). Analytical data: 1H NMR (400 MHz, DMSO-d6) δ 13.82 (s, 1H), 7.43–7.30 (m, 10H), 5.15 (s, 2H), 5.04 (s, 2H), 4.39–4.36 (m, 1H), 1.21 (s, 3H), 1.20 (s, 3H); 19F NMR (400 MHz, DMSO-d6) δ 134.17, 134.18, 134.48, 134.48. ## 4.1.11. General Procedure for Synthesis of Compounds 4a–h Oxalyl chloride (5 eq.) and two drops of DMF were added to a stirred solution of 3 (1.2 eq.) in DCM (10 mL) under an inert atmosphere at 0 °C. The reaction mixture was stirred at RT for 3 h. After this time, the reaction mixture was concentrated under reduced pressure to obtain the correspondent acid chloride. The acid chloride was added to a solution of 2 (3.0 g, 3.968 mmol, 1 eq.), DMAP (4 eq.), and TEA (4 eq.) in DCM (10 mL) at 0 °C. Then, the reaction mixture was stirred at RT 16 h. Finally, the reaction was quenched with saturated aqueous NaHCO3 solution (5 mL). The organic layer was separated, and the aqueous layer was extracted with DCM (30 mL). The combined organic phase was dried over Na2SO4, filtered, and concentrated under reduced pressure. The obtained crude compound was purified by flash-column chromatography using EtOAc and hexane as eluent to yield 4a–h. Please see Supplementary Materials for the detail of compounds 4a–h synthesis. ## 4.1.12. General Procedure for Synthesis of Compounds 1a–h Pd(OH)2 (20 wt. %, 2.0 g) was added to a solution of intermediate 4a–h (2.0 g) in 20 mL of THF:MeOH (1:1), and the reaction mixture was stirred under a hydrogen atmosphere at RT for 16 h. Then, the mixture was passed through a pad of celite to remove the catalyst. The filtrate was concentrated under reduced pressure. The obtained crude compound was purified by Prep-HPLC to obtain 1a–h as a white to off-white solid. Please see Supplementary Materials for the detail of compounds 1a–h synthesis. ## 4.2. Kinase Assays 6xHis-tagged rat-truncated DYRK1A (residues 1-497) was used in the assays, as previously described [28]. DYRK1B was prepared from human DYRK1B isoform p65 as glutathione S-transferase fusion protein, and DYRK2 was prepared from human DYRK2 isoform 1 as 6xHis-tagged protein, as previously described [22]. Kinase preparations were verified by the following immunological and biochemical criteria to ensure their identity before use: [1] immunoreactivity only to the cognate antibody in ELISA (data not shown) and [2] sensitivity to inhibitor AZ-191, which was shown to differentially inhibit different DYRKs [20]. The IC50 of AZ-191 for each kinase preparation (Table 1) was determined by the assay protocol described below and found to be consistent with the published IC50 values of 88 nM, 17 nM, and 1890 nM for DYRK1A, DYRK1B, and DYRK2, respectively [20]. The IC50 of each compound against DYRK1A was determined by an ELISA-based non-radioactive kinase assay as previously described [28] using 6XHis-tagged dynamin 1a proline-rich domain (residues 746-864) as the substrate. The DYRK1A assay protocol can also support DYRK1B and DYRK2 phosphorylation reactions in an enzyme-concentration-dependent manner; therefore, the method was adapted to measuring the IC50 of each compound against DYRK1B and DYRK2. For DYRK2, the reactions were performed exactly as described for DYRK1A. For DYRK1B, the assays were similarly conducted but with 30 ng GST-DYRK1B and a kinase reaction time of 60 min. An ATP competition assay against compound 1c was performed on DYRK1A as previously described [28]. ## 4.3. Pharmacokinetic Assays C57BL/6J mice were given a single dose of drug via the IN or PO route. The formulation for IN delivery was as follows: PEG-400 ($12.5\%$ w/w), HP-β-CD ($10\%$ w/w), and Na2EDTA ($0.125\%$ w/w) in water q.s. For PO delivery, we replaced water with saline. The volume for IN delivery was 5 µL/nostril, and the volume used for oral delivery was 10 mL/kg. After sacrifice, blood (500 µL) was collected into K2EDTA microtubes and kept on ice all times (must be centrifuged within 30 min of collection). Blood was centrifuged in EDTA vacuum at 4 °C at 15,000× g for 4 min; ~250 µL of plasma was collected into polyethylene tubes containing 50 µL of AA/TCEP stabilizing solution (20 mM ascorbic acid and 13 mM TCEP in 50 mM K2HPO4 buffer; the pH of the solution was adjusted to 6.5 using 2 M NaOH). Then, 200 µL of the collected plasma was mixed with [1] 24 µL of a solution of $10\%$ ascorbic acid and $0.1\%$ EDTA in 40 mM NaH2PO4; [2] 40 µL of 50 mM sodium phosphate (pH 7.4); [3] 500 units of β-D-glucuronidase type X-A from Escherichia coli (Sigma Chemical Co, St Louis, MO, USA), and [4] 4 units of sulfatase type VIII from abalone entrails (Sigma Chemical Co). The mixture was incubated at 37 °C for 45 min. Plasma was then extracted by the addition of 0.5 mL ACN; the mixture was vortex-mixed for 2 min, then snap-frozen with isopropanol/carbon dioxide dry ice, and the upper layer of ACN was removed. The process was repeated another 2 times. The ACN fractions were pooled into a polyethylene tube kept on ice. The combined fractions were evaporated under a gentle stream of nitrogen at ambient temperature. The residue obtained after evaporation was reconstituted in 200 µL of 75 mM citric acid//25 mM ammonium acetate: ACN (75:25 by vol), and vortexed vigorously for 5 min, and 20 µL of the resulting solution was injected into the LC-MS/MS column. Drug analysis in tissues: About ~0.4 g of the tissue was homogenized with 1 mL of ice-cold 0.4 M sodium phosphate buffer containing 6 mg of ascorbic acid and 0.5 mg of Na2EDTA (final pH of 6.5). After centrifugation at 4 °C at 15,000× g for 4 min, the supernatant was collected into polyethylene tubes containing 50 µL of the AA/TCEP stabilizing solution. Then 1 U of sulfatase and 250 U of β-glucuronidase were added to the abovementioned homogenized mixture. Samples were incubated at 37 °C for 45 min, then extracted, dried, and resuspended in a manner similar to that for plasma. Samples were then analyzed by LC-MS/MS. ## 4.4.1. LPS-Induced Inflammation Model This study was performed at BioDuro-Sundia (IACUC Approval Code: BD-202208375, Approval Date: 29 August 2022). C57BL/6J male mice (11–12 weeks old) were housed in a room with automatically controlled temperature (21–25 °C), relative humidity (45–$65\%$), and light–dark (12–12 h) cycles. The mice in each cage were divided into the following treatment groups: (I) i.p. saline group (control); (II) i.p. LPS (750 μg/kg) group; (III) i.p. LPS (750 μg/kg) + dexamethasone (1 mg/kg, PO) group; (IV) i.p. LPS (750 μg/kg) + compound 1c (30 mg/kg, IN, BID) group; and (V) i.p. LPS (750 μg/kg) + compound 1c (30 mg/kg, PO, BID) group. Each group consisted of six male mice. The vehicle for the PO and IN formulations was composed of $12\%$ PEG400, $0.2\%$ Na2EDTA, $10\%$ HP-β-CD, and water q.s. Animals were pretreated for 3 days with the drug of choice; then, treatment with LPS commenced on day 0, and on the 5th day of LPS treatment, the drug was administered half an hour before LPS injection. One hour after LPS treatment, the animals were anesthetized with a mixture of ketamine, xylazine $2\%$, atropine, and saline (4:2.5:1:2.5). The body temperature of mice under anesthesia was maintained by applying a heating blanket and monitored using a rectal thermometer. After anesthesia, the animals underwent cardiac perfusion with ice-cold saline for three minutes (3 mL/minute via peristaltic pump) via the left ventricle. The right atrium was cut as an outflow route. The right hemisphere was post-fixed overnight in $4\%$ PFA in PBS at 4 °C and stored in 1xPBS containing $0.1\%$ (v/w) sodium azide at 4 °C. The left hemisphere, hippocampus, cortex, midbrain, and brainstem were microdissected, immersed in liquid nitrogen in separate tubes (with one-fifth of the rest of the brain tissue), and stored in microfuge tubes at −80°. TNFα (in both plasma and the hippocampus) was analyzed with ELISA, and the p-tau (AT-8 antibody) level was recorded in the hippocampus and cortex with WB. ## 4.4.2. MPTP Model This study was performed at Pharmaron (IACUC approval code: IVP-CNS-06012020; approval date: 10 February 2021). C57BL/6J male mice (8–10 weeks old) were divided into four experimental groups: untreated control group, MPTP-treated group, MPTP + compound 1c (25 mg/kg, IN) group, and MPTP + compound 1c (25 mg/kg, PO) group. MPTP dissolved in saline was administered via intraperitoneal injections once daily at a dosage of 30 mg/kg/day for 5 consecutive days. The control group was administered intraperitoneal injections of saline. Treatment with compound 1c was started one day prior to MPTP treatment and continued for 16 days (twice daily for 15 consecutive days and once on the last day). Compound 1c was administered 1 h before MPTP injection on days 1–5. The behavioral tests were performed at initiation as the baseline and 3, 6, and 9 days following the last MPTP injection. Pole test: the test consisted of a gauze-taped pole (45 cm high, 1 cm in diameter) with a small cork ball at the top. Mice were placed with their head facing upwards immediately below the ball. Two times were recorded: the time it took for the mouse to turn completely downward (T-turn) and the time it took to descend to the floor (T-total), with a cutoff limit of 60 sec. The test consisted of two trials separated by 10 min intertrial intervals, and the average time was calculated. Mice were pretrained for 3 days before MPTP injection. The rotarod test was used to assess the motor coordination and balance of animals. On the test day, the mice were habituated for 30 min in the test room before testing. The drum was slowly accelerated to a speed of 4–40 rpm for a maximum of 300 s. The latency to fall off the rotarod within this time period was recorded. The test consisted of three trials separated by 10 min intertrial intervals. The mean latency to fall off the rotarod was recorded and used for analysis. Mice were trained for 3 days before MPTP injection. Tissue Collection and IHC Analysis: within 2 h following the last dose, the blood of animals was collected via cardiac puncture under isoflurane-induced anesthesia. After blood collection, animals were transcardially perfused with normal saline, followed by buffered formalin fixative. Brains were removed, post-fixed, and embedded in paraffin for subsequent IHC analysis of hydroxylase (TH)-positive cells in the substantia nigra (SN). ## Figures, Scheme and Tables Figure 1: DYRK1A and DYRK1B inhibitors. Scheme 1: Synthetic scheme for D-ring derivatives. Figure 2: Compound 1c suppresses LPS-induced inflammation. (A) Experimental scheme; (B) hippocampal TNFα protein; (C) plasma TNFα; (D) tau phosphorylation in the hippocampus; (E) tau phosphorylation in the cortex. $p \leq 0.05$; $p \leq 0.01$; ** $p \leq 0.0001.$ Data (means ± SE, $$n = 6$$/group) were analyzed by one-way ANOVA.* Figure 3: Results of treatment with compound 1c in the MPTP model (10 mg/kg, IP). Effect on behavior measured 7 days after the last MPTP injection. (A) Pole test t-turn time; (B) pole test t-total time; (C) accelerated rotarod test; (D) effect on SNc dopaminergic neurons. (E) SNc IHC slides: G1, control vehicle group; G2, MPTP-treated group; G3, MPTP + Compd. 1c at 25 mg/kg in the IN group; G4, MPTP + Compd. 1c at 25 mg/kg in the PO group. $p \leq 0.05$; ** $p \leq 0.01$, one-way ANOVA. Data are presented as the mean ± standard error of the mean ($$n = 8$$).* Figure 4: Proposed mechanism of action of DYRK1A and compound 1c in Parkinson’s disease. TABLE_PLACEHOLDER:Table 1 TABLE_PLACEHOLDER:Table 2 ## References 1. Tysnes O.B., Storstein A.. Epidemiology of Parkinson’s disease. J. Neural Transm. (2017) 124 901-905. DOI: 10.1007/s00702-017-1686-y 2. Global, regional, and national burden of neurological disorders during 1990–2015: A systematic analysis for the Global Burden of Disease Study 2015. Lancet Neurol. (2017) 16 877-897. DOI: 10.1016/S1474-4422(17)30299-5 3. Poewe W., Seppi K., Tanner C.M., Halliday G.M., Brundin P., Volkmann J., Schrag A.E., Lang A.E.. Parkinson disease. Nat. Rev. Dis. Prim. (2017) 3 17013. DOI: 10.1038/nrdp.2017.13 4. 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--- title: Disturbed Ratios between Essential and Toxic Trace Elements as Potential Biomarkers of Acute Ischemic Stroke authors: - Anna Mirończuk - Katarzyna Kapica-Topczewska - Katarzyna Socha - Jolanta Soroczyńska - Jacek Jamiołkowski - Monika Chorąży - Agata Czarnowska - Agnieszka Mitrosz - Alina Kułakowska - Jan Kochanowicz journal: Nutrients year: 2023 pmcid: PMC10058587 doi: 10.3390/nu15061434 license: CC BY 4.0 --- # Disturbed Ratios between Essential and Toxic Trace Elements as Potential Biomarkers of Acute Ischemic Stroke ## Abstract Background: Cadmium (Cd) and lead (Pb) are known to be two of the metal contaminants that pose the greatest potential threat to human health. The purpose of this research study was to compare the levels of toxic metals (Cd, Pb) in patients with acute ischemic stroke (AIS), with a control group in Podlaskie Voivodeship, Poland. The study also aimed to assess the correlations between toxic metals and clinical data in AIS patients, and to assess the potential effect of smoking. Materials and methods: The levels of mineral components in the collected blood samples were assessed by means of atomic absorption spectrometry (AAS). Results: The Cd blood concentration was significantly higher in AIS patients as compared to the control group. We found that the molar ratios of Cd/Zn and Cd/Pb were significantly higher ($p \leq 0.001$; $p \leq 0.001$, respectively), when the molar ratios of Se/Pb, Se/Cd, and Cu/Cd were significantly lower ($$p \leq 0.01$$; $p \leq 0.001$; $p \leq 0.001$, respectively), in AIS patients as compared to control subjects. However, there were no considerable fluctuations in relation to the blood Pb concentration or molar ratios of Zn/Pb and Cu/Pb between our AIS patients and the control group. We also found that patients with internal carotid artery (ICA) atherosclerosis, particularly those with 20–$50\%$ ICA stenosis, had higher concentrations of Cd and Cd/Zn, but lower Cu/Cd and Se/Cd molar ratios. In the course of our analysis, we observed that current smokers among AIS patients had significantly higher blood-Cd concentrations, Cd/Zn and Cd/Pb molar ratios, and hemoglobin levels, but significantly lower HDL-C concentrations, Se/Cd, and Cu/Cd molar ratios. Conclusions: Our research has shown that the disruption of the metal balance plays a crucial role in the pathogenesis of AIS. Furthermore, our results broaden those of previous studies on the exposure to Cd and Pb as risk factors for AIS. Further investigations are necessary to examine the probable mechanisms of Cd and Pb in the onset of ischemic stroke. The Cd/Zn molar ratio may be a useful biomarker of atherosclerosis in AIS patients. An accurate assessment of changes in the molar ratios of essential and toxic trace elements could serve as a valuable indicator of the nutritional status and levels of oxidative stress in AIS patients. It is critical to investigate the potential role of exposure to metal mixtures in AIS, due to its public health implications. ## 1. Introduction There is growing concern regarding the potential role of unorthodox threatening factors, such as exposure to air pollution, environmental chemicals, heavy metals, and persistent organic pollutants regarding cardiovascular disease development (CVD) [1,2]. These factors, alongside traditional risk factors such as obesity, diabetes, hypertension and dyslipidemia, have been considered as potential CVD contributors. According to the study by Feigin et al. [ 3], behavioral factors such as smoking, suboptimal nutritional choices, and inadequate physical activity account for a significant proportion ($47.0\%$) of stroke burden. However, environmental risks, including air pollution and exposure to toxic metals, contribute an additional $37.8\%$. Multiple studies have suggested that exposure to various metals and metalloids can adversely affect immune function and increase the risk of CVD [4]. Environmental pollution is generally considered the main factor contributing to human exposure to heavy metals. Cadmium (Cd), arsenic (As), lead (Pb), and mercury (Hg), among others, are usually highlighted because of their high toxicity. Furthermore, Cd and Pb have been identified as two of the metal contaminants that pose the greatest potential harm and risk to human health [5]. The study involved patients living in the Green Lungs of Poland, situated in the northeastern region of the country. Podlaskie Voivodeship, Poland, is an ecological region, predominantly agricultural, with minimal industrialization and no significant heavy industry. Thus, the primary sources of heavy metal exposure are contaminated food due to pollution, and tobacco smoking [6,7]. Cd and Pb are significant environmental pollutants in Podlaskie Voivodeship, due to their prevalence, despite having relatively low concentrations [8,9]. These toxic trace elements pose a significant threat to the environment as they can easily contaminate food sources, leading to the exceedance of maximum acceptable food content levels. On the other hand, exceedances of arsenic and mercury pollution are rare, even in local fish populations in the region [10]. Consistent with the systematic review by Bao et al. [ 5], the effect of arsenic and mercury on stroke risk was found to be reduced. Unbalanced levels of metals in the body have been shown to disrupt homeostasis and contribute to the progression of various diseases, including ischemic stroke [5,11,12,13,14,15]. However, the indication regarding the connection between exposure to heavy metals and stroke risk remains inconclusive. Exposure to trace elements such as Pb and Cd for the general public occurs through inhalation, dermal absorption, and long-term consumption of food products and contaminated water, as well as exposure to soil, dust and fumes, industrial materials, consumer products and ambient air [16]. Heavy metal toxicity has been linked to a range of conditions, including neurological and neurodegenerative disorders, cancer, bone and kidney diseases, and autoimmune disorders [7,17,18]. According to Renu et al. ’s study, heavy-metal-induced liver toxicity is often accompanied by inflammation that is triggered by the activation of proinflammatory cytokines, TNF-alpha, and the ERK and MAPK pathways [19]. These toxic metals can disrupt the balance of essential trace elements in the body and interfere with their physiological and biochemical processes [19,20]. Cadmium (Cd) tends to accumulate primarily in the kidneys ($50\%$), liver ($15\%$), and muscles ($20\%$) in humans. It is also found in high concentrations in erythrocytes, while its concentration in plasma is very low [21]. The possible mechanism of Cd neurotoxicity is the induction of oxidative stress, the disruption of the activity of enzymes essential for the proper functioning of the nervous system, and the destruction of the homeostasis of bioelements in the brain [22]. Comprehensive evaluations and combined analyses on the relationship between Cd and CVD have included studies on stroke, taking into account smoking habits [23,24]. Current smokers have approximately twice as much Cd in their kidneys and urine, and three to four times as much Cd in their blood, compared to never-smokers [25,26]. Numerous medical investigations have determined that it is inclined to accumulate in the vasculature’s intima. Cd has been associated with the formation of carotid plaques [27], carotid atherosclerosis [23,28,29,30,31], increased risks of CVD [14,32,32,33,34,35,36] and stroke [5,11,14,25,32,37,38,39,40,41,42,43], hypertension [44,45,46], peripheral arterial disease [47], myocardial infarction [48,49] and inflammation [50,51]. It has also been proved that exposure to Cd and obesity may have significant synergistic results on the onset of diabetes [52,53]. All the factors mentioned above are involved in stroke risk. However, data directly linking Cd exposure to the risk of ischemic stroke are limited, and the findings are contradictory. Lead is mainly taken in by respiration through the airways or digestion through the digestive system, with subsequent accumulation in bone, blood, and organs such as the brain, kidneys, and liver [54]. Pb has a half-life of several weeks in the circulatory system and nearly two years in the brain. It can accumulate in bones, serving as a continuous internal source of Pb that can leach out over time and affect the vascular endothelium and other tissues [18,55]. The central nervous system is highly susceptible to Pb toxicity. Research has proven that Pb-triggered endothelial dysfunction may increase the risk of CVD, cerebral atherosclerosis and neurodegenerative diseases [56]. Most studies analyzing the effects of Pb on the general population have focused on cardiovascular morbidity. The increased levels of Pb are associated with an increased risk of heart disease, atherosclerosis, hypertension, and cardiac disease, due to cellular signaling and atherosclerotic changes, inflammation, and dysregulation of lipid metabolism [57,58]. The detection of heavy metals has recently become a key focus in medical research. There is growing evidence that suggests a positive correlation between certain environmental pollutants and the incidence of stroke. A meta-analysis of 37 independent investigations reported a linear dose–response relationship between exposure to Pb and Cd and CVD risk, particularly stroke [32]. Furthermore, a systematic review conducted by Bao et al. highlights the fact that long-term exposure to lead and copper is associated with an increased risk of stroke [5]. The purpose of this research study was to compare the levels of toxic trace elements (Pb, Cd) in acute-ischemic-stroke (AIS) patients to those of a control group in Podlaskie Voivodeship, Poland. The study also aimed to assess the correlations between toxic metals and clinical data in stroke patients and evaluate the potential effect of smoking. Based on our previous research [59], which investigated the concentrations of essential trace elements (selenium, zinc, copper), this study examined the relationship between toxic metals and essential trace elements in AIS patients. At present time, few, if any, detailed investigations have been conducted to analyze the status of toxic metals in AIS patients in a Polish population. ## 2. Materials and Methods This medical research was carried out from January 2019 to November 2021 at the Medical University of Bialystok (MUB) in the Department of Neurology. A total of 187 AIS patients were enrolled in the study, including 85 patients who received intravenous thrombolysis and/or mechanical thrombectomy and 102 patients who received conservative treatment. The criteria for inclusion in the study were specified as follows: age between 18 and 85 years at the time of enrolment, hospitalization within 24 h of the onset of neurological symptoms, computed tomography (CT), and/or magnetic resonance imaging (MRI) to estimate the magnitude of the infarction and eliminate intracranial and subarachnoid hemorrhage and tumors. Individuals who participated in the study were selected 2–5 days after the onset of clinical signs. Exclusion criteria comprised: previous stroke or ischemic stroke of undetermined etiology (UD) according to the TOAST classification (Trial of Org 10,172 in Acute Stroke Treatment) [60], acute surgical and traumatic diseases, myocardial infarction, or acute and contagious infections and inflammations within the past month. Furthermore, advanced heart failure, autoimmune diseases (rheumatic disease), stage 5 chronic kidney disease, liver failure, cancer, recent intake of mineral supplements in the last 3 months, metal implants, or hormonal therapy. A group of 94 control subjects with no history of stroke or chronic cerebrovascular disease was selected from individuals who voluntarily contacted the Department of Bromatology at the Medical University of Bialystok. Demographic, clinical, and cardiovascular risk factors, including arterial hypertension, smoking status (never, former, or current smoker), diabetes, excessive alcohol consumption, abnormal levels of lipoproteins, previous cardiac disorders, atrial fibrillation, and a history of previous stroke, as well as a history of medication and laboratory records, were evaluated. Neurological status was estimated using the National Institutes of Health Stroke Scale (NIHSS) during admission and discharge [61] and the modified Rankin Scale (mRS) [62] on discharge. The etiology of ischemic stroke was established using the TOAST classification (Trial of Org 10,172 in Acute Stroke Treatment) [60] and was classified into three categories: cardioembolism (CE), large artery atherosclerosis (LAA), and small vessel occlusion (SVO). Findings from neurological assessment and various imaging techniques such as CT or MRI of the brain, B-mode external ultrasound carotid imaging, echocardiography, head and/or neck CT angiography, and 12-channel ECG were used as the basis for the evaluation. Smoking status was classified as never-smokers or smokers, including former (stopped smoking ≤15 years ago) or current smokers. Body mass index (BMI) was determined by the patient’s weight expressed in kilograms divided by height in meters squared, with values <25.0 or ≥25.0 considered normal weight or overweight/obese, respectively. The protocol used for this research was verified and accepted by the Ethics Committee at the Medical University of Bialystok (reference number R-I-$\frac{002}{276}$/2018). All study participants or their authorized representatives expressed a written and informed consent prior to the collection of blood specimens and the updating of clinical data from medical records. ## 2.1. Blood Sample Collection and Analysis Approximately 8 mL of blood samples were taken from each study participant using a vacuum blood-collection system with a clot activator (Becton Dickinson, France). The samples were collected within 3 to 5 days of the neurological symptoms’ onset and were processed by centrifuging at 2500× g rpm for 10 min (MPW M-Diagnostic, Med. Instruments, Warsaw, Poland). Samples of whole blood and serum were subsequently preserved at −20 °C in the Department of Bromatology (MUB). All reagents and chemicals utilized in the study were of high quality and suitable for spectral analysis. A total of 200 µL of whole blood were taken into Eppendorf tubes, and 800 µL of 1 mol/L of nitric acid (Merck, Darmstadt, Germany) and 200 µL of $1\%$ Triton X-100 (Sigma, Taufkirchen, Germany) were added. The samples were vortexed and centrifuged for 10 min at 2500× g rpm. The supernatant was then further diluted 3 times with 0.1 mol/L HNO3. The concentrations of Cd and Pb in the blood samples were determined by applying atomic absorption spectrometry (AAS) with flameless atomization in a graphite cuvette and Zeeman background rectification using the following wavelengths: 228.8 nm and 283.3 nm, respectively (Z-2000, Hitachi High-Technologies Corporation, Tokyo, Japan). During the determination of Cd, the following analytical program (start/end temperature) was used: drying $\frac{80}{140}$ °C, ashing $\frac{140}{450}$ °C, atomization $\frac{1600}{1600}$ °C and graphite cuvette cleaning $\frac{1800}{1800}$ °C. During Pb determination, the following analytical program was used: drying $\frac{80}{140}$ °C, ashing $\frac{140}{600}$ °C, atomization $\frac{2400}{2400}$ °C and graphite cuvette cleaning $\frac{2700}{2700}$ °C. Matrix modifiers, 1000 mg/L palladium nitrite (Merck, Darmstadt, Germany) for Cd and $0.5\%$ ammonium dihydrogen phosphate (Sigma, Taufkirchen, Germany) for Pb, were then added to eliminate interferences from the matrix. Calibration solutions were prepared using standard solutions of Cd and Pb with a concentration of 1 g/L (Merck, Darmstadt, Germany). The detection limits for Cd and Pb were 0.053 μg/L and 0.45 μg/L, respectively. The precision of Cd and Pb determinations was verified using certified reference material, Seronorm Trace Elements Whole Blood L-2 (Sero AS, Hvalstad, Norway). On average, the percent recovery values reported for the analytical methods used to determine the content of Cd and Pb in the reference material were $98.4\%$ and $103.2\%$, respectively, and the precision of the methods was $3.4\%$ and $2.5\%$, respectively. The concentrations of Cu (copper) and Se (selenium) in serum were also determined by atomic absorption spectrometry with electrothermal atomization using a Zeeman background correction, as previously described [59]. The concentration of Zn (zinc) in serum was determined using the same method with air-acetylene flame atomization [59]. The reliability of these methods was verified using certified reference material from human serum (Seronorm trace elements, Serum L-1, SeroA, Billingstad, Norway). The conclusions of the quality control evaluations were consistent with the reference values. Biochemical assays were performed using protocol standards, and the Cd, Pb, and Se values are expressed in μg/L, while the Cu and Zn values are expressed in mg/L [63]. The Department of Bromatology (MUB) participated in the quality control program for trace element analyses monitored by the National Institute of Public Health, the National Institute of Hygiene, and the Institute of Chemistry and Nuclear Physics (Warsaw, Poland). The concentrations of Cd, Pb, Cu, Zn, and Se in whole blood and serum were calculated in mmol/L to assess the dyshomeostasis of these metals. The concentrations of mineral components were estimated, and the molar ratios between essential trace elements and toxic metals were also calculated and compared between AIS patients and control subjects using Excel software, based on previous studies [59] on the concentration of antioxidant elements (Se, Zn, Cu). Furthermore, selected serum levels of elementary biochemical factors were determined in the accredited Biochemical Clinical Laboratory of the Medical University of Bialystok Clinical Hospital and compared to laboratory reference values. The fasting lipid profile of each patient, including the values for low-density lipoprotein cholesterol LDL-C, total cholesterol TC, triglycerides TG and high-density lipoprotein cholesterol (HDL-C), was evaluated using enzymatic methods and expressed in mg/dL. ## 2.2. Statistical Methods The frequency of qualitative variables was contrasted between the groups using Pearson’s χ2 test. Mann–Whitney tests were used to determine disparities between the groups for continuous variables. The correlations between continuous or ordinal variables were estimated using Spearman’s rank correlation coefficients. Multivariable models for continuous outcomes were identified using generalized linear models. Statistics-related calculations were performed utilizing IBM SPSS Statistics 26.0 software [64]. ## 3. Results We examined 187 sequential AIS patients, including 85 patients who received interventional management and 102 patients who underwent conservative treatment, and compared them to 94 control subjects. There was no statistically significant difference in the distribution of males and females between the AIS patients and the control subjects ($$p \leq 0.058$$). Over $90\%$ of AIS patients had arterial hypertension, and a higher mean body mass index (BMI) compared to the control subjects (27 vs. 25.2, $p \leq 0.05$). As indicated by the clinical findings, brain lesions were more prevalent in the left hemisphere of the brain, within the anterior cerebral circulation ($77\%$). It was observed that a high proportion (over $79\%$) of AIS patients exhibited unexpected results on extracranial carotid Doppler ultrasound (characterized by a protrusion of carotid intima–media thickness (CIMT) of more than 1.5 mm in the lumen or intensified thickening of the middle layer of the focal area of more than $50\%$ of the area encompassing the vessel). This was particularly prevalent in the left internal carotid artery. Carotid atherosclerotic plaques with low echogenicity were found in 99 ($53\%$) of AIS patients (including mixed echogenicity in 71 AIS patients). The baseline demographic characteristics, the biochemical values, the levels of Pb and Cd in whole blood, and the levels of Cu, Zn, and Se in serum in AIS patients and control subjects are shown in Table 1 and Table 2. The concentration of Cd in the blood was considerably higher ($p \leq 0.0001$) in AIS patients as compared to those of control subjects. We found that the molar ratios of Cd/Zn and Cd/Pb were significantly higher ($p \leq 0.001$; $p \leq 0.001$, respectively), when the molar ratios of Se/Pb, Se/Cd, Cu/Cd were significantly lower ($$p \leq 0.01$$; $p \leq 0.001$; $p \leq 0.001$, respectively), in AIS patients, as compared to control subjects. However, there were no significant fluctuations in relation to the blood Pb concentration ($$p \leq 0.223$$) or molar ratios of Zn/Pb and Cu/Pb ($$p \leq 0.059$$; $$p \leq 0.898$$, respectively), between AIS patients and control subjects (Table 2). Interestingly, most of the toxic and essential trace elements studied were correlated with each other (Figure 1). In this dissertation, we explored the potential relationships between the concentration of trace elements in plasma and whole blood and the traditional risk factors for stroke. Our investigation revealed that statistically prominent correlations were found between fibrinogen levels and the Cd and Cd/Zn molar ratios. At the same time, an inverse relationship was observed between fibrinogen levels and the Se/Cd molar ratio. Furthermore, we were able to observe positive correlations between D-dimer levels and Cd/Pb and Cu/Pb molar ratios. Additionally, the Cu/Cd molar ratio had a significant association with the NIHSS score on admission ($r = 0.18$, $$p \leq 0.016$$) and C-reactive-protein (CRP) levels ($r = 0.15$, $$p \leq 0.045$$). In AIS patients, we found positive correlations between uric-acid levels and the Cd/Pb molar ratio, as well as between the levels of the N-terminal prohormone of the brain natriuretic peptide (Nt-proBNP) and the Se/Cd and Cd/Pb molar ratios. These findings suggest the existence of potential associations between concentrations of trace elements and stroke risk factors, but comprehensive research seems to be essential to fully understand the underlying mechanisms. The study revealed statistically significant differences in the Cu/Pb molar ratios among AIS patients according to their etiology classified by the TOAST classification. The group with LAA etiology had lower Cu/Pb molar ratios as compared to the CE- and SVO-etiology groups ($$p \leq 0.029$$). Furthermore, the type of treatment received (interventional therapy versus conservative treatment) influenced the parameters studied in AIS patients. Patients who received conservative treatment had lower Cu/Cd and Se/Cd molar ratios as compared to those who received interventional therapy ($$p \leq 0.007$$ and $$p \leq 0.028$$, respectively). Furthermore, AIS patients with a more advanced stage of ICA atherosclerosis had higher NIHSS scores on admission and discharge and higher mRS scores on discharge ($$p \leq 0.003$$, $$p \leq 0.005$$, and $$p \leq 0.012$$, respectively). No significant correlations were found between BMI and the toxic elements studied in AIS patients. Multiple associations between clinical variables examined in AIS patients were identified, indicating that ischemic stroke has a complex etiology. Furthermore, a positive correlation was found between the stage of ICA atherosclerosis assessed by Doppler ultrasound and Cd levels ($r = 0.24$, $$p \leq 0.001$$), and the Cd/Zn molar ratio ($r = 0.15$, $$p \leq 0.037$$). On the other hand, the stage of ICA atherosclerosis had negative correlations with the Cu/Cd and Se/Cd molar ratios (r = −0.18, $$p \leq 0.014$$; r = −0.23, $$p \leq 0.002$$, respectively). However, after adjusting for smoking status, these correlations were no longer statistically significant ($p \leq 0.05$) (Table 3). No correlation was observed between the Zn and Cd concentrations (r = −0.04; $$p \leq 0.59$$). We also found that patients with ICA atherosclerosis, particularly those with 20–$50\%$ ICA stenosis, had higher concentrations of Cd and Cd/Zn (Figure 2) but lower Cu/Cd and Se/Cd molar ratios. Furthermore, our results demonstrated an association between serum lipid profile and trace elements. Specifically, only the molar ratios of Zn/Pb and Cd/Zn were significantly correlated with HDL values (r = −0.16, $$p \leq 0.031$$, $r = 0.16$, $$p \leq 0.027$$, respectively). At the same time, no significant associations were observed between LDL, TG, TC, non-HDL, and toxic elements. No statistically significant correlations were found between the toxic elements studied and the size of brain lesions, the NIHSS and mRS scores on discharge, ejection fraction (EF), creatinine levels, homocysteine levels, hemoglobin levels or hemoglobin A1C levels ($p \leq 0.05$). Additionally, there were no statistically significant differences in the levels of toxic metals based on the location of the brain lesion, the presence of type 2 diabetes mellitus, atrial fibrillation, hypertension, hyperlipidemia, or the type and location of atherosclerotic plaques in AIS patients ($p \leq 0.05$). In the course of our analysis, we observed that current smokers among AIS patients had significantly higher blood Cd concentrations, Cd/Zn and Cd/Pb molar ratios, and hemoglobin levels, but significantly lower HDL-C concentrations, Se/Cd, and Cu/Cd molar ratios. In contrast, no significant variations were found regarding the concentration of Pb ($$p \leq 0.702$$). We also found that current smokers were more likely to have LAA etiology, while never-smokers were more likely to have a CE etiology ($$p \leq 0.014$$). In terms of the stage of ICA atherosclerosis, current smokers had a higher prevalence of advanced stages evaluated by Doppler ultrasound examination ($p \leq 0.0001$). Higher Cd concentrations divided into quartiles were also observed in current smokers ($p \leq 0.001$) and patients with higher stages of ICA atherosclerosis assessed by Doppler ultrasound ($$p \leq 0.018$$). In fact, more than $80\%$ of AIS patients in quartiles 3 and 4 of blood-Cd concentrations (>1.568 µg/L) were current smokers, while only $40.4\%$ of never-smokers were in these quartiles. There were no statistically relevant links between blood-Cd quartile levels and variables such as sex, age, type 2 diabetes mellitus, fasting lipid profile, CRP and homocysteine values. A generalized linear regression model showed that factors such as current smoking status, atrial fibrillation, advanced age, and lower NIHSS scores on admission significantly increase Cd concentrations in AIS patients. Furthermore, a lower BMI index, advanced age, and current smoking status were significant predictors of elevated Cd/Zn molar-ratio concentrations. Conservative treatment applied in AIS patients, a more severe stage of ICA atherosclerosis, and higher hemoglobin values were related to higher Pb concentrations in these patients (Table 4A–C). We observed a prominent correlation between age and Cd/Zn molar levels, and a negative correlation between age and Se/Cd molar ratios in AIS patients ($r = 0.15$; $$p \leq 0.042$$, r = −0.20; $$p \leq 0.005$$, respectively). In control subjects, lower Se/Pb and Cu/Pb molar ratios were observed in older patients (r = −0.21, $$p \leq 0.0047$$; r = −0.25, $$p \leq 0.016$$, respectively). Furthermore, significant differences in Cu/Cd molar levels were found between male and female AIS patients ($$p \leq 0.0033$$). Lastly, female control subjects had significantly higher levels of the Cu/Pb molar ratio as compared to males ($$p \leq 0.001$$) (Table 2). ## 4. Discussion At present, few, if any, detailed investigations have been conducted to analyze the status of toxic metals in AIS patients in Podlaskie Voivodeship, Poland. The present study’s results have crucial public health implications, highlighting the presence of an imbalance of trace elements in patients with acute ischemic stroke. The most significant observation in our study was that higher concentrations of Cd in the blood had a crucial impact on the development of ischemic stroke, even at exposure levels that are relatively low. We found that the molar ratios of Cd/Zn and Cd/Pb were significantly higher ($p \leq 0.001$; $p \leq 0.001$, respectively), when the molar ratios of Se/Pb, Se/Cd, Cu/Cd were significantly lower ($$p \leq 0.01$$; $p \leq 0.001$; $p \leq 0.001$, respectively), in AIS patients as compared to control subjects. We also found that patients with higher stages of ICA atherosclerosis, particularly those with 20–$50\%$ ICA stenosis, had higher Cd and Cd/Zn concentrations but lower Cu/Cd and Se/Cd molar ratios. In this research, current smokers had a higher likelihood of LAA etiology, whereas CE etiology was more likely to be found among never-smokers. In contrast, we did not find substantial differences in the concentration of Pb in the blood between AIS patients and control subjects. There is a significant interest in the detection of heavy metals within medical science, given the mounting evidence supporting the connection between environmental pollutants and stroke. Ongoing experimental and epidemiological research is highlighting heavy metal exposure as a possible risk factor for stroke, with some recent studies suggesting a positive association between higher blood-Cd levels and stroke prevalence [5,11,14,32,35,39,40,41,42,65,66]. The results of a systematic review and meta-analysis published recently suggest that chronic exposure to Pb, Cd, and Cu could be linked to an elevated risk of stroke [5]. The systematic review by Dev et al. [ 66] did not provide sufficient evidence to either support or dismiss the relationship between heavy metal exposure and ischemic stroke. However, in our present study, there were no significant fluctuations in relation to blood-Pb concentration in AIS patients, which was also in line with other studies [11,54,67]. It should be pointed out that previous epidemiological studies have produced contradictory findings regarding the correlation between blood-Pb levels and ischemic stroke, findings that align with those of the present study. Most epidemiological studies investigating the link between toxic metals and ischemic stroke have been limited to examining one metal and various methods to measure its concentration. Recent investigations [14,34,68] have presented a novel approach for assessing the risks associated with multiple metals, with an emphasis on the fact that the general public is exposed to numerous metals in daily life [69]. The extensive prevalence of toxic metals in the environment, coupled with the limitations of current analytical techniques and other factors, makes it difficult to set appropriate health-based thresholds for some of these metals. Yet, recent advancements in nanotechnology and sensor technologies have become essential enablers for detecting toxic trace elements [70]. The atherogenic mechanism of Cd may be associated with oxidative stress, inflammation, endothelial dysfunction, and increased lipid synthesis, which may lead to the inhibition of vascular smooth-muscle-cell proliferation [30,50,51,71,72]. Some studies have found that Cd levels within symptomatic carotid atherosclerotic plaques are 50 times higher than within the blood, and concentrations are the highest in the areas of the plaque where ruptures tend to occur [27]. Population studies conducted in Sweden have also revealed a substantial association between Cd levels in the blood and the presence of the soluble urokinase plasminogen activator receptor, a biomarker related to the atherosclerotic process [51,73]. Therefore, the current study’s findings affirm that elevated Cd levels are related to internal carotid atherosclerosis, which has been corroborated by other studies [14,31,35,74]. The Borné et al. study [24] postulates that Cd may be involved in plaque rupture mechanisms. This hypothesis is supported by the fact that exposure to Cd has been linked to prothrombotic and antifibrinolytic effects. In addition, sex (female) and smoking have been identified as risk factors for plaque erosion, and these risk factors are associated with high exposure to Cd in the general population [23]. Although individuals’ blood-Cd concentrations vary according to age, sex, diet, residential area, and smoking status, exposure to Cd may explain disparities in stroke rates due to regional diversity and, thus, differences in levels of exposure among humans [69,71]. The positive alterations observed in the concentrations of the Cd and Cd/Zn molar ratios in our analysis need further medical research to assess if they can be used as standalone biomarkers of atherosclerosis in AIS patients. The presence of plaque and high levels of Cd appears to be linked to both causes of stroke, LAA and SVO [35,75]. Our study revealed statistically significant differences only in the Cu/Pb molar ratios among AIS patients, based on their etiology as classified by the TOAST classification. The group with LAA etiology had lower Cu/Pb molar ratios as compared to the CE- and SVO-etiology groups. Our study revealed statistically significant differences only in Cu/Pb molar ratios among AIS patients, based on their etiology as classified by the TOAST classification. The group with LAA etiology had lower Cu/Pb molar ratios as compared to the CE- and SVO-etiology groups. The impact of smoking on Cd levels in the urine and blood is well-documented [76,77,78,79]. After factoring in smoking habits, most studies indicated significant associations between Cd with carotid artery plaque or intima-media thickness (cIMT) of the carotid artery [23]. The studies mentioned above [14,26,30,32,80] provide strong evidence for the link between Cd exposure and risk of stroke, even after adjusting for smoking status. Other investigations have tried to solve this dilemma through subanalyses limited to non-smokers. Nonetheless, they have arrived at conflicting conclusions, ranging from no correlation to connections discovered between individuals who smoke and those who do not smoke [14,25,25,27,37,38,41,65]. In our study, current smokers among AIS patients were characterized by higher blood-Cd concentrations, Cd/Zn and Cd/Pb molar ratios, and hemoglobin values, but lower HDL-C concentrations, Se/Cd, and Cu/Cd molar ratios. Furthermore, we observed a positive correlation between the stage of ICA atherosclerosis in Doppler ultrasound examination and the Cd and Cd/Zn molar ratios, but a negative correlation with the Cu/Cd and Se/Cd molar ratios. However, no correlations were observed after adjustment for smoking status. It is worth noting that Farenberg et al. discovered that blood-Cd levels had a positive correlation with smoking status, age, serum TG, HbA1c levels, and high-sensitivity C-reactive-protein (hsCRP) values [31]. Furthermore, the prevalent stroke etiology of current smokers in our analysis was LAA etiology, which was also observed in the Fagerberg et al. study [73]. A generalized linear regression model allowed us to demonstrate that factors such as smoking status (current smokers), the coincidence of atrial fibrillation, advanced age, and lower NIHSS on admission significantly increase Cd concentration in AIS patients. Taking smoking into account does not rule out the possibility of residual confounders, yet a large number of studies carried out on never-smokers have found a connection between Cd and ASCVD (atherosclerotic cardiovascular disease) above B-Cd >0.5 μg/L [23]. In never-smokers, diet is the main source of Cd. In smokers, it is becoming increasingly plausible that Cd may, in part, mediate the risk of smoking on ASCVD [74]. The risk of myocardial infarction and ischemic stroke associated with smoking seems to disappear within 5 years of quitting [81]. Furthermore, a cross-sectional study in China indicated that the risk of carotid plaques decreased after 10–19 years of not smoking [82]. The review of recently published medical publications has shed new light on the possibility of interactions between essential elements and toxic metals, such as Cd-Zn. Both deficiency and excess of essential and toxic metals can impair immune functions and inevitably lead to CVD [83,84,85]. Exposure to Cd has been reported to increase the likelihood of the development of atherosclerosis. In contrast, the administration of Zn has the opposite effect in reliable rabbit and mouse models of atherosclerosis [76]. Zn, considered an essential metal, has been found to reduce the negative impacts of Cd [69,86]. The research carried out by Chen et al. found that never smoking and maintaining high serum-Zn levels could potentially mitigate the adverse effects of Cd [41]. Furthermore, some studies have indicated that lower levels of Zn were present in smokers, while other investigations revealed that Zn levels were not significantly affected by smoking [76]. It should be noted that this pattern was observed in our study. However, we did not observe any correlations between Zn and Cd concentrations in AIS patients. Cd and Pb have characteristics similar to those of Zn, and can compete for protein metal-binding sites. Some essential metals, such as Zn, can reduce the intestinal absorption of Cd and Pb, restore homeostasis in the body, and reduce the oxidative stress caused by Cd and Pb [87]. In our previous study, we detected a significant drop in serum Zn and Se levels with elevated concentrations of Cu/Se and Cu/Zn molar ratios in AIS patients. This can probably be attributed to the intense inflammatory state and oxidative stress caused by ischemic stroke [59]. Our previous investigation revealed that individuals with AIS and dyslipidemia had higher Se levels. The modifications observed in Cu, Se, and Zn concentrations require additional study to determine their value as independent biomarkers of atherosclerosis in AIS patients [59]. Surprisingly, only the Zn/Pb and Cd/Zn molar ratios were significantly correlated with HDL levels in the current study, while no significant associations were observed between LDL, TG, TC, non-HDL and toxic elements in AIS patients. The results of numerous studies conducted among humans and animals, and experimental studies show that high exposure to Cd may promote hyperlipidemia, which is characterized by elevated levels of TG, TC, and LDL-C, and decreased HDL-C [23,30,33,40,88,89,90,91,92,93,94]. Furthermore, exposure to Cd and Pb was closely associated with atherogenic changes in a lipid profile [30,89,90,91,94,95,96,97]. The studies conducted by Messner et al. [ 2009] and Rogalska et al. [ 2009] have shown that exposure to Cd can lead to oxidative stress, inflammation, and the impaired functioning of the lining of blood vessels in experimental models [71,98]. Numerous studies have indicated that higher levels of Cd in the blood and urine are associated with a higher risk of inflammatory complications, as evidenced by increased CRP levels in the blood [23,51,99]. This elevation in inflammation is believed to increase the risk of CVD [33,100]. Our analysis revealed that a higher Cu/Cd molar ratio was associated with elevated CRP values. In addition, Cd and Pb have been associated with changes in the coagulation profile, especially fibrinogen levels [85,96,97]. In our study, it was also revealed that there is a significant association between the toxic elements studied and hemostasis parameters. Moreover, various investigations have indicated that the coexistence of Cd exposure and obesity could have a notable influence on the occurrence of prediabetes [52]. The impact of metal pollutants on obesity has been demonstrated through their modulation of adipogenesis and the functioning of adipose tissue [54]. Furthermore, various studies have linked multiple exposures to metals to coronary heart disease and obesity [101,102]. Furthermore, a compilation of metal exposures (Pd, Cd, Hg, As) has been shown to be related to obesity and its associated conditions, such as type 2 diabetes mellitus and hypertension [103]. However, there were no significant correlations between BMI index, type 2 diabetes mellitus, and the toxic elements studied in our studied group of AIS patients. The Global Burden of Diseases Study (GBD) reported that exposure to Pb accounted for approximately $5\%$ of stroke-related deaths and DALYs in 2019 [104]. There is increasing evidence that Pb toxicity is associated with increased oxidative stress due to ROS formation (reactive oxygen species), depletion of antioxidant capacity and increased lipid peroxidation [105,106,107]. Clinical research has revealed that high and low blood levels of Pb can adversely affect cardiovascular health, resulting in an increased risk of cardiovascular diseases, such as stroke [32,54,55,58,95,96,97,108,109,110,111,112,113]. In order to establish a link between trace elements and stroke, Medina Estévez et al. [ 113] evaluated 45 elements and found that Pb was positively associated with ischemic stroke in both univariate and multivariate analyses. However, there were no considerable fluctuations in relation to the blood-Pb concentration in our AIS patients, which was also in line with other similar studies [11,54,67]. Furthermore, long-term exposure to Pb may be correlated with a possible risk of ICA atherosclerosis [97]. The primary purpose of this preliminary evaluation was to measure the concentrations of toxic blood trace elements in AIS patients in Poland, to broaden our understanding of the broad distribution and mortality of ischemic stroke. Our findings go beyond those of previous research, by providing additional evidence of the relationship between toxic trace elements, ischemic stroke, and atherosclerosis, as well as establishing a basis for conventional behavioral risk factors such as smoking and an unhealthy diet. Unlike previous investigations that mostly focused on a single heavy metal level, our research also examined the cumulative effects of multiple essential and toxic trace elements. Evaluating metal mixtures is essential, as these components coexist [114]. Similarly, future research should address the role of common exposures in atherosclerosis. To assess cardiovascular risk through alterations in environmental metals, prospective studies with multiple observations over a period of time are needed. Repeated assessments of multiple metal exposures must be performed to establish critical susceptibility windows. Thus, the discrepancies observed in the presented studies could, to some extent, be attributed to the exposure to metal mixtures that may concurrently contribute to the occurrence of ischemic stroke. It should be noted that this research was limited, since it was carried out in one department, and only one-time data were available from each participant. A single blood/urine sample is insufficient to accurately reflect the total body burden of toxic trace elements in a given region, and thus cannot be taken as an indicator of the epidemiological condition of the population across different geographical regions and varying exposure levels. The study was unable to track toxic element levels before the event of ischemic stroke. Subsequently, it was impossible to demonstrate particular changes in the levels of toxic elements in the blood over a longer time. Smoking status, sex, and age are essential covariates that must be considered when examining the influence of metal mixtures on the chance of developing CVD and stroke [69]. Despite accounting for various confounding factors, it is still conceivable that significant confounding factors, such as exposure to tobacco, were omitted or inadequately taken into consideration. Moreover, due to the limited data, it was not possible to adjust for pack-years of smoking. Furthermore, the self-reported covariates (smoking status) may have induced recall bias. Despite accounting for various confounding factors, it is still possible that significant confounding factors, such as tobacco exposure, were omitted or inadequately considered. Furthermore, due to limited data, it was not possible to adjust for pack-years of smoking. Furthermore, self-reported covariates (smoking status) may have induced recall bias. Despite the elimination of potential confounders in the analysis, the duration of exposure to heavy metals remains uncertain. Consequently, more research needs to be conducted, focusing on never-smokers or collecting more detailed information on tobacco use, including quit-years of former smokers, smoking traces, or biomarkers associated with tobacco users (e.g., nicotine levels). The confounding impact of smoking may not have been properly accounted for, due to our method of measuring exposure, which was accomplished through blood-Pb level, which captures only recent exposure to lead and therefore does not allow cumulative or long-term exposure to be evaluated. Thus, it was uncertain whether the results seen in this study were related to recent or chronic exposure to Pb. ## 5. Conclusions Our research showed that the disturbance of the metal balance, Cd, in particular, plays a crucial role in the pathogenesis of AIS. Furthermore, our results expand on those of previous studies on exposure to Pb and Cd as risk factors for AIS. The findings of the study reinforce the hypothesis that both smoking and blood-Cd concentrations are connected with the incidence of AIS. It is critical to investigate the potential role of exposure to metal mixtures in AIS. An accurate assessment of changes in the molar ratios of essential and toxic trace elements could serve as a valuable indicator of the nutritional status and levels of oxidative stress in AIS patients. The Cd/Zn molar ratio has the potential to serve as a useful biomarker for atherosclerosis in AIS patients. With heavy metal exposure being a critical public health issue worldwide, identifying heavy metal pollutants can play a pivotal role in predicting stroke and devising appropriate primary and secondary prevention and control strategies. Additional research is required to fully understand the impact of exposure to essential and toxic trace elements on the potential mechanisms underlying the development of ischemic stroke. Future studies should seek to establish the optimum levels of essential trace elements in the body and devise effective dietary strategies that can mitigate the risk of stroke resulting from toxic metals. ## References 1. 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--- title: Changes in the Urine Metabolomic Profile in Patients Recovering from Severe COVID-19 authors: - Robert Rosolanka - Peter Liptak - Eva Baranovicova - Anna Bobcakova - Robert Vysehradsky - Martin Duricek - Andrea Kapinova - Dana Dvorska - Zuzana Dankova - Katarina Simekova - Jan Lehotsky - Erika Halasova - Peter Banovcin journal: Metabolites year: 2023 pmcid: PMC10058594 doi: 10.3390/metabo13030364 license: CC BY 4.0 --- # Changes in the Urine Metabolomic Profile in Patients Recovering from Severe COVID-19 ## Abstract Metabolomics is a relatively new research area that focuses mostly on the profiling of selected molecules and metabolites within the organism. A SARS-CoV-2 infection itself can lead to major disturbances in the metabolite profile of the infected individuals. The aim of this study was to analyze metabolomic changes in the urine of patients during the acute phase of COVID-19 and approximately one month after infection in the recovery period. We discuss the observed changes in relation to the alterations resulting from changes in the blood plasma metabolome, as described in our previous study. The metabolome analysis was performed using NMR spectroscopy from the urine of patients and controls. The urine samples were collected at three timepoints, namely upon hospital admission, during hospitalization, and after discharge from the hospital. The acute COVID-19 phase induced massive alterations in the metabolic composition of urine was linked with various changes taking place in the organism. Discriminatory analyses showed the feasibility of successful discrimination of COVID-19 patients from healthy controls based on urinary metabolite levels, with the highest significance assigned to citrate, Hippurate, and pyruvate. Our results show that the metabolomic changes persist one month after the acute phase and that the organism is not fully recovered. ## 1. Introduction Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2), which caused the recent COVID-19 pandemic, is still the subject of ongoing worldwide research in various fields. The SARS-CoV-2 virus primarily targets the lung tissue. However, its impact on other organ systems, such as the gastrointestinal system, circulatory, or central nervous system, has been well described [1,2,3,4,5]. The virus, present in the organism, was able to induce changes in the metabolism of various molecules (e.g., glucose, cholesterol, amino acids, tryptophan, etc.) that are not only important for the virus itself due to survival and reproduction, but also play a crucial role in immune response regulation. Such changes at the level of metabolic processes can be referred to as metabolic reprogramming [6,7]. Viruses are in general not metabolically active, however; in infected patients, they can cause changes at the level of metabolic processes in the human body. Influencing some of these host factors may result in a different disease outcome for the infected individual. Thus, correcting the activity of some metabolic processes can be one of the promising methods for controlling infection and enhancing metabolism [8]. Metabolomics is a relatively new research area that focuses mostly on the profiling of selected molecules and metabolites within the organism. Due to progressive development in the field of data analytics and bioinformatics, metabolomics has started to be widely applied in clinical and biomedical research. The analysis of the human metabolome can contribute to a better understanding of the onset and progression of various diseases and also proves to be a promising tool in the search for new diagnostic and prognostic markers of these diseases [9,10,11]. There is even emerging evidence of a strong correlation between such complex environments as the microbiome and the metabolomic profile of various experimental models [12,13,14]. Thus, understanding the human gut microbiome with the flow of metabolites across several trophic levels, and the creation of microbial biomas, may be the key factor for understanding its health impact [15]. Among other things, several studies that focused on 16S rRNA gene sequencing have shown that COVID-19 can alter not only the upper respiratory microbiome but also the gut microbiome with the loss of a large number of important microbial strains [16]. Thus, the ability to determine the precise metabolomic and metagenomic status of human microbiota could have substantial clinical implications in the future. Since the beginning of the pandemic, research on the use of metabolomics on COVID-19 has been greatly accelerated [17]. SARS-CoV-2 infection itself can lead to major disturbances in the metabolite profile of the infected individuals. These changes can occur at several levels and in various bodily fluids. Although most studies are focused on serum metabolite levels and longitudinal alterations, a few studies have focused on the impairment of urinary metabolism [18,19] especially considering the omics profiling during the disease recovery stage. There is increasing evidence that in some patients, postacute sequelae of SARS-CoV-2 infection may persist for a long time, with significant consequences for their further quality of life. Understanding the pathophysiological processes that take place individually not only in the acute phase of infectious diseases but also in the convalescence stage, appears to be an important milestone for the future and may ultimately benefit the patient. In this study, we wish to freely follow up on our previous work, where we analyzed metabolic changes in blood plasma at three timepoints, focusing on the patients who survived the severe course of SARS-CoV-2 infection requiring hospitalization and oxygen supplementation. Similar to the previous study, where we monitored metabolomic changes in blood plasma in the three timepoints—the acute phase at the time of hospital admission, one week later during hospitalization, and after one month in the recovery phase when the acute phase had passed [20]. In this study, we aimed to evaluate metabolomic changes in the urine. As the majority of the included patients were the same individuals, we discuss the observed changes in relation to current knowledge and to the alterations resulting from changes in blood plasma metabolome, as described previously [20]. In further describing the impact of the altered metabolome on the biochemical and physiological function of an organism, we run a discriminatory analysis to judge the discriminatory power of the system relative to healthy controls. ## 2.1. Patients The sampling for the study was performed from November 2021 until February 2022. A total of twenty-four [24] patients were enrolled in the study with the following exclusion criteria: age under 18 years, pregnancy, and unwillingness or incapability to sign the informed consent. All included patients had compensated chronic diseases. All participants signed the informed consent. The study was approved by the Ethics Committee of the Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Slovakia (Certification code at the US Office for Human Research Protection, US Department of Health and Human Services: IRB00005636 Jessenius Faculty of Medicine, Comenius University in Martin IRB # 1) with identification number: EK $\frac{65}{2021.}$ Every patient included in the study had a SARS-CoV-2 infection confirmed by a polymerase chain reaction (PCR). The study was focused on patients with typical SARS-CoV-2 infection symptoms (fever, cough, and dyspnea) with the goal of achieving a high level of homogeneity (in the means of the COVID-19 presentation) within the cohort. Therefore, only hospitalized patients with a severe course of COVID-19, requiring oxygen supplementation, though not invasive artificial pulmonary ventilation, (based on the National Institutes of Health/NIH/criteria) with X-ray or CT-confirmed pneumonia were included. The first urine in the morning was sampled into a plastic tube. The first sample (sample A, $$n = 24$$) was taken within 24 h of admission to the hospital. The second sample (sample B, $$n = 22$$) was taken on days 5–8 (based on the course of the hospitalization, e.g., early discharge led to a shorter interval between samples A and B) and the third sample (sample C, $$n = 22$$) was taken at a median of 42 days (29–54 days) after the first sample (Figure 1). Blood for standard biochemical and hematological analysis was obtained during every sample-taking occasion. The groups of samples were labeled group A, group B, and group C based on the timepoint labeling. The characterization of the patient group is shown in Table 1 and patients’ biochemical and hematological results at the sampling times are listed in Table 2. ## 2.2. Controls As control samples, the first urine in the morning was used from 24 subjectively healthy volunteers aged at a median of 48 years (IQR 27); female/male, $\frac{15}{9}$, with a negative antigen SARS-CoV-2 test on the sampling day; and reporting not having had acute COVID-19 disease or any positive SARS-CoV-2 test in the three months before sampling. ## 2.3. Urine Sampling Urine was sampled into plastic tubes, centrifuged (2000 rpm, 4 °C, 20 min) within 2 h, and aliquots were stored at −80 °C. After thawing, the urine was centrifuged at 2000 rpm, at room temperature, for 20 min. For the measurement, 400 µL of centrifuged urine were carefully mixed with 200 µL of a stock solution consisting of (500 mM phosphate buffer, pH-meter reading 7.40, and 0.25 mM TSP-d4 (3-(trimethylsilyl)-propionic-2,2,3,3-d4 acid sodium salt in deuterated water) as a chemical shift reference in deuterated water). For measurement, 550 μL of the final mixture was transferred into a 5 mm NMR tube. ## 2.4. NMR Data Acquisition NMR data were acquired on a 600 MHz NMR spectrometer Avance III from Bruker equipped with a TCI (triple resonance) cryoprobe. Initial settings (water suppression frequency, pulse calibration, and shimming) were performed on an independent sample and adopted for measurements. The samples were stored in a Sample Jet at approx. 6 °C before measurement for a maximal time of 3 h. We modified standard Bruker profiling protocols as follows: profiling 1D NOESY with presaturation (noesygppr1d): FID size 64 k, dummy scans 4, number of scans 32, spectral width 20.4750 ppm; COSY with presaturation was acquired for 10 randomly chosen samples (cosygpprqf): FID size 4 k, dummy scans 8, number of scans 1, spectral width 16.0125 ppm; homonuclear J-resolved (jresgpprqf): FID size 8 k, dummy scans 16, number of scans 4; profiling CPMG with presaturation (cpmgpr1d, L4 = 126, d20 = 3 ms): FID size 64 k, dummy scans 4, number of scans 256, spectral width 20.0156 ppm. All experiments were conducted with a relaxation delay of 4 s, and all data were once zero filled. An exponential noise filter was used to introduce 0.3 Hz line broadening before the Fourier transform. Samples were measured at 310 K and randomly ordered for acquisition. The evaluation was performed on cpmg-acquired spectra. ## 2.5. Data Normalization Preanalysis normalization is often based on biological parameters such as creatinine, specific gravity, and osmolality. The creatinine concentration is one of the most commonly used reference factors since the urinary creatinine level is supposed to reflect the overall concentration of metabolites [21]. However, although creatinine excretion is assumed to remain constant across individuals, many factors such as diet, muscle mass, age, and physical activity can affect creatinine levels [22]. The second reliable method for evaluating overall urine metabolite concentration is osmolality, which, together with specific gravity, completes the trio of the most important normalization methods. Osmolality and creatinine are in a direct relationship [22], so the results should be comparable after normalization. In this work, we decided to normalize the data to the urinary level of creatinine as the easiest, most reliable, and most feasible method. ## 2.6. Data Analysis A chemical shift of 0.000 ppm was assigned to the TSP-d4 signal. Spectra were solved using an internal metabolite database, an online human metabolome database (www.hmdb.ca accessed in 1 November 2022) [23], chenomx software (free trial version), and the literature [24,25,26]. For all compounds, the multiplicity of peaks was confirmed in J-resolved spectra, and homonuclear cross peaks were confirmed in a COSY spectra. Spectra were integrated manually and normalized to the integral of the creatinine peak at 3.05 ppm. Metabolites not having appropriate signals for the evaluations—peak overlap, or with unambiguous peak assignment—were excluded from further evaluation. Similarly, metabolites without well-resolved peaks in more than $\frac{3}{4}$ of all samples were also left out of the statistical evaluation. The null hypothesis of equality of population medians among groups was tested by the nonparametric Kruskal–Wallis test, with Dunn’s post hoc test for pairwise comparison. We applied Bonferroni correction to the data to avoid type I error, considering p-value 0.0083 as a threshold to claim significance. Principal component analysis (PCA) and the receiver operating characteristic curves (ROC) derived from the random forest (RF) algorithm were performed using MetaboAnalyst [27,28]. ## 3. Results Altogether, 21 metabolites were identified in the urine samples. However, signals from only 14 were appropriate for further evaluation, meeting the strict criteria, which were no peak overlap, unambiguous assignment, and the possibility of evaluation in a sufficient number of samples. In the first step, we employed PCA analysis to obtain an estimation of the group differences in the course of the COVID-19 disease, together with the controls (Figure 2A), and also in more detail a comparison of patients at the individual COVID-19 sampling times against the controls (Figure 2B–D). The relative concentrations of urine metabolites related to urine creatinine level were used as input variables. When comparing all three sampling times with the controls, samplings A and B differed from healthy individuals, whereas sampling in time C partially overlapped with controls. PCA analysis revealed the possibility of successful statistical separation of the patients in the sampling times A and B against controls. However, for the estimation of the real discriminatory power of the system, a different approach must be used. PCA analysis is often accompanied by PLS-DA, which is not only a 2D projection of multidimensional data but is also enriched with a discriminatory algorithm. However, PLS-DA often overfits data [29] and therewith may result in overoptimistic outcomes. To avoid this shortage, we employed a cross-validated random forest discriminatory algorithm that is not known to overfit the data and is also stable to outliers [30]. As input variables, we used the relative concentrations of metabolites in urine related to creatinine. The results from the RF are summarized in Table 3. As a quantitative parameter to judge the system performance, we used the area under the curve (AUC) value derived from the ROC curve (receiver operating characteristic curve). The system was able to discriminate patients in sampling point A almost ideally against control subjects with AUC = 1 and slightly weaker but still, excellent discrimination was attained for patients in sampling point B against the controls, with AUC = 0.99. Discrimination of patients one month after hospitalization against controls was not ideal, as was already expected from PCA analyses (Figure 2D). However, the resulting value AUC = 0.90 signaled a relatively successful discrimination. The results from further combinations in discriminatory analyses (A-B, A-C, B-C, A-B-C, A-B-C-ctrl) are included in Supplementary Material S1. The statistical evaluation of the differences between the population medians marked 13 metabolites as significantly changed between the groups, with a p-value < 0.05. Bonferroni correction to avoid type I errors with a p-value of 0.0083 to claim significance, excluded TMA, DMA, and 1-methylniacinamid from significantly changed metabolites. The results, together with the relative changes derived from the medians, are summarized in Table 4. ## 4.1. Metabolic Changes in Urine Turnover from glycolytic to ketone-body metabolism in hospitalized COVID-19 patients was demonstrated in previous studies [20,31,32], and just the ability to normalize energy metabolism was suggested as one of the key parameters determining disease outcome [31]. Once in a ketotic state, the human body produces two fundamental substances, 3-hydroxybutyrate for energy utilization and acetoacetate for energy release, where the energy utilization according to need is ensured by their mutual conversion. As a side reaction, acetoacetate decarboxylates nonenzymatically to acetone, which, rather than being metabolized, is excreted from the body by urine, sweat, or breath. In the COVID-19 patients we observed, an increase in acetone level in urine in the acute COVID-19 phase (samplings A and B, Figure 3), as it was similar to our previous study where a ketotic-like state was detected during hospitalization [24]. As ketosis subsided during COVID-19 recovery [24], acetone levels in the urine of patients one month after hospitalization, decreased to being comparable to the level of control subjects. Ketone bodies, found to be increased in COVID-19 patients in the first week after hospitalization [20,31], are synthesized from acetyl-CoA produced by excessive beta-oxidation of fatty acids in the mitochondrion. Both processes, the transfer as well as subsequent oxidation, require the necessary presence of carnitine [33], which can be assumed with the diet or synthesized by the body. At the time of enhanced fatty acids catabolism, more fatty acids need to be transported into the hepatic mitochondria for oxidation, and the demand for carnitine in an organism increases. As shown in the work by Berry-Kravis et al., the levels of plasma carnitine increased in patients on a ketotic diet [34]. Carnitine in urine follows the trend of carnitine in plasma [35], where reabsorption by the kidney plays an important role. Tubular resorption in the kidney of free carnitine takes place at between $98\%$ and $99\%$ unless the transporters become saturated, and further carnitine overload leads to increased carnitine urine levels [36,37]. In parallel with acute ketosis found in hospitalized COVID-19 patients [24], overproduced carnitine is to be excreted by the urine. In our study, elevated carnitine levels in urine were more pronounced at sampling time B, where most likely the carnitine production exceeded the need. The urine carnitine level in COVID-19 patients decreased to the level of controls one month after hospitalization when the ketotic condition passed and the fatty acids utilization decreased by metabolism alterations. Hippurate, a mammalian microbial cometabolite, is formed in the mitochondrial matrix in the liver and kidney (renal cortex) [38] and is a normal constituent of the endogenous urinary metabolite profile. Its relative urinary abundance seems to be linked with metabolic state, as it was reversely related to BMI [39], and increased in urine in type one diabetes [40] and type two patients [41]. Extensive investigations of the role of gut microbiota in the metabolism of polyphenolic compounds (hippurate precursors) [42] showed that that antibiotic-induced suppression of the gut microbiota results in a reduction in the excretion of hippurate and related metabolites [38,42]. According to the last finding, we supposed that, in this study, the observed decrease in urinary hippurate in COVID-19 patients was related to antibiotic treatment that the patients underwent. Interestingly, the urinary hippurate level did not fully recover one month after hospitalization, which suggests still insufficient intestinal microbiota colonization one month after acute COVID-19 disease. In our work we observed the interesting dynamics of urine hypoxanthine levels found to be increased in COVID-19 patients on the first day against the controls, followed by a more pronounced increase one week later and achieving the control level one month after hospitalization. Elevated hypoxanthine levels in blood serum were found in COVID-19 patients previously by Dogan et al. [ 43]. Inflammation and hypoxia induce the release of ATP from intracellular stores to extracellular space, and its conversion to adenosine monophosphate (AMP), which is then metabolized to adenosine, inosine, and hypoxanthine. This process makes hypoxanthine concentration in the blood a sensitive parameter of tissue hypoxia and ischemia [44]. After tissue damage following ATP depletion, there may be a prolonged excessive excretion that lasts at least two to three days [45]. Based on this, the observed increase in urinary hypoxanthine in COVID-19 patients could be explained as a result of hypoxic and inflammatory tissue damage. The most prominent increase observed one week after hospitalization (Figure 3), could be due to a particular time delay in hypoxanthine clearance, backwardly reflecting the pathological processes in the organism and disease severity. Citrate is a central metabolite of the energy-forming Krebs cycle. It is freely filtered at the kidney glomerulus, and then, in the amount of 65–$90\%$, is reabsorbed in the proximal tubule, leaving about 10–$35\%$ of the filtered excreted in the urine [46,47]. Interestingly, it can be renally metabolized in the Krebs cycle to HCO3- and consequently represents a potential base, indicating its possible, though not extensively researched role, in the acid–base balance [47]. Further, it also serves as metabolic fuel for the kidney and an endogenous inhibitor of calcium kidney stones [47], and its low urinary levels are a known risk factor for the development of calcium kidney stones [48]. Its urinary levels were markedly decreased in the initial COVID-19 phase, though systematically increased during hospitalization and one month after, heading towards the levels of the controls. The etiology of hypocitraturia is very diverse, including the ketotic state [42,43]. In connection with this, urinary citrate levels in COVID-19 patients inversely followed the dynamics of ketosis described in blood plasma in our previous paper [20] and could be linked to the stabilization of mitochondrial energy metabolism during the tendency to recover the energy metabolism from the utilization of ketone-bodies back to glycolysis [49]. The next metabolite showing significant changes in urine in COVID-19 patients was formate, which is produced from a variety of metabolic sources. Its principal function is as a source of one carbon groups included in purine synthesis and the provision of methyl groups for synthetic, regulatory, and epigenetic methylation reactions with the active folate [50]. Its elevated clearance in urine may be a sign of impaired one carbon metabolism. A very similar time course of urinary alanine levels was observed in this study in urine, as it was observed in the blood plasma in COVID-19 patients; a decrease in the acute phase in time of hospital admission [20], achieving levels of healthy individuals already one week as well as one month later. Alanine (together with glutamine) is responsible for the detoxification of extrahepatic tissues and muscles from metabolically produced tissue-toxic NH3. Decreased alanine plasma [20], as well as urine levels found in this study, may suggest a slowdown in the nitrogen shuttle into the liver and potency for liver gluconeogenesis. In other words, alterations in the metabolic rate in an organism. This suggestion is supported by the corresponding increase of BCAAs and BCKAs in blood plasma in the previous study [20]. Furthermore, in plasma [20] as well as in urine (Table 4), decreased pyruvate signals a slowdown of glycolysis, which is in parallel with the observed hyperglycemia—a decreased utilization of glucose [20]. An increase in tyrosine may be produced by its overproduction from phenylalanine or insufficient utilization. Based on our previous study [20] we suggest that in patients with acute severe COVID-19, the use of tyrosine is lowered which may result in the underproduction of thyroid hormones and tyrosine-derived neurotransmitters such as dopamine and norepinephrine. ## 4.2. Multivariate and Discriminatory Analysis The 2D visualization of metabolic features in urine in patients at the time of the acute COVID-19 phase and one month after hospitalization, together with healthy controls, is shown in Figure 2A. The urine metabolomes belonging to the greatest clinical COVID-19 manifestation, sampling points A and B, are visually similar, however, they are different from the metabolome in sampling point C and the controls, which are partially overlapping. This trend was confirmed in the next PCA analyses, where binary systems A, B, and C were evaluated against controls (Figure 2B–D). The high potential of metabolomics in the field of biomarkers was already demonstrated by the successful discrimination of COVID-19 patients in the acute phase against controls using blood plasma levels of metabolites [20,31]. In this work, we also employed the RF algorithm that includes cross validation via balanced subsampling. It works with two-thirds of the data for training and the rest for testing for regression, and about $70\%$ of the data for training and the rest for testing during classification to overcome the negative features of training and testing on the same data. This approach may partially substitute the validation of an independent dataset; however, it cannot fully replace clinical validation. We used relative concentrations of metabolites in urine, expressed by the spectral integrals of particular NMR regions related to the signal of creatinine as input variables for the RF algorithm. In the case of highly correlating predictors, RF may label some of them as unimportant, therefore the RF was run ten times. Within the RF reruns, metabolites are permuted a little in the order of importance. The results, as summarized in Table 3, showed excellent discrimination of patients at sampling point A against controls with AUC = 1 (Figure 4), where the metabolites of the highest importance were hippurate, citrate, pyruvate, alanine, and hypoxanthine. For samples taken one week later, sampling point B, the discrimination was almost ideal with AUC = 0.99 (Figure 4), which was achieved using relative abundances of the metabolites citrate, hippurate, carnitine, hypoxanthine, and pyruvate. Slightly weaker with AUC = 0.90 (Figure 4), though still very good, was the discrimination of patients in the post-COVID phase one month after hospitalization, when all evaluated metabolites were included. These findings point out the extensive metabolomic changes in urine caused by severe COVID-19 course in hospitalized patients, present not only in the acute phase but also one month after. Note that when compared with our previous study [20], the urine metabolome performed comparably with the blood plasma metabolome with discriminating patients in sampling time A against the controls (both AUC = 1), and also similarly in sampling time B (AUC = 0.948 for blood plasma against 0.993 for urine) and sampling time C (AUC = 0.932 for blood plasma and AUC = 0.901 for urine). As both metabolomes are closely linked, this result is not surprising, and from the discriminatory point of view, both are biological samples of the same informative value. ## 5. Conclusions The longitudinal dynamics of alterations in urine metabolites in patients hospitalized with severe COVID-19 disease were monitored at three timepoints. The acute COVID-19 phase induced massive alterations in the metabolic composition of urine linked with various changes taking place in the organism. The increase in the urine levels of acetone and carnitine levels in the first week after hospital admission was linked with turnover in energy metabolism from glycolytic to ketone bodies, already known from other studies on blood plasma. Levels of both metabolites normalized with the return to glycolysis as the main energy-gaining process. Strong antibiotic treatment probably led to a decrease in urinary hippurate levels in COVID-19 patients. The urinary hippurate did not fully recover one month after hospitalization, which can point to still insufficient intestinal microbionta colonization one month after acute COVID-19 disease. Further, the increase in urinary levels of hypoxanthine in COVID-19 patients, most prominent one week after hospitalization, could be due to a particular time delay in hypoxanthine clearance reflecting backwardly the pathological processes, such as hypoxic and inflammatory tissue damage in the organism and disease severity. The initial decrease in alanine levels in urine, similar to those found in blood plasma in previous studies, suggests a slowdown in the nitrogen shuttle into the liver. In other words, alterations in the metabolic rate of an organism. This normalized with the time of treatment. Through the changes of other metabolites, other processes occurring in the body could be suggested, such as the normalization of initially decreased urinary citrate levels. This can be linked with the stabilization of mitochondrial energy metabolism during the tendency to recover the energy metabolism from the utilization of ketone bodies back to glycolysis. Further, the lowered utilization of tyrosine may result in the underproduction of thyroid hormones, as well as tyrosine-derived neurotransmitters such as dopamine and norepinephrine. Discriminatory analyses showed the feasibility of successful discrimination of COVID-19 patients from healthy controls based on urinary metabolites levels on the first day when admitted to the hospital, with AUC = 1, the fourth to the seventh day with AUC = 0.989, and one month later with AUC = 0.90, where the metabolites citrate, hippurate, and pyruvate were marked as of the highest importance. The last result shows that the metabolomic changes persist one month after the acute phase, and the organism’s recovery is not fully achieved. ## References 1. Adil M.T., Rahman R., Whitelaw D., Jain V., Al-Taan O., Rashid F., Munasinghe A., Jambulingam P.. SARS-CoV-2 and the pandemic of COVID-19. Postgrad. Med. J. (2021) 97 110-116. DOI: 10.1136/postgradmedj-2020-138386 2. Siddiqi H.K., Libby P., Ridker P.M.. COVID-19—A vascular disease. Trends Cardiovasc. Med. (2021) 31 1-5. DOI: 10.1016/j.tcm.2020.10.005 3. 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--- title: Anti-Inflammatory Salidroside Delivery from Chitin Hydrogels for NIR-II Image-Guided Therapy of Atopic Dermatitis authors: - Shengnan He - Fang Xie - Wuyue Su - Haibin Luo - Deliang Chen - Jie Cai - Xuechuan Hong journal: Journal of Functional Biomaterials year: 2023 pmcid: PMC10058600 doi: 10.3390/jfb14030150 license: CC BY 4.0 --- # Anti-Inflammatory Salidroside Delivery from Chitin Hydrogels for NIR-II Image-Guided Therapy of Atopic Dermatitis ## Abstract Atopic dermatitis (AD) is the most common heterogeneous skin disease. Currently, effective primary prevention approaches that hamper the occurrence of mild to moderate AD have not been reported. In this work, the quaternized β-chitin dextran (QCOD) hydrogel was adopted as a topical carrier system for topical and transdermal delivery of salidroside for the first time. The cumulative release value of salidroside reached ~$82\%$ after 72 h at pH 7.4, while in vitro drug release experiments proved that QCOD@Sal (QCOD@Salidroside) has a good, sustained release effect, and the effect of QCOD@Sal on atopic dermatitis mice was further investigated. QCOD@Sal could promote skin repair or AD by modulating inflammatory factors TNF-α and IL-6 without skin irritation. The present study also evaluated NIR-II image-guided therapy (NIR-II, 1000–1700 nm) of AD using QCOD@Sal. The treatment process of AD was monitored in real-time, and the extent of skin lesions and immune factors were correlated with the NIR-II fluorescence signals. These attractive results provide a new perspective for designing NIR-II probes for NIR-II imaging and image-guided therapy with QCOD@Sal. ## 1. Introduction Atopic dermatitis (AD) is one of the common clinical chronic diseases with intense itching [1,2,3]. AD is a genetic predisposition, which is difficult to cure and relapses with diseases, such as allergic rhinitis and asthma, which severely influences the patient’s quality of life [4,5]. The pathophysiology of AD is attributed to a number of factors, such as inflammation, T cell infiltration, IgE-mediated sensitization, and neuroinflammation [3,6]. The main goals of AD therapy are to reduce skin inflammation and dysbiosis, improve the skin barrier, and avoid relevant disease triggers [7]. Current treatments for AD include anti-inflammatory agents such as corticosteroids, immunosuppressants, topical emollients, and phototherapy [8]. Currently, the effective primary prevention approaches that hamper the occurrence of mild to moderate AD have not been reported. Thus, developing targeted small-molecule drugs and biological therapies for moderate-to-severe AD diseases is in high demand. The progression and severity of AD could be assessed by the Scoring Atopic Dermatitis (SCORAD) index or Eczema Area and Severity Index (EASI) [9]. However, these visual assessments are semi-quantitative and require experience. Hence, it is very desirable to have a non-invasive assessment during the therapeutic intervention and clinical trials. Recently, Raman confocal microspectroscopy (RCM) and optical coherence tomography (OCT) were used to assess the structural and functional abnormalities of AD in vivo [10,11]. Fluorescent imaging in the second near-infrared window (NIR-II, 1000–1700 nm) [12,13,14], first introduced in 2009, is an emerging imaging technique that offers non-invasive and higher-resolution images [12,15,16,17,18]. NIR-II imaging provides deep-seated anatomical and physiological imaging with micron-level resolution at the millimeter depth [18,19,20,21]. With these resolutions, the vascular transformation and drug efficacy assessment of AD could be detected by NIR-II imaging [22]. Rhodiola rosea is a perennial herb that originated in southwest China and the Himalayan Mountains [23,24]. Salidroside is the main active component of Rhodiola rosea. Salidroside is soluble in water and a very weakly acidic compound that has pharmacological effects against cerebral ischemia/reperfusion [25,26], renal fibrosis [27], nonalcoholic fatty liver, and myocardial injury [28]. It also could alleviate lipid accumulation and inflammatory responses in primary hepatocytes after palmitic acid/oleic acid stimulation [29,30,31,32,33]. In addition, salidroside can effectively prevent high-fat/high-cholesterol-diet-induced NASH (non-alcoholic steatohepatitis) progression by regulating glucose metabolism dysregulation [34,35], insulin resistance, lipid accumulation, inflammation, and fibrosis. In vivo and in vitro experiments have also demonstrated that salidroside could promote AMPK, NF-κB, IRF1/USF1, and KLF4/eNOS signaling pathways during the course of salidroside therapy [36,37]. However, there is still a lack of visual imaging evidence and the relevant mechanism from the image-guided salidroside therapy of AD. Hydrogels, consisting of swellable networks of natural or synthetic polymers with high load-bearing capacity, have been widely used as tissue engineering scaffolds or delivery vehicles for therapeutic agents [38]. Common natural polymers for hydrogel synthesis are alginate, chitin/chitosan, gelatin, agarose, hyaluronic acids, cellulose, and other components [39,40,41]. Chitin, one of the most abundant amino polysaccharides in nature, with excellent biocompatibility, biodegradability, and bioactivity, has been extensively exploited in the last decades [42,43]. Nevertheless, the applications and developments are still limited due to their poor solubility and physiologically inertness. Recently, we have reported a green and efficient KOH/urea aqueous solution with which to construct high-strength chitin and chitosan hydrogels, films, and fibers [44,45,46,47,48,49,50]. The amazing results inspired Cai et al. to develop novel self-healing QCOD hydrogels based on β-chitin under physiological conditions by dynamic Schiff base linkage between the amino group of quaternized β-chitin (QC) and the aldehyde group of oxidized dextran (OD), while QCOD hydrogels have demonstrated excellent biocompatibility, capacity, and potential to be a depot for sustained release [51]. In this paper, the quaternized β-chitin/dextran (QCOD) hydrogel containing salidroside was designed, synthesized, and characterized as a topical carrier system for topical and transdermal delivery. The therapeutic mechanism of QCOD@Sal against AD was then systematically investigated. Finally, a NIR-II fluorophore HLA4P [21] for high-resolution NIR-II fluorescence imaging and NIR-II image-guided therapy of AD, using QCOD@Sal was studied. The treatment process of AD was dynamically monitored in real-time. These attractive results provide a new perspective for designing controlled drug delivery through the skin and improving the flexibility and therapeutic efficiency of AD. ## 2.1. Materials and Reagents A 4:1 ratio of acetone (Bidepharm, Shanghai, China) and olive oil (Aladdin Biochemistry, Shanghai, China) was used to dissolve 1-fluoro-2,4-dinitrobenzene (DNFB, Tokyo Chemical Industry, Tokyo, Japan) [52]. The resulting DNFB solution was used in an animal model of AD [52,53,54,55]. The positive drug, dexamethasone acetate cream (Sanjiu Medical & Pharmaceutical Co., Guangzhou, China). All other chemicals and solvents were analytical grade. Squid pens were purchased from Zhejiang Jinke Company (Taizhou, China), and β-chitin was purified from squid pens according to our previous study [49]. Dextran, 2,3-epoxypropyltrimethylamonium chloride (EPTMAC) was purchased from Shanghai Chemical Reagent (Shanghai, China). Penicillin–streptomycin, RPMI-1640, and trypsin were purchased from Biological Industries (Shanghai, China), and fetal bovine serum (FBS) and Dulbecco’s phosphate-buffered saline (PBS) were purchased from HycloneTM (Shanghai, China). The 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) and the Calcein-AM/propidium iodide (PI) double stain kits were purchased from Shanghai Yusheng Biological Company (Shanghai, China). ## 2.2. Synthesis of Quaternized Chitin (QC) and Oxidized Dextran (OD) QC was synthesized according to the previous work, with a minor modification (Figure S1) [56]. A total of 1.0 g of purified β-chitin powder was dispersed into a mixed solution of KOH/urea/H2O in a ratio of 20:4:75 (w/w/w) to obtain a suspension (1 wt%). Then, it was stirred at −30 °C for ~30 min to form a clear and viscous chitin solution. EPTMAC (EPTMAC: N -acetyl- D -glucosamine units (GlcNAcU) = 8:1 mol/mol) was added to the chitin solution and stirred at 40 °C for an additional 24 h. The mixture was neutralized with hydrochloric acid and the resulting quaternized chitin derivatives were dialyzed in distilled water using a dialysis membrane for more than 7 days. The final product was freeze-dried and stored in a moisture-free desiccator prior to use. OD was prepared according to previous work [51]. Briefly, an aqueous dextran solution (2.0 g/200 mL distilled water) was oxidized with 1.0 g of NaIO4 at 25 °C for 2.5 h. The reaction was quenched by adding 0.5 mL of ethylene glycol, and the mixture was stirred for an additional 1 h. The above solution was, then, dialyzed in distilled water and freeze-dried. ## 2.3. Preparation and Characterization of QCOD Hydrogels QC was dissolved in a phosphate buffer solution (PBS, pH 7.4) or physiological saline at a concentration of $1.0\%$ (w/v). OD was dissolved in a phosphate buffer solution (PBS, pH 7.4) or physiological saline at a concentration of $2.0\%$ (w/v). The QCOD hydrogels were obtained by mixing equal volumes of the QC and OD solutions at 25 °C (Figure S2). The content of aldehyde groups was determined by hydroxylamine hydrochloride titration [57], and the degree of oxidation was determined to be 1.10 mmol (CHO)/g. The degree of quaternization (DQ) was determined by conductometric titration of the Cl− ion concentration using a standard AgNO3 solution in water [58]. The degree of deacetylation (DD) of QC was determined by the two-abrupt-change potentiometric titration method [59]. The weight-average molecular weight (Mw) was measured by size exclusion chromatography (SEC) with multi-angle static light scattering (MALS) (DAWN HELLEOS-II, Wyatt, USA, a He–Ne laser, λ = 663.4 nm), a differential refractometer (RI) (Opitilab T-rEX, λ = 658.0 nm), and a capillary viscosity detector (ViscoStar-II), as previously described, with a 0.1 M NH4Ac/HAc aqueous solution as the eluent and at a flow rate of 0.5 mL/min. Nuclear magnetic resonance (NMR) measurements were carried out on a Varian INOVA-600 spectrometer in the proton noise decoupling mode with deuterated water (D2O) as the solvent. The compressive strength of the hydrogels was determined on a Discovery HR-2 Rheometer (TA Instruments, Framingham, MA, USA). The specific test methods were as follows: The QC and OD solutions were rapidly mixed and placed on the rheometer plate. The upper plate was immediately lowered to a measurement gap size of 0.3 mm. The rheology properties of QCOD hydrogels were, then, measured using a Discovery HR-2 Rheometer (TA Instruments, USA) with the steel parallel-plate geometry (40 mm diameter). Strain amplitudes were determined and set to $1\%$ to ensure that all measurements were performed within the linear viscoelastic regime. Time-sweep tests were performed at 37 °C using a constant angular frequency of 10 rad/s to record the storage modulus (G′), and loss modulus (G″) versus time for the QCOD hydrogels. Frequency-(ω) sweep tests from 0.1 to 100 rad/s were performed in the linear viscoelastic region of QCOD hydrogels at 37 °C after 1 h of pre-gelation. The strain amplitude of the oscillations was switched from a low level (γ = $1\%$ at each interval of 2 min) to a high level (γ = $350\%$ at each interval of 2 min), and three cycles were performed in the experiments. The moisture retention experiment of the hydrogels was carried out in a closed desiccator containing desiccant, using pure water and dexamethasone ointment as the negative control and positive control, respectively, to measure the time-related water loss curve of the QCOD hydrogels. A certain mass (W0) of the hydrogels, water, or dexamethasone ointment was taken and placed in the desiccator; then, the samples were weighed at different time intervals (Wt), and the water loss rate was calculated at different times using the following equation:Water loss rate (%) = (W0 − Wt)/W0 × 100 ## 2.4. Preparation of QCOD@Sal Hydrogels QC was dissolved in phosphate buffer solution (PBS, pH 7.4) or physiological saline at a concentration of $1.0\%$ (w/v). OD and salidroside were dissolved in phosphate buffer solution (PBS, pH 7.4) or physiological saline at a concentration of $2.0\%$ (w/v). The OD solution (0.25 mL) containing salidroside and QC solution (0.25 mL) were mixed uniformly at 25 °C before it was settled for 2 min to obtain the salidroside-loaded hydrogel (0.5 mL). In the cell and animal experiments, the concentration of salidroside was $0.25\%$. ## 2.5. The Controlled Release of Salidroside In Vitro The standard curve of salidroside aqueous solution at 275 nm was first determined ($y = 0.0477$x + 0.00607, y: the UV absorbance of salidroside aqueous solution at 275 nm, x: the concentration of the salidroside aqueous solution, µg/mL). Firstly, different concentrations of the salidroside aqueous solution (9.375, 12.5, 15.625, 25, 31.25, 50, 62.5, 83.33, 125, and 250 μg/mL) were prepared, then, the absorbance was measured at 275 nm by UV spectrophotometer, and finally, the absorbance values and solution concentrations were used as the horizontal and vertical coordinates to make the curves and perform the standard curve (Figure S4). The OD solution (0.25 mL), containing salidroside (5 mg/mL), and the QC solution (0.25 mL) were mixed uniformly at 25 °C, and then, it was settled for 2 min to obtain salidroside-loaded hydrogels (0.5 mL). Salidroside-loaded hydrogels (0.5 mL) were immersed in 2 mL of PBS at pH 5.0 or 7.4 at 37 °C. The concentration of salidroside in all hydrogels was 2.5 mg/mL in 0.5 mL, with three parallel sets of samples at each time point. Furthermore, at predetermined time intervals (1 h, 2 h, 4 h, 6 h, 8 h, 12 h, 24 h, 36 h, and 72 h), 1.2 mL of the incubated solution was removed and the UV absorbance was recorded at 275 nm. The UV absorbance at 275 nm was calculated by bringing in the standard curve formula to determine the concentration of salidroside (Ax). The salidroside aqueous solution (2.5 mg/mL, 0.5 mL), immersed in 2 mL of PBS at pH 5.0 and 7.4, were used as the control, while the UV absorbance of PBS at 275 nm, at predetermined time intervals, was recorded to determine the concentration of salidroside (A1). The controlled release of salidroside in the hydrogel was determined by the following formula:Release of salidroside (%) = AX/A1 × 100 ## 2.6. MTT Cytotoxicity Assay Mouse fibroblast (L929) cells were propagated in RPMI-1640 with $10\%$ FBS and $1\%$ penicillin-streptomycin. To evaluate the cytotoxicity of the QCOD hydrogels and QCOD@Sal hydrogels, the cell suspension (~5 × 103 cells/well) was seeded in 96-well tissue culture plates and incubated in 200 μL of RPMI-1640 for 24 h. The cell culture medium was then replaced with fresh media containing QCOD hydrogels (10 μL) or QCOD@Sal hydrogels (10 μL). The MTT assay was used to assess the cell viability after 1, 2, and 3 days of incubation. After 1, 2, and 3 days of incubation, 10 µL of MTT (5 mg/mL) solution was added to each well and incubated for an additional 4 h. The supernatant was discarded, and dimethyl sulfoxide (DMSO) was added at 200 µL/well and shaken for ~10 min until the blue methane crystals were dissolved. The cells containing only medium were used as the control. The absorbance at 570 nm was measured and cell viability was calculated using the following formula:The cell viability (%) = OD570sample/OD570control × 100 The cell viability was also characterized using a live/dead assay kit (Calcein AM/PI). Calcein AM is a dye that can enter into the cell and be hydrolyzed by esterase to yield green fluorescence (excitation at 490 nm and emission at 515 nm). The PI dye is non-cell permeable and can only stain dead cells with red fluorescence when interacting with cellular DNA (excitation wavelength 535 nm, emission wavelength 617 nm). After 1, 2, and 3 days of co-culturing cells (1 × 104 cells/well) and hydrogels (50 μL) in 24-well tissue culture plates, the cell-seeded samples were washed thoroughly with PBS and incubated in a standard working dye solution of Calcein AM/PI (5 µL) and PBS (200 µL) for 30 min. After again washing with PBS, the sample images were obtained using a fluorescence microscope (Leica, Wetzlar, Germany). ## 2.7. Hemolysis Assay The whole blood was collected from mice and centrifuged at 1000 rpm for 10 min. After centrifugation, the supernatant was removed and washed with PBS (3 × 10 mL) until it was no longer red and cloudy. Deposited red blood cells were diluted with PBS to obtain a suspension of red blood cells at a concentration of $5\%$ v/v. The hydrogel was mixed with red blood cells (1:1). The groups were divided into the negative control group, the positive control group, the QCOD group, and the QCOD@Sal group. The negative control group was prepared from 200 microliters of PBS buffer and 200 microliters of red blood cell suspension. The positive control group consisted of 200 microliters of primary water and 200 microliters of red blood cell suspension. The QCOD group was composed of 200 microliters of QCOD hydrogel and 200 microliters of red blood cell suspension. A total of 200 microliters of QCOD@Sal was mixed with 200 microliters of red blood cells, then, the supernatant was centrifuged and placed in a 96-well plate, 100 microliters per well, and each sample was re-welled 4 times. The absorbance was measured at a wavelength of 540 nm. The hemolysis rate of the hydrogel was calculated using the following equation:Hemolysis rate (%) = (Aexperimental group − Anegative control group)/(Apositive control − Anegative control group) × $100\%$ ## 2.8. Animal Models and In Vivo Therapy For the experimental animals, six-week-old male BALB/c mice (Laboratory Animal Center, China Three Gorges University, Animal ethics: WAEF2021-0016) were purchased and kept in the individually ventilated cages (IVC) system in the laboratory animal center of Wuhan University, maintaining sufficient drinking water and feed. All animal experiments were approved by the Wuhan University Animal Ethics Committee and conducted according to the ARRIVE guidelines. A total of 30 male BALB/c mice (age, 6–8 weeks; weight, 18–20 g; $$n = 6$$/group) were purchased from China Three Gorges University and acclimatized for one week after being transferred to the individually ventilated cage system. The hair on the back of the mice was removed over an area of 3 × 2 cm using a depilatory paste one day before the following experiment. On days 1, 2, 3, and 4, the mice were sensitized with a $0.5\%$ DNFB (acetone:olive oil = 4:1, 100 μL) on the shaved areas. On day 9, the mice were sensitized with $0.2\%$ DNFB (100 μL) to induce an AD-like phenotype. In the control group, the acetone and olive oil mixture (4:1, 100 μL) was applied to the back area of mice at the same time. The mice were photographed every two days and the skin severity was evaluated according to SCORing atopic dermatitis. The erythema/deepening color, edema/popularity, exudation/crusting, exfoliation, mossy/itchy rash, and dryness were evaluated. The maximum score for each item was 3 points, and the maximum score for each group was 18 points. After the successful modeling, all mice were divided into five groups, the normal group (normal), the control group treated with saline, the QCOD group treated with QCOD, the QCOD@Sal group treated with QCOD@Sal, and the DEX group treated with 0.1 mg/kg dexamethasone (DEX). For the treatment, QCOD@Sal was daubed every day ($0.25\%$ per application) [60], and the daubed position was the same. At the end of the study, all the animals were anesthetized with pentobarbital sodium. Blood was collected and skin samples were collected for analysis. ## 2.9. Antioxidant Activity of the Hydrogel The antioxidant efficiency of QCOD@Sal hydrogels was evaluated by scavenging the stable 2, 2-diphenyl-1-picrylhydrazyl (DPPH) free radicals (Figure S5). ## 2.10. NIR-II Imaging and Image-Guided Therapy of AD All NIR-II fluorescent images were collected using the NIR-II imaging system (Suzhou NIR-Optics Technologies Co., Ltd, Suzhou, China, 808 nm, 3.5 mW cm−2, 1000 nm LP). The mice were anesthetized by pentobarbital sodium and mounted at a height of 12 cm during NIR-II imaging of AD. There were five groups: the AD group, QCOD@Sal group, QCOD group, DEX group, and NOR group. Each group had six mice. After the treatment of AD with QCOD, QCOD@Sal, or DEX, the NIR-II probe HLA4P was injected into the tail vein (Figure S6). Li [35] provided the synthetic route of the probe. Then, the back skin damage was visualized in real-time on days 5, 10, and 15. The therapeutic effect was reflected according to the NIR-II fluorescence intensity (FL. intensity) (Figure S7). ## 2.11. Measurement of IL-6 and TNF-α Release and Blood Routine Examination Blood was collected from each mouse at the end of the experiment. The whole blood samples should be placed at room temperature for 2 h or 4 °C overnight and then, separated at 3000 rpm, 2–8 °C, for 15 min. The supernatant was taken for immediate detection. ELISA kit (Servicebio, Wuhan, China) was used for the analysis of IL-6 and TNF-α release, and the operation was carried out according to the instructions. The absorbance value was read at 450 nm with a microplate reader (Spark, Männedorf, Switzerland). A blood routine examination was performed using the automatic blood cell analyzer (BC-2800VET, Mindray Animal Medical, Shenzhen, China). ## 2.12. Histological Analysis To evaluate the histology of skin tissue, skin tissues from BALB/c mice were taken and fixed with a $4\%$ paraformaldehyde solution. Tissue samples were stained by H&E, TUNEL, and ROS. The procedure for H&E staining is as follows: After the treatment of the mice, the skin, about 1 cm × 1 cm on the back of the mice, was dissected with surgical scissors, and the removed skin was fixed in $4\%$ paraformaldehyde solution. The detailed procedure for H&E staining: The sections were placed into a staining cylinder and stained with hematoxylin staining solution for 10 min. The cut was removed and washed with the staining cup water until the sections were colorless. The cells were differentiated with $1\%$ hydrochloric ethanol differentiation solution for 3 s, followed by rinsing with water for 5 min. Then, the sections were stained with eosin for 5 min, followed by immersion in water for 2 min. The sections were successively dehydrated with $80\%$ ethanol, $90\%$ ethanol, $95\%$ ethanol, and $100\%$ ethanol for 2 min. Finally, the slices were placed in xylene I for 2 min and placed in xylene II for 2 min. After drying the xylene on the back side, the neutral resin was added to the front side to seal the slices. The typical histopathological changes of the tissues were observed under a 400 light microscope (ECLIPSE Ci, Nikon, Tokyo, Japan) after staining with an H&E staining kit (Pinofil Biotechnology Co., Ltd., Pinofil, Wuhan, China). The TUNEL staining process was as follows: The frozen tissues were dehydrated with sucrose and then embedded by OCT. The embedded blocks were frozen and sliced. Before the experiment, the slices were taken out and placed on the staining rack for 15 min with a fixed solution, and then, treated at 37 °C for 5 min with protease K (in situ Cell Death Detection Kit, POD). Then, the slices were incubated at 37 °C for 2 h. After DAPI staining (Beyotime C1002, Beyotime, Shanghai, China), the slices were imaged under a fluorescence microscope (ECLIPSE Ci-L, Nikon, Tokyo, Japan). ROS determination: The frozen sections were rewarmed, and the pen circles were organized. The slices were stained with DHE (Sigma D7008) and incubated at 37 °C for 30 min in the dark condition. Then, the slices were stained with DAPI dye solution (Beyotime C1002, Beyotime, Shanghai, China) for 10 min in the dark and sealed. The sections were observed under an inverted fluorescence microscope (ECLIPSE Ci-L, Nikon, Tokyo, Japan) and the images were collected. ## 2.13. Statistical Analysis All statistical data were performed using GraphPad Prism 9.0 and presented as means ± standard deviation. Data are presented as mean ± S.D. Comparisons of means of ≥3 groups were performed by analysis of variance (ANOVA) and the existence of individual differences, in case of significant F values at ANOVA, were assessed by multiple contrasts. Values of p* < 0.05 were considered statistically significant, p < 0.01 was considered statistically significant, and p* < 0.001 was considered extremely significant. ## 3.1. Preparation and Characterization of QCOD and QCOD@Sal Hydrogels As shown in Figure S1, the quaternization of chitin was first carried out at 40 °C with a degree of deacetylation (DD) of $35\%$ and a weight-average molecular weight (Mw) of 1.6 × 105 g/mol. The quaternized chitin (QC) was homogeneously synthesized in an aqueous KOH/urea solution through a high-efficiency, energy-saving, green pathway (Figure S1). On the other hand, the oxidized dextran (OD) was obtained by oxidation reaction. The structures of QC and OD were characterized by 1H NMR analysis and potentiometric titration (Figure S3). A 2.69 ppm chemical shift was the C2 proton peak of the free amino group of the quaternary chitin. The results indicated that a large number of amino groups were generated, and the quaternary ammonium reaction of chitin was successfully deacetylated under a condition of strong alkali and high temperature. The results were consistent with the results of the potentiometric titration. In addition, the new signal of oxidized dextran at 4–6 ppm was the hemiacetal proton peak, and 9.0 ppm was the proton signal of the free aldehyde group on the oxidized dextran. The QCOD hydrogels were quickly prepared by crosslinking QC and OD under physiological conditions through the dynamic Schiff base linkage formation (Figure 1b). The scanning electron microscopy (SEM) image showed that QCOD hydrogels possessed a 3D network consisting of polysaccharide nanofibers, indicating the encapsulating and delivering capacity of QCOD hydrogels (Figure 1c). Then, the rheology properties of QCOD hydrogels were determined by a rheometer. As shown in Figure 1d, the gelation process of QCOD hydrogels was further monitored by dynamic time-sweep rheology experiments. In the early stage, storage modulus (G′) and loss modulus (G″) increased rapidly. A rapid crosslinking and gelation process was shown when G′ exceeded G″, exhibiting solid-like elastic gel properties. The QCOD hydrogels were further subjected to frequency-sweep tests by dynamic rheology at 37 °C, and the storage modulus of the hydrogel networks was 1800 Pa (Figure 1e). The cumulative release value of salidroside reached ~$82\%$ after 72 h at pH 7.4, while the maximum release value reached ~$95\%$ after 72 h, at a relatively acidic pH value of 5.0. The acid-sensitive covalent linkages of the QCOD hydrogel networks were closely associated with decreased pH, resulting in increased release of salidroside from QCOD hydrogels under acidic conditions. In addition, QCOD@Sal hydrogels have certain scavenging abilities for free radicals, and the scavenging rate increased gradually with the increase in concentration (Figure S4). The excellent water retention of QCOD was observed due to its unique 3D network consisting of polysaccharide nanofibers. The experimental results also showed that at 144 h, the water loss rates of pure water and low dexamethasone ointment groups were ~$65\%$ and ~$57\%$, respectively, while the water loss rate of the hydrogel group was ~$28\%$, indicating that the hydrogel had better water retention. The experimental results showed that at 144 h, the water loss rates of pure water and low dexamethasone ointment groups were ~$65\%$ and ~$57\%$, respectively, while the water loss rate of the hydrogel group was ~$28\%$, indicating that the hydrogel had better water retention (Figure 1f). Next, the anti-inflammatory drug, salidroside was encapsulated into QCOD hydrogels, and the pH-responsive drug release behavior was studied at 37 °C (Figure 1f). As shown in Figure S5, QCOD@Sal has the ability to scavenge free radicals, and the antioxidant capacity was increased with the increase in concentration. The above results suggest that QCOD hydrogels can be used as a carrier for the sustained delivery of anti-inflammatory drugs. The dynamic imine bonds of QCOD hydrogels resulted in shear-thinning and self-healing capabilities. The viscosity of QCOD hydrogels decreased with the increasing shear rate, which allows the pre-formed hydrogel to encapsulate and deliver salidroside in vivo (Figure 2a). QCOD hydrogels can be pushed out of the WHU letter by a syringe. Furthermore, the strain sweep measurements were performed (Figure 2c). The strains at the intersection of G′ and G″ were ~$280\%$, indicating a critical state of colloid and solution. When the shear strains were greater than $350\%$, QCOD hydrogels exhibited a sol-gel transition due to the dynamic imine bond breaking and polymeric chain reorientation within the hydrogel network. The self-healing properties of QCOD hydrogels were studied by alternating high and low strain (between $1\%$ and $500\%$ strain) scanning modes (Figure 2d). As the amplitude of the oscillatory force increased from low to high ($1\%$ strain to the $500\%$ strain), the G′ value immediately dropped from 1800 Pa to 190 Pa, and the storage modulus was lower than G″. When the strain returned to $1\%$, the G′ and G″ values rapidly returned to their initial values. The rapid recovery of hydrogen and imine bonds within the reversible hydrogel network may cause reversible recovery behavior, indicating that QCOD hydrogels can self-heal quickly and efficiently, allowing them to be used as drug carriers. The biocompatibility of QCOD and QCOD@Sal hydrogels was then evaluated by the MTT assay and hemolysis assay. The mouse fibroblast cells L929 were used to investigate the cell viabilities of the QCOD and QCOD@Sal hydrogels (10 μL hydrogel/200 μL medium) at different culture times (on days 1, 2, and 3). As shown in Figure 3a, compared with the control group, the survival rate of the L929 cells co-cultured with QCOD and QCOD@Sal on days 1, 2, and 3 was >$85\%$, which shows excellent cytocompatibility. In addition, the activity and morphology of the L929 cells were further assessed by cytofluorimetric staining assays. Almost all L929 cells emitted green fluorescence, and most of the cells showed a full oval or shuttle shape (Figure 3b). In addition, the hemolysis values of QCOD and QCOD@Sal hydrogels on red blood cells were $1.1\%$ and $4.9\%$, respectively, indicating that QCOD and QCOD@Sal hydrogels showed excellent red blood cell compatibility (Figure 3c). The excellent biocompatibility of QCOD@Sal was related to its composition. The material selection was made of chitin, one of the most abundant amino polysaccharides in nature with excellent biocompatibility and biodegradability, while its bioactivity has been intensively exploited in the last decades. ## 3.2. NIR-II Imaging and Image-Guided Therapy of DNFB-Induced AD Mice We further explored the potential of HLA4P [35] (200 μM) for NIR-II fluorescence imaging of DNFB-induced AD mice ($$n = 6$$), with or without treatment, in vivo. In vivo NIR-II imaging was carried out 3, 5, 10, and 15 days after injecting HLA4P [35], under 808 nm excitation (3.5 mW cm−2). The body weight changes were also recorded. As shown in Figure 4b, no significant differences were observed in the body weights among the treatment group (Figure 4b). Among them, the QCOD@Sal treatment group showed the best therapeutic effect on the dermatitis of DNFB-induced AD mice. It can be seen that QCOD@Sal enabled the sustained release of salidroside and enhanced the wound closure rate on day 6, while the wound was basically healed on day 15 (Figure 4c). Thus, QCOD@Sal hydrogels not only moisturized the damaged skin, yet also provided a good anti-inflammatory effect in the presence of salidroside. In the DEX treatment group, the eschar began to show on day 15, while the damaged skin was accompanied by obvious dryness, which was inferior to the QCOD@Sal treatment group. As illustrated in Figure 4d, the AD symptoms were plainly visible against the background at 120 h after injection of HLA4P. Li [35] provided the synthetic route of the probe. The probe accumulation peaked at 120 h after injection without any treatment (Figure 4d). The fluorescence signal of the QCOD@Sal treatment group was much weaker at all timepoints compared to the DEX and QCOD treatment groups (Figure S6). During the treatment, the SCORAD scores were performed on the back skin damage of the mice on days 8, 12, and 14. Analysis of the data revealed that the QCOD@Sal treatment group was more effective than the QCOD and DEX treatment groups. The back skin dermatitis of mice improved as the treatment progressed and the QCOD@Sal treatment group had a significant difference in the dermatitis score compared to the DEX group (p* < 0.001) (Figure 4e). ## 3.3. Mechanism of QCOD@Sal for Ameliorating AD To further verify the mechanism underlying the QCOD@Sal therapeutic effect in the AD treatment, we performed H&E staining, IHC-Fr staining, TUNEL staining, whole blood indicators, ROS levels, and IL-6 and TNF-α indicators. The data indicated that the expressions of central granulocytes, monocytes, macrophages, and lymphocytes in the control group were significantly increased, while they were significantly decreased in the following order: DEX, QCOD, and QCOD@Sal treatment groups (Figure 5a). TUNEL staining showed that apoptosis and inflammation were significantly elevated in the control group. The number of apoptotic cells following treatment with DEX was also significantly higher than that in the QCOD or QCOD@Sal treatment groups, yet still significantly lower than in the control group. Furthermore, the magnitude of the reduction in apoptosis after treatment with QCOD was slightly less than after QCOD@Sal treatment, which further confirmed the efficacy of the QCOD@Sal hydrogels in treating atopic dermatitis. A QCOD@Sal therapeutic effect in AD treatment was further characterized by the ROS (DHE) staining and showed that the ROS levels were in the order of the control group > DEX group > QCOD group > QCOD@Sal, with QCOD@Sal providing the most therapeutic efficiency for AD treatment (Figure 5a). The whole blood analysis of the AD mice without treatment was performed after orbital blood sampling on day 16, and elevated leukocytes, neutrophils, and lymphocytes were observed with an inflammatory response. The results also showed that leukocytes, lymphocytes, and neutrophils in the QCOD@Sal treatment group were significantly decreased relative to the DEX and QCOD treatment groups (p* < 0.001) (Figure 5b). Considering the expression of the inflammatory factors on the wound surface, IL-6 and TNF-α were analyzed by ELISA on day 16, and the therapeutic effects of the QCOD@Sal group, QCOD group, and DEX group were evaluated. The results showed that the QCOD@Sal treatment group had the lowest IL-6 and TNF-α values, indicating less inflammation (Figure 5c). ## 4. Conclusions In this work, we designed quaternized β-chitin/oxidized dextran hydrogels QCOD@Sal containing the traditional Tibetan medicine salidroside, which is in line with the concept of green chemistry and non-toxicity. QC and OD can generate hydrogels in situ under physiological conditions through dynamic imine bonding, and QCOD hydrogels have good drug encapsulation, sustained release, and moisturizing properties compared with other cutaneous drug delivery systems, including nanoparticles, ethosomes, and microneedles. QCOD hydrogels are convenient for drug delivery and belong to smear dosage forms, which do not pass through the liver and have no first-pass effects compared with oral dosage forms. QCOD@Sal hydrogels can be obtained by using QCOD hydrogels to encapsulate salidroside and moisturized the damaged skin and accelerated wound debridement during the treatment of atopic dermatitis. The results indicate that QCOD@Sal treated the DNFB-induced mouse model of AD by blocking the IL-6 and TNF-α signaling pathways. The extent of the skin lesions in the treatment process of AD was monitored in real-time by NIR-II fluorescence imaging for the first time. 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--- title: Chemical Characterization and Antioxidant, Antibacterial, Antiacetylcholinesterase and Antiproliferation Properties of Salvia fruticosa Miller Extracts authors: - Michella Dawra - Jalloul Bouajila - Marc El Beyrouthy - Alain Abi Rizk - Patricia Taillandier - Nancy Nehme - Youssef El Rayess journal: Molecules year: 2023 pmcid: PMC10058602 doi: 10.3390/molecules28062429 license: CC BY 4.0 --- # Chemical Characterization and Antioxidant, Antibacterial, Antiacetylcholinesterase and Antiproliferation Properties of Salvia fruticosa Miller Extracts ## Abstract The Salvia fruticosa (Mill.) is the most medicinal plant used in Lebanon. The aim of this study is to investigate the phytochemical composition and the biological activities (in vitro) of its extracts. The plant was extracted by cold maceration with four solvents presenting an increasing polarity: cyclohexane (CHX), dichloromethane (DCM), ethyl acetate (EtOAc) and methanol (MeOH). The extracts were screened for their chemical composition by a HPLC-DAD detector for phenolic compounds identification and quantification and by GC-MS for volatile compounds detection. The antioxidant capacity (DPPH inhibition) was tested. Biological activities, mainly anti-Alzheimer activity (acetylcholinesterase inhibition), the antiproliferation of two human colon cancer cell lines (HCT-116 and Caco-2 cells) and antibacterial activity, were evaluated. Ten aromatic compounds were quantified by HPLC-DAD analysis. A total of 123 compounds were detected by GC-MS analysis. The MeOH extract showed a very interesting antioxidant activity with an inhibition percentage (IP) of $76.1\%$ and an IC50 of 19.4 μg/mL. The EtOAc extract exhibited the strongest inhibition against the acetylcholinesterase activity (IP = $60.6\%$) at 50 μg/mL. It also strongly inhibited the proliferation of the HCT-116 cells (IP = $87.5\%$), whereas the DCM extract gave the best result with the Caco-2 cells (IP = $72.3\%$). The best antibacterial activity was obtained with the MeOH extract against Staphylococcus aureus (MIC = 1.2 μg/mL) and with the EtOAc extract against Escherichia coli (MIC = 2.4 μg/mL). This study highlights the chemical composition and therapeutic potential of S. fruticosa. It is important to mention that the following chemical compounds were identified for the first time in plant extracts: 2,6,11,15-tetramethyl-hexadeca-2,6,8,10,14-pentaene; 4,5,6,7-tetrahydroxy-1,8,8,9-tetramethyl-8,9-dihydrophenaleno [1,2-b]furan-3-one; podocarpa-1,8,11,13-tetraen-3-one,14-isopropyl-1,13-dimethoxy; podocarpa-8,11,13-trien-3-one,12-hydroxy-13-isopropyl-,acetate; 3′,8,8′-trimethoxy-3-piperidin-1-yl-2,2′-binaphthyl-1,1′,4,4′-tetrone; and 2,3-dehydroferruginol, thus underlining the originality of this study. ## 1. Introduction In recent decades, due to the excessive need for healthy medications devoid of harmful synthetic and chemical products, there was a growing interest in finding new efficient, non-toxic and natural bioactive compounds. Aromatic and medicinal plants, including Salvia species, are known to have a potent role in the treatment of various illnesses, such as aches, epilepsy, colds, bronchitis, tuberculosis, hemorrhage and menstrual disorders [1]. Although there are around 900 species of Salvia, only a few are commercially important [2]. Particularly, the Salvia fruticosa Miller (S. fruticosa Mill.), also named S. libanotica and formerly S. triloba, belonging to the Lamiaceae family, is an endemic species of the Mediterranean Basin generally and Lebanon specifically. It is also known as the East Mediterranean sage or Lebanese sage and represents most of the imported sage in the United States rather than the S. officinalis [3]. It is considered the most widely used medicinal plant in Lebanon since ancient times [4] and grows at an altitude of 200–400 m [5]. In folk medicine, S. fruticosa aerial parts are used by herbalists and pharmacists, either internally as infusions to treat cold symptoms, mouth and throat inflammation, cough [4] and abdominal pain [6] or applied externally. The essential oils of the Salvia fruticosa were widely investigated and more than 100 volatile compounds were identified in several sage species. They mainly belonged to the classes of monoterpenes, sesquiterpenes, diterpenes and non-isoprenoid compounds, usually with thujone, camphor and 1,8-cineole as the most dominant ones [7]. Regarding non-volatiles, about 160 polyphenolic compounds were identified from sage plants: flavonoids and their glycosides, anthocyanins, and phenolic acids with characteristic caffeic acid derivatives, such as rosmarinic acid, phenolic diterpenes, such as carnosic acid, and other phenolic glycosides [7,8]. The latter play an important role in the prevention against oxidative damages [5,6,7,8,9]. It is very important to draw to the attention that, in the case of thujone, notwithstanding many beneficial effects, the tremendously neurotoxic danger of this volatile organic constituent has been checked out [10]. Conforming to the European Medicines Agency EMA/HMPC [2016], the daily exposure of 6.0 mg (for a 2-week duration) is allowed. Thereby, it is extremely important to control the thujone content in sage and sage-based products. Contrariwise, rosmarinic acid is one of the most useful flavonoids resulting in sage and derivative products, due to its value through anticancer and antioxidant treatments [11]. Moreover, several studies revealed that S. fruticosa essential oils exhibited pharmacological properties, for instance, antibacterial, antioxidant, anticholinesterase and antiproliferative activities [12]. Salvia is also known for its use as a culinary herb and an ornamental plant that has a sweet nectar and pollen for pollinators. Economically, it is easily accessible and has an affordable price in the market. In the literature, the medicinal properties of S. fruticosa are often related to volatile compounds in essentials oils. However, the non-volatile compounds can also contribute to the importance of this plant. The primary purpose of this study was to carry out comprehensive research and provide data on the phytochemistry and biological activities of S. fruticosa extracts (CHX, DCM, EtOAc and MeOH) grown in Lebanon. The antioxidant and biological activities of the S. fruticosa were identified in vitro through testing the radical scavenging effects on DPPH, then the capacity of each extract to inhibit the AChE enzyme, the proliferation of HCT-116 and Caco-2 cells, and the antibacterial activity against several bacterial strains. ## 2.1. Plant Materials and Extraction Yields The yields of the four extracts of S. fruticosa are shown in Figure 1. The highest one was obtained with the MeOH extract ($9.2\%$), followed by the CHX extract ($3.6\%$), DCM extract ($3.4\%$) and EtOAc extract ($1.1\%$). Dincer et al. reported that Salvia sp. extraction yields ranged between 17.8 and $20.3\%$ [1]. Bozan et al. showed that the methanolic extracts yields of eight Salvia species including the S. halophila Hedge, S. tomentosa Miller, S. fruticosa Miller, S. chrysophylla Stapf, S. sclarea L, S. clicica Boiss. and Kotschy, S. cryptantha Montbret and Aucher ex Bentham, and S. palaestina Bentham varied between 12.8 and $26.3\%$ [13]. The highest yield ($26.3\%$) was recorded with the S. fruticosa Miller. Variations in the yields and composition could be affected by many factors, such as the plant development stage, extraction and ecological conditions, soil nature and geographical coordinates [4]. ## 2.2. Total Phenolic Content The largest amount of phenolic compounds was obtained with the MeOH extract and was 135.1 mg GAE/g of dw as shown in Figure 2. This indicates that either the majority of the phenolic compounds of the S. fruticosa were polar or the most abundant ones were polar. The TPCs of the other extracts were 54.4, 44.4 and 23.5 mg GAE/g of dw, respectively, for the DCM, EtOAc and CHX extracts. Depending on the weather conditions through the years, the TPC detected in the aerial part, especially in the leaves of the S. fruticosa, ranged between 63.7 and 144 mg GAE/g dw [12]. Dincer et al. stated that the methanolic extracts of the S. fruticosa collected from Turkey presented a TPC between 41.5 and 44.6 mg GAE/g dw, almost 3.2 times lower than the amount obtained in the current study [2]. Moreover, they mentioned that the TPC of the MeOH extracts of S. fruticosa was more abundant than the one obtained with other Salvia species extracts. Duletić-Laušević et al. obtained a TPC of 132 mg GAE/g dw in the methanolic extract of the S. fruticosa, which is slightly lower than the one obtained in the current study [14]. Salvia with a high phenolic content has several interesting applications. It can be used in oily food because of its significant capacity to reduce undesirable fragrances, extend shelf life, delay the formation of toxic oxidation products, increase nutritional value and prevent microbial growth. It is also widely employed in the cosmetic industry [15]. ## 2.3. Identification and Quantification of Phenolic Compounds by HPLC-DAD Ten compounds, of which nine were phenolic compounds and one a methoxy-phenolic compound, were detected and quantified by HPLC-DAD as reported in Figure 3 and Table 1. The identification of the compounds by HPLC-DAD was based on the comparison of the HPLC retention times and the DAD spectra to those found in the literature. It is worth mentioning that the detected compounds were found for the first time in S. fruticosa extracts. The amount of compound 10 was the highest in the CHX extract and decreased gradually in the DCM and EtOAc extracts underlining its non-polar character. Polydatin (compound 4), which was found in the EtOAc and MeOH extracts, presented the highest amount in the MeOH extract, which underlines its polarity. These results are in agreement with those obtained with the TPC determination. The MeOH extract presented the highest TPC mainly because of the presence of polydatin, which was the most abundant phenolic compound detected by HPLC-DAD. The majority of the compounds ($70\%$ of the detected molecules) were extracted by the non-polar solvents (CHX and DCM). The CHX extract contained the following compounds: 5′,3′-dihydroxyflavone [5] ($y = 0.0126$x−0.0317; 0.09 mg/g); 3-benzyloxy-4,5-dihydroxy-benzoic acid methyl ester [7] ($y = 0.0961$x+0.5481; 0.1 mg/g); pinosylvin monomethyl ether [9] ($y = 0.1265$x−0.5347; 0.9 mg/g); and 3,6,3′-trimethoxyflavone [10] ($y = 0.1017$x+0.1091; 0.9 mg/g). The rutin [3] ($y = 0.1029$x+0.6179; 0.3 mg/g), 5,7-dihydroxy-4-phenylcoumarine [6] ($y = 0.1605$x−0.0115; 1.6 mg/g) and 4′,5-dihydroxy-7-methoxyflavone [8] ($y = 0.1159$x+2.1574; 0.35 mg/g) were extracted by the DCM solvent. The EtOAc extract contained the 3-amino-4-hydroxybenzoic acid [1] at 0.1 mg/g ($y = 0.5959$x+0.4365), the 3,4-dihydroxy-5-methoxybenzoic acid [2] at 7.7 mg/g ($y = 0.1682$x−0.047) and the polydatin [4] at 2.7 mg/g ($y = 0.0445$x−0.0083). Compound [1] was also found in the MeOH extract but at a higher amount (0.3 mg/g). Polydatin [4] was the most abundant compound and was present at 74.3 mg/g in the MeOH extract. Compound 6 was present in the MeOH extract (0.1 mg/g) at a lower amount than in the DCM extract (1.6 mg/g). Compounds 1, 4, 6 and 10 were detected in several extracts of Salvia fruticosa but at different concentrations depending on their polarity and solubility. ## 2.4. GC-MS Analysis of the S. fruticosa Extracts before and after Derivatization (Trimethylsilylation) A total of 58 compounds were identified by GC-MS before derivatization (trimethylsilylation) and 65 additional ones after derivatization (Table 2). A total of $68.1\%$ of the detected compounds were present in the CHX extract underlining their non-polar nature. This is the first study that analyzes the volatile compounds of the S. fruticosa organic extracts. It is important to mention that this research has allowed us to reveal, for the first time, the presence of the following molecules in plants extracts: 2,6,11,15-tetramethyl-hexadeca-2,6,8,10,14-pentaene [30]; 4,5,6,7-tetrahydroxy-1,8,8,9-tetramethyl-8,9-dihydrophenaleno[1,2-b]furan-3-one [38]; podocarpa-1,8,11,13-tetraen-3-one, 14-isopropyl-1,13-dimethoxy- [40]; podocarpa-8,11,13-trien-3-one, 12-hydroxy-13-isopropyl-, acetate [41]; 3′,8,8′-trimethoxy-3-piperidin-1-yl-2,2′-binaphthyl-1,1′,4,4′-tetrone [45]; and 2,3-dehydroferruginol (33′). Some molecules were found for the first time in S. fruticosa and were the following: 4-terpineol [4]; humalane-1,6-dien-3-ol [36]; (+/−)-demethylsalvicanol [46]; 12-O-methylcarnosol [49]; β-eudesmol (5′); cuminyl alcohol (7′); androstenediol (35′); kolavenol (36′); 6,7-dihyroferruginol (38′); 2-palmitoglycerol (40′); 2-monostearin (48′); monoolein (49′); 2-monolinolenin (51′); cytosine (54′); campesterol (55′); germanicol [58]; α-amyrin (59′); and micromeric acid (65′). Some volatile compounds detected in the extracts of this study were previously found in the EO of many Salvia species. For instance, camphor [12], β-pinene [4] and caryophyllene oxide [25] were detected in the EO of S. lavandulaefolia [16]. Camphene [2], p-cymene [5], α-thujone [9], β-thujone [11], endo-borneol [14], terpinen-4-ol [16], β-caryophyllene [19] and viridiflorol [26] were found in the EO of the African S. officinalis [17]. Some alkanes, such as heptacosane [51] and octacosane [52], were detected in the EO of the Salvia hierosolymitana Boiss growing wild in Lebanon [18]. Furthermore, uvaol [58], betulin [61], oleanolic acid (63′) and ursolic acid (64′) were previously found in the $70\%$ acetone-water extract of the S. officinalis and the rosmarinic acid (60′) was found in the S. officinalis, S. limbata, S. virgata, S. hypoleuca, S. macrosiphon and S. choloroleuca [19]. As shown in Table 2, some compounds existed in two or three extracts, such as the 2-monopalmitin [45] and carnosol (45′). This behavior is attributed to the extraction process intended to soften and break the plant’s cell walls in order to release the soluble phytochemicals. The amount of each compound will then depend on its affinity to each organic solvent, mainly on its polarity and solubility. ## 2.5. DPPH Assay for the Determination of the Antioxidant Activity The antiradical activity of the aerial part of the S. fruticosa organic extracts was assessed and compared with the standard ascorbic acid (IC50 = 4 μg/mL). The concentration of the extracts was adjusted to 50 μg/mL. As listed in Table 3, it can be stated that the strongest inhibition of DPPH was obtained with the MeOH extract ($76.1\%$) with an IC50 value of 19.4 μg/mL. It was followed by the EtOAc extract, which showed an inhibition percentage of $20.9\%$, then the DCM extract with $6.5\%$ and finally no inhibition was registered with the CHX extract. The strongest DPPH inhibition was obtained with the MeOH extract. Several authors tested the capacity of the MeOH extracts of many Libyan, Turkish and Iranian Salvia species to quench the DPPH free radical and found that the IC50 values were as follows: S. fruticosa, IC50 = 36.37 μg/mL; S. multicaulis, IC50 = 386.9 μg/mL, S. viridis, IC50 = 570 μg/mL [20]; and S. macrosiphon, IC50 = 2743.05 μg/mL [21]. Interestingly, the concentrations were, respectively, 9, 97, 142 and 686 times higher than those obtained with the MeOH extract of the current study (IC50 = 19.4 μg/mL). El Boukhary et al. assessed the ability of S. fruticosa MeOH extracts prepared from the roots and the aerial parts to inhibit DPPH. The inhibition percentages obtained were 32.16 and $41.5\%$, respectively, and were 2.37 and 1.83 times less effective than the MeOH extract of the current study ($76.1\%$) [3]. Moreover, the capacity of the MeOH extract to inhibit the DPPH was 3.3 times less effective than that of the ascorbic acid (19.4 vs. 4.0 μg/mL). Nevertheless, the antioxidant activity of the methanolic extract was significant and resulted from the presence of several molecules in the extract. The fractioning and separation of these molecules may give more interesting IC50 values than those obtained with the ascorbic acid. The high correlation coefficient (R2 = 0.92) between the phenolic content of the extracts and their corresponding antioxidant activity confirmed that the phenolic compounds were the main components responsible for the antioxidant activity of the S. fruticosa extracts. The MeOH extract, which exhibited the highest antioxidant activity, contained, per gram of extract, 0.3 mg of 3-amino-4-hydroxybenzoic acid; 74.3 mg of polydatin; and 0.1 mg of 5,7-dihydroxy-4-phenylcoumarine (Table 1). It also contained salvianolic acid A (22′); 2,3-dehydroferruginol (33′); and rosmarinic acid (60′) (Table 2). These molecules may have worked synergistically in order to give a good inhibition. In the EtOAc extract, the presence of phenol, 2,2′-methylenebis 6-(1,1-dimethylethyl)-4-methyl-[43]; 4-hydroxybenzoic acid (9′); and 2-palmitoyl glycerol (40′) that have a labile proton may have contributed to the quenching of the DPPH free radical (Table 2). The CHX and DCM extracts showed a poor antioxidant activity. However, some of their chemical compounds may have inhibited the DPPH free radical, such as the β-sitosterol (IC50 = 140 μg/mL) [22], caryophillene oxide (IC50 = 84.0 μg/mL [23]), carnosol (IC50 = 0.59 μM [24]) and carnosic acid (IC50 = 60 μM) [24]. The lupeol [56] was previously shown to exhibit a good antioxidant behavior. In fact, it quenched the DPPH free radical by $50.0\%$ at 70 μg/mL [25]. ## 2.6.1. Antiacetylcholinesterase Activity (Anti-AChE) The analysis was carried out with 50 μg/mL of each S. fruticosa extract. The results were compared to that of the standard GaHbr. As shown in Table 3, a similar inhibition percentage was registered for the CHX ($59.5\%$), DCM ($60.5\%$) and EtOAc ($60.6\%$) extracts. Although the MeOH extract presented the lowest inhibition with $52.46\%$, it was not significantly different from the previous ones (p ˃ 0.05). This behavior against the AChE enzyme could be attributed to many molecules that are present in the samples. Ayaz et al. proved that the β-sitosterol exhibited a considerable AChE inhibition with an IC50 value of 55 μg/mL. This compound was present in the non-polar CHX and DCM extracts (55-Table 2) [22]. Savelev et al. isolated the (−)-β-pinene (4-Table 2), the caryophyllene oxide (26-Table 2) and the (−)-camphor (12-Table 2) from S. lavandulaefolia EO [16]. These compounds were also found in the S. fruticosa CHX and/or DCM extracts. The (−)-β-pinene inhibited the AChE activity with an IC50 value of 0.2 mg/mL, while the camphor reduced its activity by $39.0\%$ at 0.5 mg/mL. Recently, Karakaya et al. proved that the caryophyllene oxide isolated from Salvia verticillata subsp. Amasiaca EO presented a good anti-AChE potency since it reduced the enzyme activity by $41.4\%$ at 200 μg/mL. It can be concluded from the previous data that the anti-AChE activity of the extracts resulted from complex interactions, both synergistic and antagonistic, between their terpene constituents [23]. ## 2.6.2. MTT Assay for the Measurement of the Antiproliferation Activity The antiproliferation activity of the S. fruticosa extracts prepared at 50 μg/mL was tested on two lines of cancer cells: Caco-2 and HCT-116. The tamoxifen was used as a positive control. The highest growth inhibition of the Caco-2 cells was registered with the DCM extract ($72.3\%$), followed by the EtOAc extract ($62.1\%$), whereas the highest inhibition of the HCT-116 cells was recorded with the EtOAc extract ($87.5\%$), followed by the DCM extract ($70.7\%$) (Table 3). The CHX extract was not active at all, while the MeOH extract only reduced the growth of the HCT-116 cells by $7.2\%$ (p ≤ 0.05). Therefore, the S. fruticosa extracts were more active against the proliferation of the HCT-116 cells than the Caco-2 ones. The American National Cancer Institute (NCI) considered that the extracts with an IC50 < 30 μg/mL had a promising cytotoxic activity (Suffness, 1990), which is the case of the DCM and EtOAc extracts of the current study (Table 3) [25]. Duletić-Laušević et al. tested the antiproliferation activity of the Libyan S. fruticosa- EtOH extract against the HCT-116 cells and found that it was able to reduce their growth with an IC50 of 375.96 μg/mL [14]. The obtained value was 25.7 times higher than the one recorded with the EtOAc extract (14.6 μg/mL) of the current study. The latter gave the best antiproliferation activity and showed a promising anticancer application. Polydatin was found to inhibit the growth of Caco-2 cells and gave an IC50 of 74.9 μg/mL [26]. This compound was present in the EtOAc extract that presented an IC50 of 31.1 μg/mL when tested against the same cancer cell line. Therefore, polydatin may have contributed to the antiproliferation activity of the EtOAc extract along with other compounds leading to a better result than when tested alone. ## 2.6.3. Antimicrobial Activity Assay The four S. fruticosa extracts were tested individually for their capacity to inhibit the growth of seven foodborne pathogenic bacterial strains including four Gram-negative and three Gram-positive bacteria. The minimum inhibitory concentrations (MICs) obtained are displayed in Table 4. The DCM extract significantly inhibited the growth of S. Kentucky (MIC = 19.5 μg/mL) and moderately that of L. monocytogenes ATCC 19115 (MIC = 78.1 μg/mL). The MeOH extract showed an important antibacterial activity against S. aureus ATCC 25923 and E. coli ATCC 8739 with very low MIC values of 1.2 and 2.4 μg/mL, respectively. The antibacterial activity of the EtOAc extract against E. coli was the same as for the MeOH one (same MIC value of 2.4 μg/mL). The EtOAc extract also showed a moderate activity against L. monocytogenes ATCC 19115 (MIC = 39 μg/mL). Duletić-Laušević et al. tested the antimicrobial activity of a Libyan S. fruticosa extract (EtOH and water) against E. coli, S. Enteritidis, S. aureus and L. monocytogenes and found MIC values of 1500, 1500, 1000 and 1000 μg/mL, respectively [14]. When comparing these values to the best MIC values obtained in the current study against the same bacterial species, we find that the MIC values of this study were, respectively, 625, 19.21, 833 and 208 times lower than those found in the literature, underlining the important antibacterial activity of our extracts. However, we should take into consideration that the extraction solvents used, the geographical origin and the bacterial strains were not the same. Based on the study conducted by Kosová et al., the EtOAc extract’s behavior could be explained by the presence of the 4-hydroxybenzoic acid (9′-Table 2) considered a preservative [27]. This acid was shown to inhibit the growth of S. aureus and E. coli at 20 mmol/l. The extracts of the current study exhibited a bacteriostatic activity against some of the bacterial strains tested, while some others, mainly Gram + ones, were not affected. This can be explained by the presence of resistance mechanisms in these strains [28]. ## 2.7. Principal Component Analysis (PCA) The PCA analysis was used in this study in order to establish the relation between the different biological activities and the chemical composition of the extracts. As shown in Table 5, the axes of inertia have been hidden from this analysis. The percentage of total variation was recorded at $98.6\%$ and proven by the structuring accessions in Figure 4. The axes were retained because they expressed $57.1\%$ (PC1) and $41.5\%$ (PC2). Simultaneously, the loadings in the PCA loading plots expressed how good the correlation was between the major components and the original variables studied. There was a very good correlation between the antioxidant activity and the TPC. PC1 was highly correlated only with the TPC with a loading of 0.93 (Table 6). The second axis was well correlated with HCT-116, Caco-2 and AChE with loadings of 0.73, 0.63 and 0.59, respectively (Table 6). When applying the principal component analysis, it seemed that there was a discriminate structure. The oval forms grouped the different extracts into three classes: C1 (S. fruticosa—DCM and S. fruticosa—EtOAc), C2 (S. fruticosa—CHX) and C3 (S. fruticosa—MeOH). Since the two plots (biplot) were gathered together, it can be noticed that the high TPC and antioxidant activity were related to the S. fruticosa—MeOH extract. In addition, the S. fruticosa—DCM, S. fruticosa—EtOAc and S. fruticosa—CHX (poor in TPC) were located symmetrically in the negative side of the PC1 axis, which suggested that the high antiproliferation and antiacetylcholinesterase activities of these extracts were not only related to the phenolic compounds. ## 3.1. Chemicals and Plant Materials In October 2018, the fresh leaves of the S. fruticosa were collected from Naher Ibrahim, Lebanon. The botanical identification was made by Dr. Marc El Beyrouthy, chairman and general manager of the company Nature by Marc Beyrouthy. The samples were deposited in the Herbarium of Botany, Medicinal Plants and Malherbology, School of Engineering, Holy Spirit University of Kaslik, Lebanon under the registry number MNIIIb177a. The analytical standards used for the identification and quantification of the main phenolic compounds found in the plant extracts were as follows: 3-amino-4-hydroxybenzoic acid; 3,4-dihydroxy-5-methoxybenzoic acid; rutin; polydatin; 5′,3′-dihydroxyflavone; 5,7-dihydroxy-4-phenylcoumarine; 3-benzyloxy-4,5-dihydroxy-benzoic acid methyl ester; 4′,5-dihydroxy-7-methoxyflavone; pinosylvin monomethyl ether; and 3, 6,3′-trimethoxyflavone, all of which were obtained from Sigma-Aldrich (St Louis, MO, USA). ## 3.2. Preparation of the Extracts The collected aerial parts of S. fruticosa were dried in shade at an ambient temperature and transformed into powder with a particle size of 0.8 mm [29]. A cold maceration with four solvents presenting an increasing polarity (CHX, DCM, EtOAc and MeOH) was performed to yield the four organic extracts. A total of 100 g of powder was successively extracted with 2 L of each solvent during 2 h with an agitation of 300 rpm. The filtrates were recovered after filtration through whatman filter papers (Fisher, Asiane, France). The extracts were obtained by evaporating the solvent under vacuum at 35 °C. The extraction yield was calculated as follows: Yield %=mM×100, “m” being the dry weight obtained in grams and “M” being the weight of the plant material in grams. ## 3.3. Total Phenolic Content Determination The total phenolic content (TPC) of each extract was evaluated spectrophotometrically at 765 nm using the Folin–Ciocalteu (FC) method as described by Dawra et al. [ 29]. Gallic acid (0–115 μg/mL) was used for the calibration curve. The results were expressed as mg of gallic acid equivalents (GAE)/g dw. ## 3.4. HPLC-DAD Fingerprint The HPLC analysis was performed in an ultimate 3000 pump—Dionex and Thermo separation product detector DAD model (Thermo Fisher Scientific, Waltham, MA, USA). Separation was achieved on an RPC18 reversed-phase column (Phenomenex, Le Pecq, France), 25 cm × 4.6 mm and particle size of 5 μm, thermostated at 25 °C as described by Dawra et al., with modifications [28]. The elution was performed at a flow rate of 1.2 mL/min, using a mobile phase consisting of MilliQ water (pH 2.6) (solvent A) and acidified water/MeCN (20:80 v/v) (solvent B). The samples were eluted by the following linear gradient: from $12\%$ B to $30\%$ B for 35 min, from $30\%$ B to $50\%$ for 5 min, from $50\%$ B to $88\%$ B for 5 min and finally from $88\%$ B to $12\%$ B for 15 min. The extracts were prepared at a concentration of 20 mg/mL using the mixture acidified water/MeCN (80:20 v/v) and then filtered through a Millex-HA 0.45 µm syringe filter (Sigma Aldrich). Then, 20 μL of each sample were injected and the detection was registered at 280 nm. The phenolic compounds were identified by comparison to the retention time of some known standards and then quantified using their corresponding calibration curves. ## 3.5. Gas Chromatography GC-MS Analysis The identification of the volatile compounds of the organic extracts, before and after derivatization, was conducted using the protocol described by Dawra et al., with some modifications [29]. The analyses were conducted using an Agilent gas chromatograph 6890 coupled to a 5975 Mass Detector. The 7683 B auto sampler injected 1 μL of each extract. A fused silica capillary column DB-5 MS (30 m × 0.25 mm internal diameter, film thickness 0.25 μm) (Supelco, Sigma-Aldrich, Darmastadt, Germany) was employed. The temperature ramp was settled between 35 and 300 °C. The column temperature was initially set to 35 °C before being gradually increased to 85 °C at 15 °C/min, held for 20 min at 85 °C, raised to 300 °C at 10 °C/min and finally held for 5 min at 300 °C. Helium (purity $99.99\%$) was used as a carrier gas at a flow rate of 0.8 mL/min. Mass spectra were registered at 70 eV with an ion source temperature held at 310 °C and a transfer line heated at 320 °C. The record of each acquisition was made in full-scan mode (50–400 amu). The main target was to find the maximum resemblance in terms of spectra between the compounds found in the extracts and those suggested by the NIST08 database (National Institute of Standards and Technology, https://www.nist.gov/ (accessed on 15 April 2021)), using AMDIS software, and the retention time was used to facilitate many tasks. The derivatization method consisted of dissolving 5 mg of each extract in 1 mL of its own solvent except for the MeOH extract. The latter was dissolved in MeCN. After that, 150 μL of BSTFA and 1.5 μL of TMSC were added to the solution. The mixture was agitated for 30 s in order to increase the solubility. The reaction mixture was maintained at 40 °C for 30 min. A total of 10 μL of each derivatized solution were injected into the GC-MS and analyzed as previously reported. ## 3.6. Free Radical Scavenging Activity: DPPH Test The antioxidant scavenging activity of the extracts was examined using the DPPH method as described by Dawra et al. [ 29]. A total of 20 μL of the diluted plant extract (500 μg/mL) was added to 180 μL of a 0.2 mM methanolic DPPH solution in a 96-well microplate (Micro Well, Thermo Fisher Scientific, Bordeaux, France). After an incubation period of 30 min at 25 °C, the absorbance was measured at 515 nm. The antioxidant activity was expressed as the inhibition percentage of DPPH using the following equation: % INB=100×Ablank−AsampleAblank. The extract concentration providing a $50\%$ reduction in the DPPH initial absorbance (IC50) was calculated using the linear relation between the extract concentrations and the corresponding % INB of DPPH. All measurements were performed in quadruplicate. ## 3.7.1. Antiacetylcholinesterase Activity The antiacetylcholinesterase (AChE) activity was tested using the Ellman’s procedure as previously reported by Dawra et al. [ 29]. In a 96-well microplate, 50 μL of 0.1 mM sodium phosphate buffer (pH = 7.5), 125 μL of DTNB (5,5′-dithiobis-2-nitrobenzoic acid), 25 μL of the diluted plant extract (500 μg/mL) and 25 μL of the enzyme solution (493.2 U) were mixed. The microplate was incubated at 25 °C for 15 min. Then, 25 μL of ACTHI was added and the final blend was incubated at 25 °C for 25 min. Finally, the absorbance was measured at 421 nm. The Ablank was measured without the extract. The inhibition percentage of the enzyme activity was calculated as follows: % INB=100×Ablank−AsampleAblank. ## 3.7.2. Antiproliferation Activity The antiproliferation activity of the plant extracts was assessed on two different types of human colon cancer cells (HCT-116 and Caco-2). The test was based on the MTT reduction by the mitochondrial dehydrogenases of intact cells to a purple formazan product. MTT is a yellow water-soluble tetrazolium salt. The cell lines were purchased from Sigma-Aldrich (Manassas, VA, USA). A volume of 100 μL of a suitable culture medium containing 3 × 104 cells was added to each well of a 96-well microplate. Then, 100 μL of the same culture medium containing the plant extract was added. The final concentration of the extract in each well was 50 μg/mL. The culture media used were, respectively, the RPMI 1640 (Sigma Aldrich, St. Louis, MO, USA) for the HCT-116 cells and the Dulbecco’s modified Eagle’s medium GlutaMAX (DMEM, Sigma Aldrich, USA) for the Caco-2 cells. The microplate was incubated at 37 °C for 48 h. The supernatant was then removed, and 50 μL of the MTT solution was added followed by an incubation of 40 min. After removing the MTT reagent, 80 μL of DMSO was added to solubilize the formazan crystals. Finally, the absorbance was measured at 605 nm. The tamoxifen was used as a positive control whereas the negative control was composed of the cell suspension without the plant extracts (blank). The inhibition percentage of the cells’ proliferation was calculated as follows: % INB=100×Ablank−AsampleAblank. ## 3.7.3. Antimicrobial Activity Assay The Gram-negative strains used in this assay were Escherichia coli ATCC 8739 and the Kentucky, Infantis and Enteritidis serotypes of Salmonella enterica provided by the Lebanese Agriculture Research Institute (LARI), Lebanon. The Salmonella serotypes were isolated from chicken samples collected from slaughterhouses. The Gram-positive strains were Staphylococcus aureus ATCC 25923, Listeria monocytogenes ATCC 19115 and Listeria monocytogenes isolated from “fish-filet” at the LARI. A bacterial suspension of each bacterial strain was prepared in a Mueller–Hinton Broth (MHB) at a concentration of 2 × 108 CFU/mL (0.5 McFarland standard) [30]. The minimum inhibitory concentration (MIC) values of the Salvia fruticosa extracts were determined by serial dilution in a 96-well microplate. Each well first contained 100 μL of MHB. The dried extracts were dissolved in pure DMSO to a concentration of 5 mg/mL. Then, the extract solutions were half-diluted with MHB to obtain a concentration of 2.5 mg/mL. Afterwards, 100 μL of the latter were placed in the first well and a serial dilution was conducted in order to obtain the following concentrations in each row: 1250, 625, 312.5, 156.2, 78.1, 39, 19.5, 9.7, 4.8, 2.4 and 1.2 μg/mL. Next, 100 μL of each bacterial strain tested were added to the extract solutions. Therefore, the initial bacterial concentration was adjusted to 108 CFU/mL in each well. The negative control was composed of 100 μL of DMSO and 100 μL of the bacterial strain tested while the positive control contained 100 μL of MHB and 100 μL of the bacterial strain. The absorbance was measured at time 0 min and after an overnight incubation at 37 °C (24 h) using a Multiskan Sky Microplate Spectrophotometer (Thermo Fisher Scientific, Cleveland, OH, USA). ## 3.8. Statistical Analysis The data represent the mean of four replicates ± standard deviation (SD). The results were subjected to a multiway analysis of variance, and the mean comparisons were performed by a Tukey’s multiple range test using SPSS version 20.0 (Statistical Package for the Social Sciences, Inc., Chicago, IL, USA). The differences between means were considered significant at p-value < 0.05. The linear correlation coefficient (R2) was calculated to establish the relationship between the TPC and the antioxidant or any other biological activity. For exploratory data analysis, the results were processed by one of the multivariate analysis techniques, the principal components analysis (PCA). The PCA was conducted using XLSTAT (version 2020.1, Addinsoft, Pearson edition, Waltman, MA, USA) for a better discrimination between the studied parameters. ## 4. Conclusions This novel research shed light on the phytochemistry and biological activities of the Salvia fruticosa Miller extracts native to Lebanon. The HPLC-DAD analysis permitted the identification and quantification of ten aromatic compounds; nine of which were recognized as phenolic compounds. The GC-MS analysis revealed the presence of 123 volatile compounds. S. fruticosa extracts showed interesting biological activities. The MeOH extract showed a high antioxidant activity. The four extracts presented a good antiacetylcholinesterase activity. The DCM and EtOAc extracts revealed a significant antiproliferation activity against the HCT-116 and Caco-2 cancer cells. 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--- title: Evaluation of the Approach towards Vaccination against COVID-19 among the Polish Population—In Relation to Sociodemographic Factors and Physical and Mental Health authors: - Justyna Gołębiowska - Anna Zimny-Zając - Mateusz Dróżdż - Sebastian Makuch - Krzysztof Dudek - Grzegorz Mazur - Siddarth Agrawal journal: Vaccines year: 2023 pmcid: PMC10058603 doi: 10.3390/vaccines11030700 license: CC BY 4.0 --- # Evaluation of the Approach towards Vaccination against COVID-19 among the Polish Population—In Relation to Sociodemographic Factors and Physical and Mental Health ## Abstract Due to the rapid development of COVID-19 vaccines, the world has faced a huge challenge with their general acceptance, including Poland. For this reason, we attempted to determine the sociodemographic factors influencing the decision of positive or negative attitudes toward COVID-19 vaccination. The analysis included 200,000 Polish participants—80,831 women ($40.4\%$) and 119,169 men ($59.6\%$). The results revealed that the most common reasons for vaccine refusal and hesitancy were the fear of post-vaccination complications and their safety (11,$\frac{913}{31}$,338, $38.0\%$; $\frac{9966}{31}$,338, $31.8\%$). Negative attitudes were observed more often among male respondents with primary or secondary education (OR = 2.01, CI$95\%$ [1.86–2.17] and OR = 1.52, CI$95\%$ [1.41–1.63], respectively). On the other hand, older age ≥ 65 (OR = 3.69; $95\%$CI [3.44–3.96]), higher education level (OR = 2.14; $95\%$CI [2.07–2.22]), living in big cities with a range of 200,000–499,999 inhabitants and more than 500,000 inhabitants (OR = 1.57, CI$95\%$ [1.50–1.64] and OR = 1.90, CI$95\%$ [1.83–1.98], respectively), good physical conditions (OR = 2.05; CI$95\%$ [1.82–2.31]), and at last normal mental health conditions (OR = 1.67, CI$95\%$ [1.51–1.85]) were significantly associated with COVID-19 vaccine acceptance. Our study indicates which population group should be further supplied with data and information by health education, the government, and healthcare professionals to alleviate the negative attitude toward COVID-19 vaccines. ## 1. Introduction The Coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus has led to a dramatic public health problem since its first outbreak at the beginning of 2020. Confirmed cases of this disease reached approximately 700 million by February 2023, with a death toll exceeding more than 6 million worldwide. In Poland, the total number of confirmed cases reached more than 6 million, with over 120,000 deaths [1]. Undoubtedly, this alarming increase in the number of COVID-19-associated morbidities and mortalities had an unprecedented negative impact on economic activity, education, travel, international trade and transport, global production, distribution, social activities, and healthcare [2,3]. Health services and researchers worldwide were working under severe pressure to provide the public best available care. Other comorbidities (e.g., cancer [4], chronic kidney disease [5], heart disease [6], and diabetes mellitus [7]) and sociodemographic factors (e.g., older age [8], stress [9], and obesity [10]) have the greatest impact on the risk of severe COVID-19 complications. To date, despite the unprecedented efforts of scientists, there is no successful treatment strategy for COVID-19 infection. Therefore, the urgent COVID-19 vaccine development and vaccination campaigns are the only breakthrough in the fight against the SARS-CoV-2 virus and the primary exit strategy from this global crisis. In November 2020, approximately one year after the COVID-19 outbreak, at least 55 vaccines were undergoing clinical trials on humans, and at least three were approved for public use. As estimated by Anderson et al., at least 60–$72\%$ of the population has to be vaccinated to herd immunity, which could significantly lead to SARS-CoV-2 eradication [11]. However, the approach to outrun the virus mutation, immunize the majority of the population, and stop its spread has led to unexpected results. Due to the accelerated vaccine development, there has been a loss of confidence in their safety and effectiveness. According to the World Health Organization (WHO), the hesitancy to take a COVID-19 vaccination is among the top ten global threats [12]. It is, however, worth keeping in mind that the willingness to vaccinate varies in different countries and can be shaped by various factors (e.g., history of diseases, sociodemographic factors, and society). For instance, Lazarus et al., surveyed 13,426 randomly selected individuals from 19 countries to determine the willingness to accept a COVID-19 vaccination. The highest acceptance rate (more than $80\%$) was observed in Asian nations (including China, the Republic of Korea, and Singapore) and middle-income countries, such as Brazil, India, and South Africa. In contrast, the lowest willingness to take the COVID-19 vaccination was observed in Poland and Russia (around $55\%$) [13]. Interestingly, according to the Public Opinion Research Center in Poland, there was an increase in the intention to be vaccinated against COVID-19 over time. Compared to November 2020, the percentage of these individuals increased by nearly $67\%$ [14]. Taking into account only European countries, Portugal is at the top in the ranking of people taking the COVID-19 vaccination ($94.9\%$%—in 2023) [15]. Therefore, constant monitoring of the statistical data in this regard, especially in countries with relatively low acceptance rates in the global perspective, is highly beneficial to implement proper strategies for COVID-19 vaccination programs and achieve the public healthcare success [15]. Poland is one of the countries offering vaccination to its populations in a phased manner. The vaccination program in Poland started on 27 December 2020, when the first vaccine was delivered the Polish healthcare facility [16]. Initially, vaccines were directed to senior citizens at the age of 80 or more [16], as this age group is at the highest risk of COVID-19 complications. Subsequently, other Polish citizens categorized by age had access to free-of-charge vaccination. To date, several studies from Poland brought up the problem of concerns of COVID-19 vaccination. For instance, Sowa et al. determined that the fear of side effects is the reason for refusion of COVID-19 vaccination for $82\%$ of a study group [17]. Similarly, Stasiuk et al. concluded that the main arguments against vaccinations were as follows, among others: [1] no proven effectivity, [2] low quality of the research on vaccines, and [3] the intention of the pharmaceutical industry and medical profession [18]. Furthermore, Walkowiak et al. showed that a low level of education is a negative predictor of COVID-19 vaccine acceptance [19]. Other factors influencing the vaccination acceptability seem to be religion, national narcissism, and conspiracy theories [17]. According to Raciborski et al., Polish females had higher odds of refusing COVID-19 vaccination compared with males, suggesting that age is another factor playing role in this regard [20]. Understanding the concerns and factors triggering a decision not to be COVID-19 vaccinated can be useful to overcome vaccine hesitancy. For this reason, we utilized the National Test for Poles’ Health (NTZP)—an online study performed yearly since 2020, collecting data from a large group of Polish Internet users. The decision to vaccinate may result from culture, beliefs, or sociodemographic characteristics. Based on data collected in the NTZP, the current study aims to determine sociodemographic factors contributing to the attitude to vaccination against COVID-19. We believe our study is one of the stepping stones to target the groups of Polish citizens with the highest risk of vaccine hesitancy. Including other reports from Poland, our study is crucial to be considered while developing strategies to strengthen the COVID-19 vaccination programs and educational interventions. Furthermore, it may be used by healthcare agencies in different countries willing to re-align their vaccination programs and target groups with the most negative attitudes to COVID-19 vaccination. ## 2.1. Study Design The National Test for Poles’ Health (NTPH) is a valuable information source on Polish Internet users’ health. Thus far, it has been conducted in three waves (2020, 2021, and 2022) [21]. The questionnaire was filled out in Polish by over 970,000 respondents in all three waves [22]. It was distributed online via a social networking site. The survey was fully anonymous and voluntary. For the purpose of this particular study, responses from one wave [2022] were analyzed—a representative sample of 200,000 adults. The scheme of the online survey is shown in Table S1; it was translated from Polish to English for reader’s understanding. The evaluated sample of the study group was obtained by stratified sampling per the voivodeship demographic structure of Poland. The duration of the survey ranged from 15 to 20 min. All participants provided informed consent for collecting the data and were informed about the goal of the survey. Participation in the study provided no compensation. ## 2.2. Explanatory Variables The online survey used in the study included questions regarding the respondent’s sociodemographic data and questions necessary to evaluate the attitude toward COVID-19 vaccination (Table S1). Sociodemographic data included: [1] gender (male or female), [2] age (categorized as 18–24, 25–34, 35–44, 45–54, 55–65, 65, and more), [3] education (primary, secondary, or higher), [4] place of residence (village; town less than 19,000 inhabitants; town between 20,000 to 49,000 inhabitants; town between 50,000 to 99,000 inhabitants; town between 100,000 to 199,000 inhabitants; town between 200,000 to 499,000 inhabitants; and town more than 500,000 inhabitants), and [5] region of Poland (south, northwest, southwest, north, central, east, and Masovian voivodeship). Furthermore, to determine BMI levels (kg/m2), respondents were asked to provide body weight (kg) and body height (cm), allowing us to categorize their weight into [1] underweight, [2] normal, [3] overweight, and [4] obese. Additionally, respondents were asked to rate subjective physical and mental health on a five-point Likert scale, choosing from “excellent” to “very bad” (Table 1). ## 2.3. Measures The survey included three questions (Table S1): [1] Are you vaccinated against influenza?; [ 2] Will you get vaccinated against COVID-19?; [ 3] Why do you not want to get vaccinated against COVID-19?; The evaluation of the attitude toward influenza vaccination in the study group was measured by counting points obtained while answering the abovementioned questions (Table S1, question 1 (Q1)). The fewer points received, the more positive attitude towards vaccination, and vice versa; the more points obtained, the more negative attitude towards vaccination. The measurement of patients who were vaccinated against seasonal influenza was made based on the honest and reliable participants’ responses, which we believe are consistent with the actual truth. In the case of COVID-19 vaccination evaluation (Table S1, question 2 (O2)), the positive attitude was measured by answering “1—I have already been vaccinated” or “2—I intend to take a COVID-19 vaccination”. The negative attitude to COVID-19 vaccination was measured by answering “3—I don’t know yet” or “4—No, never” (Table 2). Additionally, among respondents with a negative attitude toward COVID-19 vaccination, we asked about the reason for that statement (Table S1, question 3 (Q3)). Respondents could select the argumentation from: “I have concerns about the safety of the COVID-19 vaccine”, “I am afraid of post-vaccination complications”, “I can’t get vaccinated due to medical reasons”, and “I am against vaccination in general”. The dichotomization of the answers to the question about the attitude to COVID-19 vaccination allowed us to estimate the odds ratios and highlight significant predictors of their statements. ## 2.4. Statistics Nominal and ordinal variables are presented in the contingency tables as numbers (n) and percentages (%). Spearman’s rank correlation coefficient (rho) and Pearson’s chi-square test were used to assess the relation between two ordinal variables. Odds ratios and their $95\%$ confidence intervals were also calculated for the 2 × 2 tables. Significant predictors of negative or positive attitudes towards COVID-19 vaccination were those whose odds ratios were outside the range of 1.5 times the reference values. Statistical software package STATISTICA v. 13.3 (TIBCO Software Inc., Palo Alto, CA, USA) was used for the analysis. ## 3.1. Study Group The analysis included 200,000 participants—80,831 women ($40.4\%$) and 119,169 men ($59.6\%$). Of the total respondents, $26.4\%$ were older respondents aged more than 65 years old. The majority of the participants had higher education ($56.2\%$). The place of residence was quite evenly distributed; a similar percentage of the study group lived either in a village or in a large city with more than 500,000 inhabitants ($22.1\%$ and $17.4\%$, respectively). Only $1.7\%$ of respondents were underweight, and more than half of the study population had excessive body weight: $38.8\%$ were overweight, and $25.2\%$ suffered from obesity. Most respondents defined their physical and mental health status as “good” ($40.2\%$ and $41.8\%$). Further characteristics of the subjects included in this study can be found in Table 1. At the time of the study [2022], most respondents declared COVID-19 vaccination ($83.2\%$); $6.7\%$ were uncertain about taking the vaccine, and $8.9\%$ maintained a negative attitude (Table 2). To clarify if the negative attitude refers to COVID-19 vaccination specifically or if is it a general opinion, respondents were also asked about their willingness to take an influenza vaccination. The vast majority of the study group was never vaccinated against influenza ($72.2\%$; Q1, answer 7 in Table 2, Figure 1). However, $11.3\%$ of respondents declared taking an influenza vaccination regularly ($11.3\%$; Q1, answer 1 in Table 2, Figure 1). Due to the observed positive relation between the attitude to COVID-19 vaccination and influenza vaccination (rho = 0.219, $p \leq 0.001$), we were able to determine how these approaches were changing under the influence of each other. Among those vaccinated against COVID-19, the number of respondents regularly taking an influenza vaccination increased from $11.3\%$ (Table 2) to $13.3\%$ (Figure 2). Furthermore, among those denying the COVID-19 vaccination, only $0.7\%$ of them declared taking an influenza vaccination, including in 2022. ## 3.2. Predictors of a Positive Attitude toward COVID-19 Vaccination According to our study, the positive attitude toward COVID-19 vaccination increases with age. Respondents over 65 years old were nearly four times more likely to declare positive approaches to COVID-19 vaccination than respondents aged 18–24 (OR = 3.69 CI = $95\%$ [3.44–3.96], Table 3). A slightly lower but statistically significant relation was observed among respondents aged 55–64 compared to those aged 18–24 (OR = 2.17, CI = $95\%$ [2.03–2.33], Table 3). Furthermore, respondents with higher education compared to those with primary education were approximately two times more likely to declare positive approaches to COVID-19 vaccination (OR = 2.14, CI = $95\%$ [2.07–2.22], Table 3). In addition, people living in large cities (200,000–499,999 inhabitants and more than 500 000 inhabitants) were more likely to take the vaccine (OR = 1.57, CI$95\%$ [1.50–1.64] and OR = 1.90, CI$95\%$ [1.83–1.98], respectively, Table 3). Among respondents in good physical condition, there was a twofold increased likelihood to declare a positive attitude toward COVID-19 vaccination compared to those in very bad physical condition (OR = 2.05, CI = $95\%$ [1.82–2.31], Table 3). Additionally, we found a statistically significant relation among respondents in other than good physical condition. Still, it never achieved the twofold change compared to those declaring very bad physical condition (Table 3). The same situation was observed among respondents in very good, good, and normal mental conditions—they were more likely to declare a positive attitude toward COVID-19 vaccination than those in very bad mental condition, but this likelihood was less than twofold (for instance, very good mental condition—OR = 1.62, CI$95\%$ [1.46–17.79], good mental condition—OR = 1.89, CI$95\%$ [1.71 = 2.09], and normal mental condition—OR = 1.67, CI$95\%$ [1.51–1.85], Table 3). We did not observe a significant relation between gender and region in Poland (Table 3). The odds ratios and the $95\%$ confidence intervals for statistically significant predictors of a positive attitude toward COVID-19 vaccination are shown in Figure 3. Thus, the positive attitude toward COVID-19 vaccination was observed predominantly among older respondents with higher education, living in large cities (at least 200,000 inhabitants), and declaring good physical and mental condition (Table 3). ## 3.3. Predictors of Negative Attitude toward COVID-19 Vaccination The rationale for refusing vaccination against COVID-19 (Q3, Table 2) was provided by $15\%$ of the study population (31,$\frac{338}{200}$,000 respondents). The most frequently cited reasons were fear of post-vaccination complications and concern about their safety ($38.0\%$ and $31.8\%$, respectively). Furthermore, 4372 respondents could not be COVID-19 vaccinated due to medical reasons ($16.2\%$), and 5087 respondents declared to be against vaccinations in general ($14.0\%$, Table 2). The likelihood of being against COVID-19 vaccination was more than twofold higher among men than women ($p \leq 0.001$, OR = 2.20, CI = $95\%$ [2.07–2.34], Table 4). We may assume that education status plays a crucial role in the decision-making process. Respondents with primary or secondary education were more likely to declare anti-vaccine attitudes ($p \leq 0.001$, OR = 2.01, CI = $95\%$ [1.86–2.17] for primary education, and $p \leq 0.001$, OR = 1.52, CI = $95\%$ [1.41–1.63] for secondary education, Table 4). Furthermore, respondents declaring very good physical health status were approximately 1.5 times more likely to report anti-vaccination approaches compared to those with very bad status ($p \leq 0.001$, OR = 1.51, CI$95\%$ [1.15–1.99], Table 4). There was no statistically significant relation between negative vaccination attitude, place of residence, region in Poland, and BMI. Overall, reluctance toward COVID-19 vaccination was observed mainly among men with primary and secondary education declaring very good physical condition (Table 4). ## 4. Discussion Our study is one of the largest population-based studies ($$n = 200$$,000 participants) addressing attitudes toward vaccination in the context of the COVID-19 pandemic in Poland. Furthermore, to the best of our knowledge, it is the most up-to-date study on attitudes toward COVID-19 vaccines in Poland. Collected data show that $83.2\%$ of the respondents were COVID-19 vaccinated. However, the percentage applies only to the adult population of Poland. Official updates from the Polish Ministry of Health show that $60.6\%$ of the total population ($67.4\%$, 18+ year) was vaccinated with at least one dose against COVID-19. Compared to other European countries, the highest percentages of at least one dose uptake of COVID-19 vaccines were observed in Portugal ($94.9\%$), Spain ($87.2\%$), and Iceland ($83.3\%$). The cumulative vaccine uptake in the total population in European countries was $75.6\%$ (data as of 26 January 2023) [15]. The acceptance rate varies over time and may be caused by constantly developing new vaccines, improving the quality and effectiveness of current vaccines, the emergence of different mutations within the SARS-CoV-2 virus, and the spreading of incorrect information from unauthorized parties [23]. Furthermore, due to the fact that SARS-CoV-2 has many similarities to influenza regarding its pathogenicity and respiratory complications [24], respondents were also asked about their willingness to take an influenza vaccination. In addition, this comparison was chosen due to influenza vaccine hesitancy, which is strongly manifested in the general population [25]. Several independent studies reported these concerns increased during the COVID-19 pandemic [26,27]. Most respondents ($72.2\%$) did not take an influenza vaccination. The low influenza vaccination coverage in Poland ($61\%$) was also observed by Zaprutko T et al. [ 28]. The main concerns are the efficacy, disbeliefs, and misconceptions about the safety and vaccine hesitancy over the years [28]. Since the beginning of the COVID-19 pandemic, influenza epidemiology and surveillance have sharply decreased. The lowest historical level of influenza circulation worldwide was observed in weeks 9 and 10 of 2020 [29]. In Poland, compared to 2019 (before the COVID-19 pandemic), in 2020, $34\%$ fewer influenza-infected patients were registered, while in 2021, this number increased to $37\%$ [30]. This tendency is likely due to social mitigation measures implemented to alleviate the transmission of SARS-CoV-2 infection, which also contribute to the weakening of the transmission of other viral infections, especially those transmitted by similar routes. Another factor contributing to the low influenza circulation is higher influenza vaccination coverage, seen mainly among the age groups at greatest risk of COVID-19 infection. For instance, in Spain, the influenza vaccine uptake increased from an average of $55\%$ in the previous five vaccination campaigns to $64\%$ during the $\frac{2020}{2021}$ campaign [31]. In Poland in 2020, only $2.5\%$ more patients were taking the influenza vaccination compared to in 2019. However, in 2021 this number increased to approximately $26\%$ [30]. This result is in line with our data showing the increase in influenza vaccination among those vaccinated against COVID-19 (from $11.3\%$ to $13.3\%$). Therefore, better coverage in immunization against influenza may positively influence the attitude to COVID-19 vaccination and vice versa. Several studies have shown that the best predictor of the uptake of COVID-19 vaccine is the administration of an influenza vaccine in the previous season [32,33,34]. Furthermore, Conlon et al. determined that patients who took an influenza vaccination during the COVID-19 outbreak (from August 2019 to mid-July 2020) were less likely to be tested as COVID-19 positive. They also found the association between influenza vaccination and decreased COVID-19 mortality and reduced need for intensive care treatment [34]. These and other [24] findings are hence factors leading to an increase in the willingness to take the flu vaccine, which may be potential consequences of alleviating the risk of being COVID-19 infected. In our study, $15.7\%$ of all respondents declared anti-vaccine attitudes toward COVID-19. The most frequently cited reasons were fear of post-vaccination complications and their safety ($38.0\%$ and $31.8\%$, respectively, Table 2). This outcome meets the results of other studies concerning the same problem [33,35,36]. In general, a great majority of vaccines have side effects. However, COVID-19 vaccines were approved for use recently; hence, side effects may be different than those found in clinical trials. Consequently, the concerns observed in our study are understandable. It is, therefore, crucial to provide the public with reliable information about the side effects of COVID-19 vaccines [37]. Furthermore, as we know which factors contribute to COVID-19 vaccine refusal, we can propose strategies that should be implemented to increase vaccine acceptance. For instance, Rashid et al. suggested that a few combined interventions, including education, training sessions, and easy vaccine accessibility, may increase influenza vaccine uptake [38]. We believe these strategies may also be useful regarding the COVID-19 vaccine. It is essential for health professionals and medical practitioners to inform patients about the benefits of protecting themselves and their relatives with COVID-19 vaccination. Studies conducted all over the world highlighted the most critical determinants of intention to take a COVID-19 vaccination, such as age, occupational status, gender, marital status, education level, income, knowledge about COVID-19, past COVID-19 infection, the pre-existence of chronic diseases, as well as physical and mental health conditions [39,40,41,42,43]. In our study, we considered some of the abovementioned sociodemographic factors affecting the attitude toward COVID-19 vaccination. Firstly, we observed positive attitudes toward COVID-19 vaccination among older adults. Respondents over 65 years old were almost four times more likely to accept COVID-19 vaccination than younger adults (OR = 3.69, CI = $95\%$ [3.44–3.96], Table 3). This result is consistent with several other studies reported in the UK, Turkey, Saudi Arabia, Ethiopia, China, and South Africa [40,43,44,45,46,47]. Kilic et al. found a positive relationship between the increase in age and the attitude toward vaccination [44]. Furthermore, in line with our data, the study found a significant relation between education level and positive attitudes toward COVID-19 vaccination [44]. Answers collected in our online questionnaire show that higher education level increased the positive attitudes toward COVID-19 vaccination (OR = 2.14, CI$95\%$ [2.07–2.22], Table 3); however, negative attitudes were more frequently observed among respondents with primary and secondary education levels ($p \leq 0.001$, OR = 2.01, CI = $95\%$ [1.86–2.17], and <0.001, OR = 1.52, CI = $95\%$ [1.41–1.63], respectively, Table 4). In another independent study in Ethiopia, Abebe et al. found the same interplay: age above 46 years or secondary and higher education were significantly associated with COVID-19 vaccine acceptance [48]. In Poland, Raciborski et al. also showed that the lack of higher education is significantly associated with lower willingness to obtain COVID-19 vaccination [20]. Since older people are at the highest risk of severe COVID-19-related complications, they are more afraid to be infected, which in turn increases their willingness to seek vaccination. In addition, highly educated people are more aware of the benefits of prevention in health and have higher receptivity to new health-related information [48]. These results, taken together, show that improving educational status may be one of the general strategies to improve attitudes to vaccinations. Furthermore, advertising and educational campaigns on the safety and efficacy of COVID-19 vaccines should be taken into consideration in order to reach the groups without higher education. In 2021, Zintel et al. conducted a study comparing 60 reports aiming to determine the role of gender in stating the attitude toward COVID-19 vaccination. A total of $58\%$ of men declared more willingness to take the COVID-19 vaccination compared to their female counterparts [49]. This finding is consistent with several other studies [33,44,50,51], but not with our study. We found that male respondents were more likely to have an anti-vaccine approach compared to females ($p \leq 0.001$, OR = 2.20, CI = $95\%$ [2.07–2.34], Table 4). However, this study group was not asked about other factors that might affect their final decision, including net income or occupation. There were also no questions about addictions and smoking history. Furthermore, it sounds reasonable that more male respondents are against COVID-19 vaccination due to their “laid-back” approaches to COVID-19 vaccination, which in turn, decreases their awareness about the health crisis caused by COVID-19. This phenomenon was observed more often among male respondents declaring very good physical condition (OR = 1.51 CI$95\%$ [1.15–1.99]). Nevertheless, additional research is needed on gender regarding COVID-19 vaccine hesitancy. This study has several limitations. First, this study was based on the results of an online survey. Therefore, we are forced to believe in the sincerity of the participants filling in the questionnaire. It is also very difficult to determine the percentage of uncompleted questionnaires at each stage of the research. Secondly, the study was conducted in a period of almost two years. Public opinion may change because of media campaigns and vaccination promotions by public authorities and medical professionals. As the survey was anonymous, it was not possible to inform participants of the results of the study or provide psychological support if necessary. The study group is not representative of Polish society despite the fact that the questionnaire was distributed to various general groups. In order to reduce this risk, the online questionnaire was spread around social media for different groups of interest. The lack of knowledge regarding potential vaccine complications and their safety should constitute essential targets for educational programs in the Polish population. The aim is to alleviate the COVID-19 pandemic crisis and enhance vaccination rates [52]. The healthcare system plays a primary role in this task: the global challenge is to educate, inform, and intervene to increase positive attitudes toward COVID-19 vaccination. The results of this study may motivate public benefit organizations and local authorities in Poland to reach specific groups, provide reliable knowledge about the importance of COVID-19 vaccinations, and reduce COVID-19 vaccine hesitancy. ## References 1. Hopkins J.. COVID-19 Map—Johns Hopkins Coronavirus Resource Center 2. WHO Director-General’s Opening Remarks at the Media Briefing on COVID-19—11 March 2020 3. 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--- title: Obstructive Sleep Apnea as a Predictor of a Higher Risk of Significant Coronary Artery Disease Assessed Non-Invasively Using the Calcium Score authors: - Piotr Macek - Monika Michałek-Zrąbkowska - Barbara Dziadkowiec-Macek - Małgorzata Poręba - Helena Martynowicz - Grzegorz Mazur - Paweł Gać - Rafał Poręba journal: Life year: 2023 pmcid: PMC10058620 doi: 10.3390/life13030671 license: CC BY 4.0 --- # Obstructive Sleep Apnea as a Predictor of a Higher Risk of Significant Coronary Artery Disease Assessed Non-Invasively Using the Calcium Score ## Abstract The aim of this study was to assess the coronary artery calcium score in patients with obstructive sleep apnea (OSA). The study group (group A) consisted of 62 patients with diagnosed obstructive sleep apnea (mean age: 59.12 ± 9.09 years, mean AHI index in polysomnography: 20.44 ± 13.22/h), and 62 people without diagnosed obstructive sleep apnea (mean age 59.50 ± 10.74 years) constituted the control group (group B). The risk of significant coronary artery disease was assessed in all patients, based on the measurement of the coronary artery calcium score (CACS) using computed tomography. The following cut-off points were used to assess the risk of significant coronary artery disease: CACS = 0—no risk, CACS 1–10—minimal risk, CACS 11–100—low risk, CACS 101–400—moderate risk, and CACS > 400—high risk. Group A was characterized by statistically significantly higher CACS than group B (550.25 ± 817.76 vs. 92.59 ± 164.56, $p \leq 0.05$). No risk of significant coronary artery disease was statistically significantly less frequent in group A than in group B ($0.0\%$ vs. $51.6\%$, $p \leq 0.05$). A high risk of significant coronary artery disease was statistically significantly more frequent in group A than in group B ($40.3\%$ vs. $4.8\%$, $p \leq 0.05$). In group A, patients with severe OSA and patients with moderate OSA had statistically significantly higher CACS than patients with mild OSA (910.04 ± 746.31, 833.35 ± 1129.87, 201.66 ± 192.04, $p \leq 0.05$). A statistically significant positive correlation was found between the AHI and CACS ($r = 0.34$, $p \leq 0.05$). The regression analysis showed that OSA, male gender, older age, type 2 diabetes, peripheral arterial disease, and smoking were independent risk factors for higher CACS values. AHI ≥ 14.9 was shown to be a predictor of a high risk of significant coronary artery disease with a sensitivity and specificity of $62.2\%$ and $80.0\%$, respectively. In summary, obstructive sleep apnea should be considered an independent predictive factor of a high risk of significant coronary artery disease (based on the coronary artery calcium score). ## 1. Introduction Coronary artery disease (CAD) is defined as the presence of atherosclerosis in coronary arteries [1]. The formation of atherosclerotic plaque is a complex process that depends on many factors affecting the intimal layer of the coronary artery wall. Endothelial dysfunction, oxidized serum lipids, inflammation, and thrombosis, with secondary effects of angiogenesis and calcification, are involved in the pathogenesis of plaque formation and progression [2]. Coronary heart disease includes the diagnosis of stable angina, acute coronary syndrome, and silent myocardial ischemia [3]. The main symptom of this disorder is chest pain or discomfort, which may radiate to the shoulder and arm. Typically, symptoms are exacerbated by physical exertion or emotional stress and decrease during rest [4]. CAD is the most common reason for a single cause of mortality and loss of disability-adjusted life years globally. In 2015, the CAD caused 8.9 million deaths and 164 million DALYs [5]. The main risk factors of CAD are type 2 diabetes mellitus [6], cigarette smoking [7], sedentary lifestyle [8], high cholesterol level [9], arterial hypertension [10], and obstructive sleep apnea [11]. Coronarography is the primary method used to diagnose significant coronary artery stenosis [12]. Its disadvantages are its cost and risk of vessel damage, and the physiological effect of the stenosis on myocardial function cannot be clearly assessed. To assess the physiological significance of coronary artery stenosis, the FFR (fractional flow reserve) is measured during coronary angiography [13]. During the measurement, it is necessary to insert a coronary pressure guidewire and administer a vasodilator. There is a low risk of damage to the coronary artery during the measurement [14]. However, the relevance of computed tomography angiography (CCTA), which may be used to assess significant coronary artery diseases, is growing [15]. CCTA is a non-invasive, fast, reliable, and reproducible method that assesses the coronary artery calcium (CAC) score based on the presence of calcium in the coronary artery [16]. CAC is a mathematically estimated, quantitative, unit-free parameter characterizing the amount of calcium within atherosclerotic plaques in coronary walls [17]. The following cut-off points were used to assess the risk of significant coronary artery disease: CACS = 0—no risk, CACS 1–10—minimal risk, CACS 11–100—low risk, CACS 101–400—moderate risk, and CACS > 400—high risk. According to recent guidelines, CCTA is increasingly recommended for screening in asymptomatic individuals to identify those at high risk of developing coronary artery disease and cardiac events, as well as for assessing coronary artery obstruction in symptomatic individuals [18]. Obstructive sleep apnea (OSA) is one of the most common respiratory disorders that is characterized by recurrent complete (apneas) and partial (hypopneas) upper airway collapse events [19]. The event can cause intermittent hypoxemia, autonomic fluctuation, and sleep fragmentation [20]. Snoring, apnea, and sleepiness are the main symptoms of OSA, although fatigue, breathlessness and choking, erectile dysfunction, concentration problems, and even insomnia have been reported in some patients [21]. Notably, 40–$80\%$ of patients with hypertension, heart failure, atrial fibrillation, and ischemic heart disease suffer from OSA [11]. Sympathetic activation, low-grade inflammation, oxidative stress, and endoplasmic reticulum stress are induced by intermittent hypoxia and play a role in cardiometabolic dysfunction [20]. Approximately $34\%$ and $17\%$ of middle-aged men and women suffer from OSA [22]; generally, approximately one billion people meet the criteria for OSA [23]. This study aimed to evaluate the coronary artery calcium score in patients with obstructive sleep apnea, specifically assessing the relationship between CACS and diagnosed OSA and between OSA severity and CACS. ## 2. Materials and Methods A total of 124 patients were included in this study. The inclusion criteria included age > 18 years and coronary artery computed tomography indications and willingness to participate. Patients with previously diagnosed myocardial ischemic disease, chronic renal failure, history of stroke, and hyper- and hypothyroidism, and patients with insufficient coronary CT, severe mental disorders that prevent polysomnography, drug intake that can affect the breathing and/or neuromuscular activity, active malignancy, and active inflammation were excluded from the study. All participants provided informed consent to participate in the study, and the study was approved by the Ethics Committee of Wroclaw Medical University (ID KB $\frac{369}{2020}$) and conducted following the Declaration of Helsinki. The clinical examination methodology included a medical history, measurement of total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, fasting glucose, and coronary computed tomography angiography. Full-night polysomnography was performed in patients with a high clinical probability of OSA. Blood pressure values were measured using the Korothov method. Hypertension and assessment of its degree were performed based on the European Society of Cardiology guidelines. Standard methods determined blood cholesterols, triglycerides, and glucose concentration according to the manufacturer’s instructions for the used reagent kits. The clinical characteristics of the studied group of patients are presented in Table 1. Diagnosis of OSA was made based on the American Academy of Sleep Medicine (AASM) standards. Patients with a clinical probability of OSA were admitted to the Department of Internal Medicine, Occupational Diseases, Hypertension, and Clinical Oncology, where they underwent one-night polysomnography. Afterward, a certified polysomnographist assessed automatic 30 s epochs of polysomnograms, and the epochs were classified based on the standard criteria for sleep using the AASM 2013 Task Force. Respiratory events were documented as follows: no airflow (>$90\%$) for ≥10 s was scored as apnea, while a ≥$30\%$ reduction in respiratory amplitude for ≥10 s with a ≥$3\%$ drop in blood oxygen saturation or arousal was scored as hypopnea. The total number of apneas and hypopneas per hour, defined as the AHI (apnea–hypopnea index) was used to assess the severity of OSA. Taking into account the value of the AHI, mild (5 ≤ AHI < 15), moderate (15 ≤ AHI < 30), and severe OSA (AHI ≥ 30) was diagnosed [24]. A 128-slice SOMATOM Definition Dual-Source CT scanner (Siemens Healthineers, Erlangen, Germany) was used to perform coronary computed tomography angiography. The study protocol included the following phases: topogram, a phase without an intravenous contrast agent to estimate the coronary artery calcium index (CACS), bolus tracking, nitroglycerin administration, and a phase with an intravenous contrast agent to assess the heart and coronary arteries properly. Iodine-based non-ionic contrast agent iomeprol (Iomeron 400, Bracco UK Ltd., Wycombe, UK) was administered intravenously using an automatic syringe through the ulnar fossa veins. The CACS was calculated using the syngo. CT CaScoring application (Siemens Healthineers, Erlangen, Germany). The software automatically classified any lesion ≥ 1 mm2 and density ≥ 130 Hounsfield units (HUs) as calcification. Each lesion classified as calcification was then classified as a lesion in the corresponding coronary arteries, namely the left main (LM), left anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA). Based on Agatston’s algorithm, the application calculated the CACS for each coronary artery as well as the total CACS. Two experienced radiologists verified the calculated values. The risk of significant coronary artery disease was determined based on the CACS value. The following criteria were used: CACS = 0, practically no risk of significant CAD; CACS 1–10, minimal risk of significant CAD; CACS 11–100, mild risk of significant CAD; CACS 101–400, moderate risk of significant CAD; and CACS ≥ 400, high risk of significant CAD. The result of each patient undergoing a CT scan of the coronary arteries was prepared using the Coronary Artery Calcium Data and Reporting System (CAC-DRS). This system indicates the result of the total calcium score, the calcium score of individual coronary arteries, and the number of vessels involved in the atherosclerotic process. Based on the result, the system provides suggestions for further management for the primary and secondary prevention of cardiovascular incidents [25]. Statistical analysis was performed using Dell Statistica 13 software (Dell Inc., Tulsa, OK, USA). Mean, median, interquartile range, and standard deviation were calculated for quantitative variables. The normal distribution of variables was verified using Lilliefors and Shapiro–Wilk tests. The quantitative independent variables with a normal distribution were analyzed using the t-test for independent variables. Variables with a non-normal distribution were analyzed using the Mann–Whitney U test for the quantitative independent variables. A chi-square test with the highest reliability was used for the analysis of independent quantitative variables. Correlation and regression analysis were conducted to determine the relationship between the study variables. Due to the lack of normal distribution of the analyzed variables, non-parametric Spearman correlation coefficients were determined. Backward stepwise multiple regression analysis was performed. In addition, accuracy was tested by proposing cut-off points for the tests estimated from receiver operating characteristic (ROC) curves. The level of statistical significance was set at $p \leq 0.05.$ ## 3. Results The patients included in this study were divided into a group of individuals with OSA (group A) and a group without diagnosed OSA (group B). The mean age was 59.12 ± 9.09 and 59.50 ± 10.74, respectively. The mean AHI index in the subgroup with OSA was 20.44 ± 13.22/h. The clinical characteristics are shown in Table 1. Group A had a significantly higher CACS than group B (550.25 ± 817.76 vs. 92.59 ± 164.56, $p \leq 0.05$). The calcium score of individual coronary arteries (LM, LAD, LCX, and RCA) was significantly higher in the group of patients with OSA than in those without diagnosed OSA. Considering the cardiovascular risk estimated based on the CACS, there were statistically significant differences between groups A and B in the categories of no risk of significant coronary artery disease ($0.0\%$ vs. $51.6\%$) and a high risk of significant coronary artery disease ($40.3\%$ vs. $4.8\%$). Patients without OSA were significantly more likely to have no atherosclerotic lesions in the coronary arteries than those with OSA. All details can be found in Table 2. In the next step, we checked whether there were statistically significant differences in the OSA group, considering disease severity as a differentiating factor. In group A, patients with severe OSA and moderate OSA had a significantly higher CACS than patients with mild OSA (910.04 ± 746.31, 833.35 ± 1129.87, 201.66 ± 192.04, $p \leq 0.05$). All the details are shown in Table 3. A statistically significant positive correlation was found between the AHI and CACS ($r = 0.34$, $p \leq 0.05$). Furthermore, a statistically significant correlation was observed between the CACS and age, BMI, and triglyceride levels. All details are presented in Table 4 and Figure 1. To verify the independence of the obtained relationships between the basic body parameters (age, gender, and BMI), blood pressure (systolic and diastolic blood pressure), the basic biochemical parameters (total cholesterol concentration, triglycerides concentration, and glucose concentration), history of concomitant cardiovascular diseases (arterial hypertension, type 2 diabetes, hypercholesterolemia, and peripheral artery diseases), smoking, obstructive sleep apnea, and the CACS, backward stepwise multiple regression analysis was performed, obtaining the model presented in Table 5. The regression analysis showed that OSA, male gender, older age, type 2 diabetes, peripheral arterial disease, and smoking were independent risk factors for higher CACS values. ROC analysis identified the optimal AHI values that were predictive factors for a specific risk of significant CAD. Based on the ROC curve analysis, an AHI ≥ 14.9 was detected as a predictor of at least moderate risk of significant coronary artery disease with a sensitivity and specificity of $63.2\%$ and $62.8\%$, respectively. AHI ≥ 14.9 predicted a high risk of significant coronary artery disease with a sensitivity and specificity of $62.2\%$ and $80.0\%$, respectively. All details are presented in Table 6 and Figure 2 and Figure 3. ## 4. Discussion Patients who underwent coronary artery tomography were eligible for the study. Patients with a high probability of OSA underwent polysomnography. The results of this study showed that patients with OSA had significantly higher CACS than patients without OSA, in terms of both their global and individual coronary artery scores. Based on the CACS, the risk of significant CAD was calculated. Statistically significant differences between groups A and B were shown in patients with practically no risk and high risk of CAD. In the next step of the analysis, patients with diagnosed OSA were compared among themselves, considering the severity of the disease. In our study, group A patients with severe OSA and moderate OSA had statistically significantly higher CACS than patients with mild OSA. Moreover, a statistically significant positive correlation was found between the AHI and CACS in our group of patients. The regression analysis showed that OSA, male gender, older age, type 2 diabetes, peripheral arterial disease, and smoking were independent risk factors for higher CACS values. AHI ≥ 14.9 predicted a high risk of significant coronary artery disease. There are few studies in the available literature on the association of OSA with the CACS. Sea et al., conducted a study involving 461 patients who underwent polysomnography and coronary artery tomography. Their analysis, after excluding the confounding factors, showed that lower saturation was independently associated with the CACS. There was no association of other parameters measured during polysomnography with the CACS [26]. In addition, in a subsequent study, the authors decided to assess the progression of subclinical CAD using the CACS. Patients underwent polysomnography and computed tomography of the coronary arteries. A follow-up CT scan was performed at any time. Total sleep time of SaO2 < $90\%$, the percentage of time of SaO2 < $90\%$, and the degree of mean oxygen desaturation were significantly correlated with CACS progression, even after excluding the confounding factors. The above study indicates that a lack of OSA treatment is associated with CAD progression [27]. Medeiros et al., evaluated the hypothesis of an association between OSA and the presence of atherosclerotic coronary lesions. They analyzed women aged 45–65 years without known cardiovascular disease. In contrast to our study, cardiovascular risk was not differentiated by the CACS value; CACS > 100 Agatston scores were used as the cut-off point. Based on the regression analysis, moderate or severe OSA was indicated as an independent risk factor for the presence of atherosclerotic lesions in the coronary arteries, which is consistent with the results of our study [28]. In contrast, in another study, Arik et al., showed that the AHI was weakly correlated with the CACS. In univariate analysis, age, AHI, basal oxygen desaturation, and oxygen desaturation index were associated with the CACS. However, in regression analysis, only the AHI and age were independent predictors of atherosclerotic lesions in the coronary arteries, which partly coincides with the results of our study, in which the regression analysis revealed that OSA, sex (male), type 2 diabetes mellitus, age, and smoking were independent predictors of significant CAD [29]. Bikov et al., investigated the association between OSA and CAD, showing that segment involvement and segment stenosis scores were higher in patients with OSA than in the control group. Furthermore, these indices significantly correlated with the severity of OSA. However, no significant correlation was shown between the CACS and OSA [30]. In a meta-analysis, Hao et al., showed an association between OSA and the presence of atherosclerotic lesions in patients without symptoms of heart disease. Furthermore, in a pairwise comparison, they indicated that the CACS might depend on the severity of OSA, which corresponds to our results [31]. CACS is a good method for detecting calcified atherosclerotic plaques and determining the risk of significant CAD. However, non-calcified plaques are identified in approximately $10\%$ of patients with CACS = 0 [32]. A study is available in which the authors investigated the association between coronary non-calcified plaques and the severity of stenosis in patients with OSA. They showed that non-calcified plaques were significantly more common in patients with OSA than in patients without OSA. Patients with OSA also had more severe stenosis and a greater number of involved vessels than those without OSA. [ 33] Similar observations have also been reported in other studies [34,35,36,37]. Criqui et al., showed that higher coronary artery calcium density was associated with a lower cardiovascular disorder risk, affecting plaque stabilization [17]. Obstructive sleep apnea is a common sleep-breathing disorder affecting an increasing number of patients [38]. OSA is associated with a higher incidence of hypertension [39], coronary artery disease [5], stroke and cardiac arrhythmias [40], and type 2 diabetes mellitus [41]. The pathogenesis of the disease includes intermittent hypoxia, oxidative stress, and endothelial dysfunction, which are involved in the progression of the atherosclerotic process [20]. Coronary artery calcium is a highly specific feature of atherosclerosis in the coronary arteries, and the CACS is one of the best-studied and available tests in cardiovascular risk assessment. The development of CAC is understood as an active pathogenic process that can be stopped by controlling cardiovascular risk factors [42]. However, a different prevalence of coronary artery calcium was shown between Caucasians and the other three ethnic groups. In addition, it was revealed that the scores of all four ethnic groups with similar strength coronary artery calcium can be used to assess the probability of significant CAD [43]. The assessment of coronary artery calcium allows for the assessment of the likelihood of significant CAD and the implementation of primary prevention. CACS = 0 is the best predictive marker of practically no risk of significant CAD. In contrast, patients with CACS > 0, who are more likely to have significant CAD than having practically no risk, will benefit from pharmacotherapy [25]. However, CACS = 0 cannot be used alone to exclude significant CAD in patients with symptoms of CAD. In a study involving 2088 patients with symptoms of coronary artery disease, Kim et al., found CACS = 0 in 1114 patients, 48 of whom were diagnosed with significant CAD in the next step [44]. In another study, Aslan et al., revealed that age >50 years, male sex, and diabetes were independently associated with non-calcified coronary plaques, and in these patient groups, coronary computed tomography angiography is more recommended [45]. In our study, based on the ROC curve analysis, a cut-off point of AHI ≥ 14.9 was found to be a possible predictor of significant CAD. Therefore, a global assessment of the coronary arteries based on computed tomography angiography should be considered to exclude coronary artery disease even in asymptomatic patients with OSA. Obstructive sleep apnea is associated with CAD. It is important to select patients at risk based on the presence of the risk factors of OSA to perform an appropriate diagnosis and, if OSA is confirmed, to implement treatment as soon as possible. In patients with higher AHI values, it is advisable to diagnose CAD by evaluating the CACS, but, as shown in the study cited above, there is a risk that even with CACS = 0, CAD cannot be ruled out unequivocally. Therefore, contrast-enhanced CT angiography should be considered in this case to detect non-calcified atherosclerotic plaques. The limitations of our study include the relatively small size of the groups and their heterogeneity. It should be noted, however, that the studied groups with and without OSA did not differ in the incidence of cardiovascular risk factors and the incidence of coexisting cardiovascular diseases. In addition, the regression analysis was used in our statistical analysis, which made it possible to assess the impact of the potential modifying factors on the assessed relationship between OSA vs. CACS. This approach was used to demonstrate the independence of this relationship from other co-occurring factors. The main methodology limitation of our study is the lack of polysomnography in patients at low risk of OSA. Unfortunately, even a low risk does not exclude OSA. Another major problem is the non-simultaneous performance of polysomnography and coronary computed tomography. Only the AHI was included in the analysis performed. As a next step, the relationship between hypoxemia, sleep fragmentation, arousal, and CAD severity would have to be investigated. A review of the literature showed that the above parameters have a particular association with oxidative stress, inflammation, and endothelial dysfunction, which may be related to atherosclerosis. Other parameters available in polysomnography were not included, which requires further research. In addition, the relationship between the use of appropriate treatment and the severity of atherosclerotic lesions, as assessed with the CACS, should be investigated in the next step. In our study, we investigated the association of OSA with the CACS, so we did not check the association of OSA with non-calcified atherosclerotic plaques, which also needs to be explored in the future. Other quantitative parameters of cardiac morphology and function, which can be assessed in coronary computed tomography angiography images, should also be verified in terms of their dependence on the occurrence and severity of OSA. ## References 1. 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--- title: Monoterpenoid Epoxidiol Ameliorates the Pathological Phenotypes of the Rotenone-Induced Parkinson’s Disease Model by Alleviating Mitochondrial Dysfunction authors: - Yulia Aleksandrova - Kirill Chaprov - Alexandra Podturkina - Oleg Ardashov - Ekaterina Yandulova - Konstantin Volcho - Nariman Salakhutdinov - Margarita Neganova journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10058627 doi: 10.3390/ijms24065842 license: CC BY 4.0 --- # Monoterpenoid Epoxidiol Ameliorates the Pathological Phenotypes of the Rotenone-Induced Parkinson’s Disease Model by Alleviating Mitochondrial Dysfunction ## Abstract Parkinson’s disease is the second most common neurodegenerative disease. Unfortunately, there is still no definitive disease-modifying therapy. In our work, the antiparkinsonian potential of trans-epoxide (1S,2S,3R,4S,6R)-1-methyl-4-(prop-1-en-2-yl)-7-oxabicyclo [4.1.0]heptan-2,3-diol (E-diol) was analyzed in a rotenone-induced neurotoxicity model using in vitro, in vivo and ex vivo approaches. It was conducted as part of the study of the mitoprotective properties of the compound. E-diol has been shown to have cytoprotective properties in the SH-SY5Y cell line exposed to rotenone, which is associated with its ability to prevent the loss of mitochondrial membrane potential and restore the oxygen consumption rate after inhibition of the complex I function. Under the conditions of rotenone modeling of Parkinson’s disease in vivo, treatment with E-diol led to the leveling of both motor and non-motor disorders. The post-mortem analysis of brain samples from these animals demonstrated the ability of E-diol to prevent the loss of dopaminergic neurons. Moreover, that substance restored functioning of the mitochondrial respiratory chain complexes and significantly reduced the production of reactive oxygen species, preventing oxidative damage. Thus, E-diol can be considered as a new potential agent for the treatment of Parkinson’s disease. ## 1. Introduction Parkinson’s disease is the second most common disease among neurodegenerative disorders [1,2] after Alzheimer’s disease [3] and is characterized primarily by motor disorders caused by the loss of dopaminergic neurons in the compact part of the substantia nigra [4,5]. In patients with advanced stages of this disease, up to $95\%$ of these neurons die [6]. A large number of papers describing the possible mechanisms of dopaminergic neurons loss are devoted to the study of the mitochondrial complex I (NADH-dehydrogenase complex) activity, a decrease in the activity of which is shown in the brain of patients with parkinsonism [7,8,9]. This complex is the main entry point of electrons into the respiratory chain, by which initiates oxidative phosphorylation and the ATP production by mitochondria [10]. Given that an impairment in the functioning of mitochondria currently plays a key role in the pathogenesis of Parkinson’s disease [11,12], a promising direction in the search for potential drugs is to focus on their ability to level mitochondrial dysfunction. A promising class of compounds on the basis of which highly effective neuroprotective drugs for the treatment of Parkinson’s disease can be developed are monoterpenoids [13,14,15,16]. Previously, the antiparkinsonian potential of (1R,2R,6S)-3-methyl-6-(prop-1-en-2-yl)cyclohex-3-en-1,2-diol (diol (Prottremin), Figure 1) [17,18], which is currently in the first stage of clinical trials, was discovered. The active metabolite epoxide (1S,2S,3R,4S,6R)-1-methyl-4-(prop-1-en-2-yl)-7-oxabicyclo[4.1.0]heptane-2,3-diol (E-diol, shown in Figure 1) was also found to produce a similar effect as the compound mentioned earlier. E-diol has a high antiparkinsonian activity. In addition, epoxidiol has demonstrated the ability to repair dopaminergic neurons damaged by the neurotoxin MPTP, triggering a signaling cascade of mitogen-activated protein kinase (MAPK) [19]. It gives hope for an effective treatment of the disease. In order to bring more insight into possible mechanisms of the antiparkinsonian action of epoxidiol, in this work, we conducted for the first time a study of its biological activity as part of a consecutive study of mitoprotective properties at in vitro, in vivo and ex vivo testing stages. To simulate the pathogenesis of Parkinson’s disease, rotenone was used, which is a widely used neurotoxin in a large number of studies. It is used both to elucidate the mechanisms underlying the death of dopaminergic cells and to study new potential neuroprotective agents [20,21,22,23]. This is due to its involvement in many pathological pathways that mediate the death of dopaminergic neurons [24,25,26], the ability to reproduce both motor [27,28] and non-motor symptoms of parkinsonism [29,30,31], as well as an extremely high lipophilicity [32], which allows it to penetrate easily the blood–brain barrier. Figure 2 shows the mechanisms of rotenone action that cause neuropathological signs, as well as motor and non-motor symptoms. It has been proven that rotenone reproduces the most common symptoms of Parkinson’s disease due to direct inhibition of the mitochondrial respiratory chain complex I [33,34]. In our work, we tried to reproduce a rotenone-induced model of Parkinson’s disease using in vitro, in vivo and ex vivo approaches. It was investigated whether treatment with epoxidol by modulating mitochondrial functions could restore the behavioral and neurochemical profile of mice with the phenotype of this disease. ## 2.1. Rotenone-Induced Neurotoxicity on the SH-SY5Y Cell Line To assess the effect of diol (initial compound) and epoxidiol on the viability of SH-SY5Y cells, an MTT analysis was performed based on the ability of mitochondrial dehydrogenases of living metabolically active cells to cleave the membrane-permeable yellow tetrazolium salt (3-[4,5-dimethylthiazole-2-yl]-2,5-diphenyltetrazolium bromide, MTT), restoring it to purple intracellular formazan crystals. Initially, to assess the possible intrinsic toxic effects of the compounds under study, their effect on cell survival was tested at the maximum used concentration of 100 µM in absence of rotenone. It was found that diol leads to suppression of cell survival by 18.13 ± $0.63\%$ ($p \leq 0.0001$), but its epoxide did not cause any decrease in cell viability (Figure 3a) (97.48 ± 0.93, $$p \leq 0.43$$). In turn, the selected concentrations of rotenone (100 nM and 400 nM) led to a decrease in cell survival by 26.13 ± $1.75\%$ and 37.40 ± $1.34\%$ ($p \leq 0.0001$) (Figure 3b) compared with control samples, which is consistent with the already known data obtained for this toxin in similar experiments [35,36]. In experiments with the combined use of the studied compounds and rotenone, it was found that epoxidiol showed a protective effect on the SH-SY5Y cell line exposed to rotenone (Figure 3c,d). This effect was concentration-dependent, reaching a maximum at 100 µM and increasing the number of viable cells from 73.87 ± $1.75\%$ (rotenone concentration—100 nM) and 62.60 ± $1.34\%$ (rotenone concentration—400 nM) up to 91.74 ± $2.54\%$ and 90.53 ± $3.18\%$ ($p \leq 0.0001$), respectively. At the same time, diol had no effect on the viability of cells treated with rotenone (Figure 3e,f). ## 2.2. Rotenone-Mediated Depolarization of Isolated Rat Liver Mitochondria To analyze the process of depolarization of the mitochondrial membrane under the action of rotenone, the transmembrane potential of organelles pretreated with the studied compounds in the concentration range from 10 to 100 µM was measured. A potential-dependent safranin O label was used, the fluorescence of which is quenched in the mitochondrial matrix of polarized organelles [37]. The value of the transmembrane potential is inversely proportional to the values of the safranin O fluorescence. The kinetic curves of changes in the mitochondrial membrane potential in samples by the action of modulators are shown in Figure 4b,c. Energization of organelles by substrates of the respiratory chain complex I—glutamate and malate led to a decrease in fluorescence, which corresponds to an increase in the transmembrane potential and reflects the use of a proton gradient to stimulate ATP synthesis. As expected, the sequential addition of rotenone led to a significant decrease in the transmembrane potential, which indicates the depolarization of the mitochondrial membrane. In turn, for the studied compounds, the ability to reduce the response of organelles to the rotenone pulses was observed. Epoxidiol most effectively normalized the impairment of the mitochondrial membrane potential caused by the toxin. This compound in the maximum studied concentration prevented the amplification of the fluorescence signal by $47\%$ (after the first ROT injection), $37\%$ (after the second ROT injection) and $26\%$ (after the third ROT injection). ## 2.3. Bioenergetic Profile of the SH-SY5Y Cell Line under Conditions of Reduced Mitochondrial Function Caused by Rotenone To study the bioenergetics of mitochondria, a Seahorse/Agilent Mito Stress Test was used on Seahorse XFe96 Extracellular Flux Analyzer [38] with some modifications. Before starting the analysis according to the standard protocol, neuroblastoma cells were subjected to 24 h treatment with the test compounds at a 100 µM concentration. Interestingly, the oxygen consumption rate (OCR) in the analysis of basal respiration was the same for all groups with the exception of diol, which significantly reduced it (Figure 5b). After the first injection, a significant decrease in the oxygen consumption rate from 28.22 ± 0.65 pmol/min to 14.68 ± 2.11 pmol/min was observed in cells treated with a non-toxic 10 nM rotenone concentration compared to control cells receiving solvent injection (on average by $48\%$, $$p \leq 0.01$$, Figure 5b,e). It was also confirmed by analyzing the quantitative indicator of the acute response parameter (Figure 5c). However, pretreatment of neuroblastoma cells with epoxidol was able to neutralize the effects caused by the toxin (Figure 5b,e). The OCR of the ROT + E-diol group was at the level of control samples (26.63 ± 5.11 pmol/min) and had a strong tendency to increase compared to the ROT group ($$p \leq 0.07$$). A similar situation was observed in the OCR indicator associated with ATP production (Figure 5f). Rotenone significantly reduced this parameter from 18.43 ± 1.53 pmol/min to 5.33 ± 1.11 pmol/min (by $71\%$ when compared with the control group, $$p \leq 0.04$$). Finally, the use of epoxidiol kept the OCR associated with ATP production at the level of 18.87 ± 4.93 pmol/min, which is significantly higher than in the samples with rotenone (by $72\%$ when compared with ROT, $$p \leq 0.04$$). In the case of samples pretreated with diol at a 100 µM concentration, the OCR was already at a much lower level from the first measurement, and the subsequent addition of modulators to the medium did not cause any pronounced responses. This is most likely due to some cytotoxic activity detected above for this substance, where 18.13 ± $0.63\%$ of cells died at this concentration (Figure 3a). ## 2.4. In Vivo Study of Motor Activity and Endurance of Mice Simulating Parkinson’s Disease To simulate the pathological phenotype of Parkinson’s disease with the in vivo studies, male mice of the C57BL/6J line were injected with rotenone at a 1 mg/kg dose daily for 21 days by intraperitoneal injection (Figure 6). In order to compare possible differences in the neuroprotective effects of epoxidiol, the compound at a 15 mg/kg dose was administered according to two schemes: [1] daily, starting from the 8th day of the experiment in already formed pathology conditions, and [2] daily throughout the entire period of the experiment. As a control group, animals of the same age were used, which received injections of equivalent volumes of solvents. The motor characteristics of the animals were evaluated in the Open Field test by the average speed and distance traveled during a 5-min experiment. As shown in Figure 7a,b, in the ROT group there was a statistically significant decrease in the average movement speed of animals compared to the control group from 8.83 ± 0.71 m/s to 3.23 ± 0.89 m/s ($$p \leq 0.008$$ vs. Control). A similar pattern was shown in the distance traveled, which was reduced from 2645.41 ± 213.47 cm to 969.46 ± 265.69 cm ($$p \leq 0.008$$ vs. Control). Animal groups treated with epoxidiol in addition to the toxin demonstrated the ability to restore motor activity indicators. This was expressed in the tendency of mice from the ROT + E-diol (I) group to increase the average speed and distance traveled ($$p \leq 0.080$$ vs. ROT). In the ROT + E-diol (II) group, there was a significant improvement in these indicators to 9.43 ± 1.58 m/sec and 2827.26 ± 472.78, which corresponds to the level of control animals ($$p \leq 0.002$$ vs. ROT and $p \leq 0.999$ vs. Control). Mice motor coordination and endurance were evaluated using an accelerating speed Rotarod test. Interestingly, most of the animals from the control group successfully passed the 5-min test during the testing phase, demonstrating almost $100\%$ stay on the rolling rod (Figure 7d). In turn, mice simulating Parkinson’s disease spent significantly less time on rotarode than intact animals, reducing this indicator from 94.73 ± $3.52\%$ to 68.87 ± $7.12\%$ ($$p \leq 0.002$$ vs. Control). This indicates that the mice motor function from the ROT group was significantly impaired, which was expressed in their inability to stay on the rolling rod. Treatment with epoxidiol significantly improved the ability of animals to stay on the rotarode, while, as in the Open Field test, when using the first administration scheme, there was a tendency to improve endurance and coordination (86.13 ± $3.98\%$, $$p \leq 0.076$$ vs. ROT). Combination therapy with epoxidiol during the entire period of the in vivo experiment led to a significant increase in the time spent on rotarode—94.03 ± $2.78\%$ ($$p \leq 0.002$$ vs. ROT) up to the level of control mice ($p \leq 0.999$ vs. Control). ## 2.5. In Vivo Study of Hippocampus-Dependent Spatial Memory of Mice Simulating Parkinson’s Disease Hippocampus-dependent spatial working memory was evaluated by measuring the time mice spent in the target arm of the maze (Figure 8). It was found that mice receiving rotenone injections spent less time in the target arm of the maze during the testing phase compared to C57BL/6J control animals (39.38 ± 9.46 s for the ROT group and 70.13 ± 12.60 s, $$p \leq 0.043$$ vs. Control). In turn, for the ROT + E-diol (II) group, which received epoxidiol starting from the first day of the in vivo experiment, the ability to significantly increase this indicator up to 108.63 ± 16.80 s ($$p \leq 0.005$$ vs. ROT) was observed, exceeding that of the control group. ## 2.6. The Level of Dopaminergic Neurons in Brain Samples of Mice Modeling Parkinson’s Disease To determine the number of dopaminergic neurons, brain slices were stained with an anti-tyrosine hydroxylase antibody (TH), an enzyme that limits the dopamine synthesis rate [39], and stereological counting of TH-positive neurons in substantia nigra pars compacta (SNpc) and ventral tegmental area (VTA) was performed. In mice from the ROT group, there was a significant decrease in the number of TH-positive dopaminergic neurons in both studied areas (Figure 9b,e) by $27.8\%$ ($$p \leq 0.050$$ vs. Control) and $32.4\%$ ($$p \leq 0.023$$ vs. Control, Figure 9a), respectively. On the contrary, the number of neurons was significantly increased in animals treated with epoxidiol during 14 (Figure 9c,e) and 21 (Figure 9d,e) days of administration. In mice from the ROT + E-diol (I) group, this value was significantly higher by $36.6\%$ (in SNpc; $$p \leq 0.050$$ vs. ROT) and $41.7\%$ (in VTA; $$p \leq 0.028$$ vs. ROT). In turn, for the ROT + E-diol (II) group, the number of TH-positive dopaminergic neurons exceeded that for ROT by $45.7\%$ (in SNpc; $$p \leq 0.010$$ vs. ROT) and $45.9\%$ (in VTA; $$p \leq 0.017$$ vs. ROT). ## 2.7. Dynamics of Mitochondrial Respiration and Oxidative Stress in Brain Samples of Mice Modeling Parkinson’s Disease To confirm that the symptoms of parkinsonism observed in the rotenone-induced model are due not to systemic toxicity, but to the targeted effect of the toxin on the electron transport chain, and the ability of epoxidiol to exert antiparkinsonian effects in the in vivo model of the disease is associated with the mitoprotective properties of the compound, a functional assessment of the mitochondrial complex's activity was carried out. The Seahorse XF96 cellular metabolism analyzer was used to measure the oxygen consumption rate by the mitochondrial p2 fraction obtained from the animal brain after injections of various substrates and inhibitors of electron transport chain complexes. The first three cycles of measuring the oxygen consumption rate by mitochondria pretreated with glutamate and malate substrates of complex I confirmed the hypothesis of the inhibitory effect of rotenone on NADH dehydrogenase (Figure 10a,b). This was evidenced by a decrease in this indicator from 74.78 ± 2.34 pmol/min (for control samples) to 45.73 ± 1.95 pmol/min ($$p \leq 0.0003$$ vs. Control). This effect was reduced in brain samples of animals from groups treated with epoxidiol, where exposure to the compound led to an increase in the oxygen consumption rate by $28.7\%$ (in the case of ROT + E-diol (I); $$p \leq 0.037$$ vs. ROT) and $29.4\%$ (for ROT + E-diol (II); $$p \leq 0.033$$ vs. ROT). After inhibition of the NADH-dehydrogenase complex by rotenone, its substrate, succinate, was added to stimulate complex II respiration. Enhanced respiration was shown for all groups; however, in the mitochondrial p2 fraction obtained in ROT mice, the activity of this complex was reduced by more than $50\%$ ($$p \leq 0.0002$$ vs. Control). In turn, mice treated with epoxidiol for 21 days had an increase in OCR from 195.04 ± 7.336 pmol/min to 360.49 ± 26.46 ($$p \leq 0.008$$ vs. ROT). As expected, the subsequent addition of an inhibitor of complex III, antimycin A, reduced OCR, which was eliminated by the introduction of electron donors of complex IV—ascorbate/N,N,N, N-tetramethyl-p-phenylenediamine (TMPD), delivering them directly to cytochrome C oxidase. A similar situation was found in the ROT samples with a decrease in the oxygen consumption rate observed in the case of complex II. It indicates that the blocking of complex I by rotenone entails a further cascade of events that prevents the transport of electrons throughout the subsequent chain. And in this case, epoxidiol had the ability to improve mitochondrial function. To analyze the effect of epoxidiol on the formation of free radicals in the brains of experimental animals, the lipid peroxidation level in mouse brain homogenates was studied. It was found that treatment with rotenone significantly increased the malondialdehyde content, a marker of the oxidative stress intensity in the body (Figure 11). At the same time, this indicator was 0.453 nmol/mg protein compared to 0.410 nmol/mg protein in control samples ($$p \leq 0.003$$ vs. Control). In turn, in the brain samples of animals treated with epoxidiol, there was a significant decrease in the lipid peroxidation level up to 0.342 nmol/mg protein in the case of a 21-day treatment regimen of the compound. It should be noted that in addition to significant differences compared to the ROT group ($p \leq 0.0001$), the epoxidiol injection significantly reduced the malondialdehyde content and when compared with the control ($$p \leq 0.0005$$ for ROT + E-diol (I) and $p \leq 0.0001$ for ROT + E-diol (II) vs. Control), which suggests the presence of antioxidant properties for the studied compound. ## 3. Discussion Mitochondria, which control energy metabolism, generation of reactive oxygen species and release of apoptotic factors, play a key role in the processes of survival and apoptotic cell death. Disruption of the functioning of these organelles is an early manifestation of almost all neurodegenerative diseases [40,41], including Parkinson’s disease [42,43,44]. For more than 30 years, mitochondrial dysfunction has been considered a key factor leading to the loss of dopaminergic neurons in the substantia nigra of the brain of patients with both sporadic and familial forms of Parkinson’s disease [45,46]. This is evidenced by a large amount of experimental data, as well as the results of clinical and preclinical studies [47,48,49,50,51,52]. In this regard, a promising direction with high potential in the development of pharmacological approaches for the prevention and treatment of Parkinson’s disease is the development of therapeutic strategies aimed at maintaining the function of mitochondria [53,54]. To date, there are several experimental models used to reproduce Parkinson’s disease. These methods are based on the introduction of toxic chemical compounds, the purpose of which is to simulate the pathological conditions observed in this disease. Such substances primarily include 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), the use of which, however, has some limitations precisely in the context of considering mitochondrial dysfunction as the main mechanism underlying Parkinson’s disease. In this regard, in our work, another neurotoxic compound, rotenone, which is a classic inhibitor of mitochondrial complex I, was used to investigate the possibility of using the monoterpenoid epoxidiol as a potential antiparkinsonian agent. So, in the work of Zhang et al. [ 55], it was shown that the mitochondrial-dependent oxygen consumption and the activity of the NADH dehydrogenase enzyme in the substantia nigra were at a significantly lower level in the rotenone group compared to MPTP. This indicates that rotenone makes it possible to more accurately reproduce the pathological sign associated with mitochondrial dysfunction, without loss of effectiveness in relation to neurobehavioral reactions. A number of studies have shown that rotenone induces cell death along the path of mitochondrial-dependent apoptosis, increasing the number of apoptotic cells [25,56,57]. In the present study, the effect of diol and its epoxidized form on the survival of the neuroblastoma cell line SH-SY5Y exposed to rotenone was studied. Neuronal-like SH-SY5Y cells are one of the most frequently used models for the study of neurotoxic and neuroprotective effects of compounds [58,59]. Our results confirmed the ability of rotenone to induce toxicity in SH-SY5Y cells. Treatment with rotenone for 24 h resulted in the death of SH-SY5Y in a dose-dependent manner, and at a toxin concentration of 400 nM, ~ $60\%$ cell viability was observed. Such conditions simulate the situation observed in the early stages of Parkinson’s disease, when the death of about $50\%$ of neurons in the substantia nigra is recorded, but most of them are subject to subcellular stress [60]. In our work, the preliminary 24 h incubation of epoxidiol led to a significant increase in the number of living cells in a dose-dependent manner. At the maximum studied concentration of 100 µM, this compound was able to protect SH-SY5Y cells from damage caused by rotenone, increasing viability to the values of control samples. The toxicity shown for rotenone can be induced by apoptosis using various mechanisms, among which the key is its ability to lead to the dissipation of the mitochondrial transmembrane potential. This correlates with the pathological condition in Parkinson’s disease, when, due to a deficiency of PTEN-induced kinase 1 (PINK1), there is a decrease in the basement membrane potential and an impairment of calcium homeostasis [61], leading to the vulnerability of neurons to the opening of a transitional permeability pore, followed by the death of nerve cells [62]. When monitoring representative tracks showing the dynamic reaction of the transmembrane potential in response to the sequential addition of subthreshold nontoxic concentrations of rotenone, we detected a step-by-step increase in the fluorescence signal. This indicated a time-increasing depolarization process in response to rotenone pulses, which is consistent with the data known for this toxin [63]. On the contrary, for epoxidiol, there was a pronounced ability to retain an electric gradient on the membrane of mitochondria exposed to the toxin. Obviously, this may explain its protective role in neurotoxicity conditions on the neuroblastoma cell model due to the modulation of events in the apoptotic cascade following the loss of mitochondrial membrane potential. As mentioned above, rotenone is a potent inhibitor of the mitochondrial electron transfer chain complex I, blocking the subsequent use of oxygen during oxidative phosphorylation and reducing the ATP production [64,65]. Such modulation of metabolism and respiratory capacity of organelles has a pronounced correlation with cell death, which is important for the formation of pathology in Parkinson’s disease [66,67,68,69]. This is due to the fact that the NADH-dehydrogenase complex is higher in the mitochondrial electron transfer chain, due to which electrons are transferred from nicotinamide adenine dinucleotide to lower molecules [70]. A number of studies show that the mitochondrial complex I dysfunction occupies a central place in the pathogenesis of Parkinson’s disease. In our work, it was found that the treatment of neuroblastoma cells with a non-toxic concentration of rotenone leads to a decrease in the oxygen consumption of the SH-SY5Y culture as a result of the function of complex I inhibition. It is not surprising that with the further addition of modulators to the system, no pronounced responses were observed in samples with rotenone, as shown in the control. This confirms the statement about the key role of blocking the NADH-dehydrogenase complex in the subsequent cascade of mitochondrial respiration events [71,72,73]. More importantly, epoxidiol significantly weakened the effect of rotenone, which indicates the ability of this compound to protect the respiratory function of organelles from the toxin action. Thus, the results obtained as part of a phased in vitro screening using biological objects of different organization levels, demonstrated for epoxidiol the ability to inhibit the rotenone toxicity, due to alleviating mitochondrial dysfunction. Next, the effect of the compound on the parameters of mice motor function and spatial memory was investigated in a rotenone-induced model of Parkinson’s disease in vivo. Due to the fact that the observed differences in the pharmacological effects of rotenone when using different doses require an accurate choice of the protocol for the use of the toxin, an analysis of the experimental data available to date was initially carried out. It was found that excessively high doses of rotenone lead to the development of obvious systemic toxicity affecting internal organs and causing death of the body, and do not induce the phenotype of parkinsonism [22,74]. In turn, when using low doses of the toxin with repeated administration a clear time dependence of the development of Parkinsonian pathology is observed [75,76,77], which led to the selection of the rotenone administration scheme in an in vivo experiment. In our study, intraperitoneal administration of rotenone at a 1 mg/kg dose per day for 21 days significantly worsened the motor functions and endurance of mice. This was manifested in a decrease in motor activity in the Open Field test and motor coordination and endurance in the Accelerating Rotarod test, which, as can be assumed, mimic hypokinesia, rigidity and violation of postural reflexes observed in patients with Parkinson’s disease [78,79]. It is noteworthy that when epoxidiol was administered according to the first scheme (starting from the 8th day of the experiment, when the formation of pathology had already begun), there was a tendency to alleviate motor disorders and coordination in mice with Parkinsonism. In turn, 21-day treatment with this compound reduced motor dysfunction, which obviously implies the most pronounced success of the use of epoxidiol as a preventive therapeutic approach, as well as at the earliest stages of the disease development. In addition to the symptoms associated with motor disorders, so-called non-motor disorders are observed in patients with parkinsonism, among which cognitive dysfunctions are the most common [80,81,82]. In particular, a large number of papers describing the pathological phenotype of Parkinson’s disease in both humans and animal models indicate an impairment of hippocampus-dependent spatial memory [83,84,85]. As part of our study in the Y-shaped maze test, mice receiving rotenone spent significantly less time in the correct maze arm, which indicates their impaired ability to learn and form memory. Interestingly, epoxidiol leveled this non-motor sign of Parkinsonism, which is an important indicator of the Parkinson’s disease progression [86]. Summarizing the results of an in vivo study of the epoxidiol effects on the neurobehavioral characteristics of mice simulating Parkinson’s disease, the combined use of the compound from the first day of rotenone administration significantly improved the behavioral status in animals, which may be due to its neuroprotective effect due to mitoprotective properties. At the end of in vivo testing, in order to form a full understanding of the mechanisms of the antiparkinsonian action of epoxidiol, we analyzed brain samples from mice of experimental groups. Despite the fact that various types of neuronal cells are affected in Parkinson’s disease, the role of dopamine neurons has been best studied up to date [87]. Pathophysiological studies of patients with this disease indicate that the cardinal signs, manifested primarily in the progressive development of motor symptoms, are caused by a decrease in dopamine levels and the loss of dopaminergic neurons in the nigrostriatal system [88,89]. To study the protective effect of epoxidiol on dopaminergic neurons, we performed tyrosine hydroxylase immuno-staining. The results showed that compared with the control group, mice treated with rotenone had a serious loss of TH-positive neurons. These data are completely consistent with the results of a large number of similar studies, where rotenone selectively damaged neurons in dopamine-rich brain areas. In turn, treatment with epoxidiol facilitated this situation due to the protective effect on neuronal cells in the areas most affected by Parkinson’s disease—the compact substantia nigra and the ventral tegmental area of animals with Parkinsonism. Thus, there is a direct correlation of the results obtained with the data of in vivo series of experiments, where the administration of epoxidiol significantly improved the neurobehavioral profile of mice with parkinsonism caused by rotenone. Due to the fact that Parkinson’s disease is associated with disorders in the mitochondrial respiratory chain, which is the main source of reactive oxygen species (ROS) formation, post mortem analysis of brain samples of patients with Parkinsonism proves that dopaminergic neurons are in a condition of permanent oxidative stress and undergo radical oxidation with the ROS formation [90,91,92]. In turn, reactive oxygen species convert dopamine into reactive dopamine-quinone, which is highly toxic, and which, apparently, may be the cause of pronounced death of dopaminergic neurons [93]. A similar pattern is observed with the action of rotenone. Blocking of the complex I of the respiratory chain and, as a consequence, the transfer of electrons to oxygen leads to the formation of reactive oxygen species, especially superoxide radicals [94]. This was confirmed in our work, which shows that the administration of low rotenone doses for 3 weeks led to the disruption of the mitochondrial respiratory chain complexes and, as a consequence, an imbalance of redox homeostasis in the brain of mice, which was expressed in an increase in the level of malondialdehyde, a marker of lipid peroxidation. In turn, epoxidiol markedly reduced the generation of reactive oxygen species induced by rotenone, which suggests the presence of a protective antiparkinsonian mechanism of epoxidiol associated with the ability to reduce oxidative stress. ## 4.1. Agents Diol and E-diol were synthesized from [-]-verbenone (Sigma-Aldrich, St. Louis, MO, USA) according to earlier published methods [17,18] with the purity > $98\%$. ## 4.2. Preparation of Working Solutions To obtain initial solutions of the studied compounds in a 10 mM working concentration, diol and epoxidiol were dissolved in sterile bidistilled water. Rotenone solution (400 µM, Sigma-Aldrich, St. Louis, MO, USA) it was prepared in dimethyl sulfoxide (DMSO, Sigma-Aldrich, St. Louis, MO, USA). The obtained solutions were stored at a temperature of +2 to +4 °C. Methods of processing cells or organelles with compounds are indicated in the relevant subsections of this section and the captions to the figures. ## 4.3. Cell Lines and Cultivation The human neuroblastoma cell line SH-SY5Y provided by the Institute of Cytology of the Russian Academy of Sciences was cultured in a humidified atmosphere with $5\%$ CO2 at +37 °C. Cells were grown in Dulbecco’s Modified Eagle Medium (DMEM) (Gibco, Scotland, UK) containing $10\%$ fetal bovine serum (ThermoFisher Scientific, Paisley, UK), L-glutamine (2 mM) (Gibco, Scotland, UK), and penicillin-streptomycin ($1\%$ by volume) (PanEco, Moscow, Russia). The nutrient medium was changed every 2–3 days after reaching 85–$90\%$ of cell growth. ## 4.4. Cell Viability Assay The human neuroblastoma cell line SH-SY5Y (provided by the Institute of Cytology of the Russian Academy of Sciences) was seeded into 96-well plates (1 × 104 cells/200 µL, Corning Inc., New York, NY, USA) in a growth medium (composition described above) and cultured for 24 h at +37 °C, $5\%$ CO2. A day later, diol and epoxidiol were added (1, 10, 50 and 1.0 and 100 µM). Rotenone (100 nM and 400 nM) was introduced into the wells of the plate 24 h after the addition of the studied compounds and incubated for another 24 h. The negative control was treated with appropriate volumes of solvents used to obtain working solutions of diol and epoxidiol (bidistilled H2O) and rotenone (DMSO), and the positive control was bidistilled H2O and rotenone. Cell viability was assessed by MTT analysis, as described in [95]. To do this, MTT (bromide 3-(4,5-dimethylthiazole-2-yl)-2,5-diphenyltetrazolium, 5 mg/mL, Dia-m, Moscow, Russia) was introduced into each well and additionally incubated for 2 h (until a characteristic color appears). Using a flatbed analyzer (Cytation3, Biotech Instruments Inc., Winooski, VT, USA), the optical density of the formed formazan granules was determined at λ = 530 nm. ## 4.5. Mitochondrial Membrane Potential Measurements The mitochondrial transmembrane potential was measured by recording the fluorescence of the potential-dependent marker Safranin O [96] in a 96-well plate. The well of the tablet contained mitochondria (0.5 mg/mL) previously diluted in a buffer (225 mM mannitol (Dia-m, Moscow, Russia), 75 mM sucrose (Dia-m, Moscow, Russia), 10 mM HEPES (Dia-m, Moscow, Russia), 1 mM KH2PO4, 20 µM EGTA (Cabiochem, San Diego, CA, USA), pH = 7.4) mixed with 5 µM safranin O. According to the experimental scheme, the studied substances were added to the mitochondria in a concentration of 10 up to 100 µM and incubated for 5 min. After the incubation time, the initial measurement was carried out for 10 cycles. After that, substrates of the mitochondrial respiratory chain complex I were added to each well—a solution of sodium glutamate and sodium malate (5 mM). The measurement continued for the next 30 cycles until a stable signal indicating the polarization of the mitochondrial membrane appeared. Next, the rotenone was titrated with pulses in all wells (three times in 10 nM) with 20 measurement cycles after each addition. Finally, 25 µM of Ca(II) was added to achieve maximum fluorescence due to the opening of the mitochondrial pore and measured for 20 cycles. Fluorescence measurements were carried out on a Victor 3 plate analyzer (Perkin Elmer, Rodgau, Germany) at λex = 485 nm and emission λem = 590 nm. ## 4.6. Automatic Measurement of Energy Metabolism in Real Time by Registering Oxygen Consumption Rate The oxygen consumption rate (OCR) of the SH-SY5Y neuroblastoma cell line was measured in real time using the Seahorse XFe96 cellular metabolism analyzer (Agilent Technologies, Santa Clara, CA, USA) and the Seahorse/Agilent Mito Stress Test [38] with some modifications. SH-SY5Y cells in the exponential growth phase were seeded into a 96-well Seahorse cell culture microplate. The planting density of the cell culture was 3 × 104/well. After 24 h, solutions of diol and epoxidiol (100 µM) were added to the cells, and an equivalent volume of solvent was added to the remaining wells and left to incubate at +37 °C, $5\%$ CO2 per day. The next day, according to the protocol, the sensor cartridge with injection ports was filled with reagents to assess changes in OCR by modulating cellular metabolism. Next, the analyzer was calibrated, after which the plate was replaced with a research plate with cells and the oxygen consumption rate was recorded. Initially, three measurements of the basic OCR rate of the SH-SY5Y cell line were carried out. Then, from port A, rotenone was injected into the medium at a non-toxic concentration of 10 nM or a medium containing the appropriate solvent (as a control) and the oxygen consumption rate was measured for five cycles. Further, oligomycin (2 µM, Sigma-Aldrich, St. Louis, MO, USA), FCCP (carbonyl cyanide-4 (trifluoromethoxy) phenylhydrazone, 2 µM, Sigma-Aldrich, St. Louis, MO, USA) and antimycin A (1 µM, Sigma-Aldrich, St. Louis, MO, USA) were sequentially injected through ports B, C and D and three measurements were carried out. The use of such a protocol made it possible to evaluate a number of parameters, including acute reaction, basal respiration, respiration after blocking the I complex of the respiratory chain of electron transfer by rotenone, respiration associated with ATP production, proton leakage, maximum respiration, etc. The acute reaction was calculated as the last OCR measurement before injection of rotenone minus the last measurement after injection into port A. The addition of oligomycin, which blocks ATP synthase and leads to the suppression of oxidative phosphorylation, made it possible to calculate the OCR associated with ATP production by subtracting the last measurement before injection of oligomycin and measuring the minimum rate after injection of oligomycin. Cells treatment of FCCP that dissociate electron transport and ATP synthesis made it possible to evaluate the maximum OCR associated with respiration and spare respiratory capacity. Antimycin A, which is an inhibitor of cellular respiration by blocking the III complex of the respiratory chain, allowed us to calculate OCR that is not associated with mitochondrial respiration. The results were analyzed using Wave Desktop software version 2.6 (Agilent Technologies, Santa Clara, CA, USA). ## 4.7. Experimental Animals Forty adult male mice of the C57BL/6J line (The Jackson Laboratory, Bar Harbor, ME, USA), crossing in an animal facility for several years on identical genetic background (age 14 weeks; weight 24 ± 2 g), were used for the study. The animals were kept in conditions with controlled temperature (23 ± 1 °C), humidity (50 ± $5\%$) and lighting cycle (12 h/12 h light/dark). Water and food were given ad libitum. All behavioral tests were conducted in the test room at the same time of day. On the day of testing, one hour before the start of the experiment, the mice were moved to the experimental room, and the animals were allowed to adapt to the environment. By simple aleatorization, four groups of mice were formed ($$n = 10$$ per group):[1]Control—a group of mice that were intraperitoneally injected with bidistilled water and a solution of NaCl + $10\%$ DMSO—1 µL/g/day (for 21 days);[2]ROT—a group of mice receiving intraperitoneal injections of bidistilled water and rotenone (1 mg/kg)—1 µL/g/day (for 21 days);[3]ROT + E-diol (I)—a group of mice treated intraperitoneally with epoxidiol (15 mg/kg) and NaCl + $10\%$ DMSO solution—1 µL/g/day (for 14 days (starting from the 8th day of the experiment);[4]ROT + E-diol (II)—a group of mice treated intraperitoneally with epoxidiol (15 mg/kg) and NaCl + $10\%$ DMSO solution—1 µL/g/day (for 21 days (starting from day 1 of the experiment). Epoxidiol was dissolved in sterile bidistilled water immediately before the experiment. The rotenone solution was prepared in DMSO and additionally dissolved in NaCl (up to $10\%$ DMSO). ## 4.8. Analysis of the Motor Activity of Mice in the Open Field Test An Open Field test was used to assess the motor activity of mice. The installation was a square gray box with a floor size of 40 × 40 cm and walls 40 cm high (the lighting intensity was 50 lux). The animal was placed in the center of the arena to study the installation for 5 min, after which the mouse was returned to the holding cage. After each test, the open-field arena was cleaned with $70\%$ ethanol in order to remove any odors from the previous animal and thoroughly dried. Each test was recorded using a camera connected to a computer, which subsequently allowed the results to be processed using the EthoVision XT system software (Noldus, Wageningen, The Netherlands). The parameters of motor function were evaluated, such as average speed and distance traveled. ## 4.9. Assessment of the Motor Function and Endurance of Animals in the Accelerating Speed Rotarod Test The motor function of animals was assessed on a rolling rod in the accelerating speed Rotarod test. The Rotarod hardware and software complex (Ugo Basile 7650, Biological Research Apparatus, Italy) is a cylinder divided by circular partitions into individual compartments and rotates cylindrical rods (3 cm in diameter) at a given speed. The installation makes it possible to assess motor and coordination disorders by the ability of animals to stay on a rotating cylinder. For training, on the first day of the experiment, mice were placed on a rolling rod for 5 min at a constant speed (4 rpm), after which they were returned to the holding cell. After 24 h, each animal was tested four times in accelerating mode (from 4 to 40 rpm) with 30 min intervals between trials, giving the mouse a maximum of 5 min to try. Latency to fall in each trial was recorded. The average latency to fall value for all four trials was included in the final statistics. After each animal, the apparatus was cleaned with $70\%$ ethanol and air-dried. ## 4.10. Analysis of Hippocampus-Dependent Spatial Memory of Mice in the Y-Maze Test The analysis of hippocampus-dependent spatial memory of animals was carried out in the Y-maze test. The installation of the Y-maze test is made of acrylic with three arms (arm size 32.5 × 8.5 × 15 cm) located at a distance of 120° from each other. During the training phase, the mouse was placed at the beginning of one maze arm (the starting arm) and allowed to move freely through two open arms of the maze for 5 min. After 30 min, a testing phase was carried out, during which the animal was placed in the same starting position but allowed to examine all three arms of the installation. After each animal, all the arms of the maze were thoroughly cleaned with $70\%$ ethanol and dried. All attempts were recorded on video for subsequent processing using the EthoVision XT system (Noldus, Wageningen, the Netherlands). The duration of the stay of the animals during the testing phase in the maze arms was analyzed. As a criterion for the effectiveness of the spatial memory formation, the animals’ presence in a new arm of the maze was considered. ## 4.11. Preparation of Histological Sections, Immunohistochemistry and Counting of Neuronal Cells Four-month-old male mice were terminated, and their brains were dissected. Fixation, preparation of histological sections, staining with anti-tyrosine hydroxylase antibody (TH, mouse monoclonal antibody, clone TH-2, Sigma diluted 1:1000) and stereological counting of TH-positive neurons in the SNpc and ventral tegmental area (VTA) were performed as described [97,98]. Briefly, the margins of SNpc and VTA on stained sections were outlined using distribution atlas of TH-positive cells [99]. The first section for counting was randomly chosen from the first ten sections that included the SN/VTA region. Starting from this section, on every fifth section, TH-positive cells with a clearly visible nucleus were counted through the whole region. ZEN Microscopy Software (Carl Zeiss) was employed to measure diameters of 30 nuclei of dopaminergic neurons in each of these regions of every mouse brain included in this study. The nuclei were chosen randomly, and the distance measured as the horizontal length as they appeared on the screen. A mean was calculated for each animal and used for Abercrombie’s correction [100] to obtain an actual number of TH positive cells in the structure. ## 4.12. Evaluation of Bioenergetic Parameters of the Mitochondrial p2 Fraction The study of the electron transport chain complexes was carried out on a preparation of the brain mitochondrial p2 fraction obtained by differential centrifugation. The Agilent Seahorse XF96e analyzer (Seahorse Bioscience, North Billerica, MA, USA) was used to measure the rate of oxygen uptake by organelles under the action of modulators. A total of 10 micrograms of mitochondria were loaded into the well of the tablet and a cold analysis buffer was added (1xMAS: 220 mM D-mannitol, 70 mM sucrose, 10 mM KH2PO4, 5 mM MgCl2, 2 mM HEPES, 1 mM EGTA, $0.2\%$ bovine serum albumin, free of fatty acids, pH = 7.2). The tablet was centrifuged at 2000× g for 20 min at 4 °C. Then, a warm 1xMAS buffer containing 10 mM of sodium malate and 10 mM of sodium glutamate was added to each well. Mitochondrial electron flow was evaluated by sequentially adding an inhibitor of the complex I—rotenone (2 µM), a substrate of the comp—lex II—sodium succinate (2 µM), an inhibitor of the complex III—antimycin A (1 µM) and substrates of the complex IV—ascorbate/N,N,N’,N’-tetramethyl-p-phenylenediamine dihydrochloride (TMPD) (0.5 µM). ## 4.13. Study of the Intensity of Lipid Peroxidation in Mouse Brain Homogenates The study of the intensity of lipid peroxidation (LPO) was carried out using a modified version of the TBA test. This technique is based on the reaction of 2-thiobarbituric acid with intermediate LPO products, as a result of which a colored trimethine complex is formed, the main role in the formation of which belongs to malonic dialdehyde. The intensity of LPO was determined in mouse brain homogenates. To do this, mice were sacrificed using the method of cervical dislocation and the brain was extracted, half of which was homogenized in a buffer containing 120 mM KCl, 20 mM HEPES pH = 7.4, at 4 °C, centrifuged at 1500 rpm and the supernatant was selected. The resulting homogenate (4 mg/mL) was introduced into the wells of a deep-well plate and a reagent for TBA-reactive products was added to each sample, after which it was incubated for 90 min at 90 °C. After the incubation time, the samples were centrifuged at 6000 rpm for 20 min and the optical density of the selected supernatant was measured on a flatbed analyzer (Cytation3, Biotech Instruments Inc., Winooski, VT, USA) λ = 540 nm. ## 5. Conclusions Parkinson’s disease is a multifactorial disease and is characterized by heterogeneous symptoms, including classical motor disorders and non-motor features caused by the loss of dopaminergic neurons in the brain substantia nigra. One of the key roles in the pathogenesis of this disease belongs to disorders in the functioning of the NADH-dehydrogenase complex, which is a trigger in starting the process of oxidative phosphorylation and ATP production by mitochondria. And due to the fact that currently there are no treatment methods that would slow down or stop the neurodegenerative process in Parkinson’s disease, the urgent task of modern biomedicine is to search for new drugs, in particular, due to the ability to modulate mitochondrial dysfunction. In this study, the analysis of the antiparkinsonian properties of trans-epoxide (1S,2S,3R,4S,6R)-1-methyl-4-(prop-1-en-2-yl)-7-oxabicyclo [4.1.0]heptane-2,3-diol (epoxidiol) on a model of rotenone-induced neurotoxicity using in vitro, in vivo and ex vivo approaches in the context of studying the mitoprotective properties of the compound. Our results showed that epoxidiol had cytoprotective properties on the SH-SY5Y cell line exposed to rotenone. This may be due to the ability of the compound to prevent the loss of mitochondrial membrane potential and, as a consequence, to modulate events in the subsequent apoptotic cascade. The analysis of the bioenergetic profile of neuroblastoma cells showed for epoxidiol the ability to restore the rate of oxygen consumption after inhibiting the complex I function and, as a consequence, weaken the effect of rotenone. In the conditions of modeling Parkinson’s disease in vivo, treatment with epoxidiol led to the leveling of both motor disorders and a non-motor symptom—cognitive dysfunction. In conclusion, the post mortem analysis of animal brain samples demonstrated the ability of epoxidiol to prevent the loss of dopaminergic neurons, which may be due to its properties to restore the functioning of mitochondrial respiratory chain complexes and significantly reduce the production of reactive oxygen species. 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--- title: Metabolic Features of Increased Gut Permeability, Inflammation, and Altered Energy Metabolism Distinguish Agricultural Workers at Risk for Mesoamerican Nephropathy authors: - Nathan H. Raines - Dominick A. Leone - Cristina O’Callaghan-Gordo - Oriana Ramirez-Rubio - Juan José Amador - Damaris Lopez Pilarte - Iris S. Delgado - Jessica H. Leibler - Nieves Embade - Rubén Gil-Redondo - Chiara Bruzzone - Maider Bizkarguenaga - Madeleine K. Scammell - Samir M. Parikh - Oscar Millet - Daniel R. Brooks - David J. Friedman journal: Metabolites year: 2023 pmcid: PMC10058628 doi: 10.3390/metabo13030325 license: CC BY 4.0 --- # Metabolic Features of Increased Gut Permeability, Inflammation, and Altered Energy Metabolism Distinguish Agricultural Workers at Risk for Mesoamerican Nephropathy ## Abstract Mesoamerican nephropathy (MeN) is a form of chronic kidney disease found predominantly in young men in Mesoamerica. Strenuous agricultural labor is a consistent risk factor for MeN, but the pathophysiologic mechanism leading to disease is poorly understood. We compared the urine metabolome among men in Nicaragua engaged in sugarcane harvest and seed cutting ($$n = 117$$), a group at high risk for MeN, against three referents: Nicaraguans working less strenuous jobs at the same sugarcane plantations ($$n = 78$$); Nicaraguans performing non-agricultural work ($$n = 102$$); and agricultural workers in Spain ($$n = 78$$). Using proton nuclear magnetic resonance, we identified 136 metabolites among participants. Our non-hypothesis-based approach identified distinguishing urine metabolic features in the high-risk group, revealing increased levels of hippurate and other gut-derived metabolites and decreased metabolites related to central energy metabolism when compared to referent groups. Our complementary hypothesis-based approach, focused on nicotinamide adenine dinucleotide (NAD+) related metabolites, and revealed a higher kynurenate/tryptophan ratio in the high-risk group ($$p \leq 0.001$$), consistent with a heightened inflammatory state. Workers in high-risk occupations are distinguishable by urinary metabolic features that suggest increased gut permeability, inflammation, and altered energy metabolism. Further study is needed to explore the pathophysiologic implications of these findings. ## 1. Introduction Mesoamerican nephropathy (MeN) is a devastating form of chronic kidney disease (CKD) in agricultural communities in the Pacific coastal region of Mesoamerica [1]. Two decades after its initial description, important questions remain about how environmental exposure and physiologic susceptibility intersect to produce kidney disease in at-risk populations. MeN is characterized as a non-diabetic non-hypertensive syndrome of CKD with minimal proteinuria, sterile pyuria, hyperuricemia, and nonspecific biopsy findings demonstrating tubular injury with ischemic features and cellular inflammation [2,3]. Notably, this description of MeN lacks details regarding the etiology and pathophysiology of the disease, as they remain poorly understood. Environmental stressors linked to agricultural labor are of particular interest in MeN, given the high prevalence of the disease among agricultural workers. Through use of metabolomics, the study of patterns of small molecules derived from cellular metabolism and exogenous sources [4], we can begin to understand the physiologic processes arising in response to exposures related to agricultural work [5,6]. An area of particular interest regarding the pathophysiology of MeN is derangement in the biosynthesis of nicotinamide adenine dinucleotide (NAD+). NAD+ is an essential coenzyme linking glycolysis and the citric acid (tricarboxylic acid, TCA) cycle with the mitochondrial electron transport chain [7,8]. NAD+ also participates in cellular repair and immune function [7,8]. Deficiency of NAD+ can become rate-limiting for normal oxidative metabolism, which in turn may impair organ function [7]. Alterations in energy metabolism centered around NAD+ emerge in the setting of physiologic stress in the kidney. These alterations are characterized by a decline in cellular NAD+ biosynthesis mediated in part by decreased activity of quinolinate phosphoribosyltransferase (QPRT) [9,10]. Depletion of cellular NAD+ plays a role in the pathophysiology of ischemic and inflammatory renal tubular injury [9,10,11,12]. While the contributions of ischemia and inflammation to the pathogenesis of MeN are not definitively established, they are among the leading hypothesized causes underlying the development of MeN [2,13,14]. NAD+ biosynthetic derangement and broader dysfunction in energy metabolism are also involved in the pathogenesis of chronic kidney disease, including fibrogenesis [15,16,17]. Exploration of NAD+ biosynthetic derangement among individuals engaged in activities associated with the development of MeN may therefore provide a link between these activities and disease pathogenesis. NAD+ biosynthesis occurs along three key pathways: the de novo pathway that utilizes tryptophan (Trp), the salvage pathway that uses nicotinamide (Nam), and the Preiss–Handler pathway that uses the acid form of Nam, nicotinic acid (Figure 1) [7]. In vivo, measurement of component metabolites in these pathways can provide insight into metabolic activity. For example, urine kynurenic acid (KynA), a derivative of Trp, is a useful biomarker of inflammation due to its role as a modulator of inflammatory response [18]. Increased urinary KynA levels are linked to non-recovery from acute kidney injury (AKI) [19]. Urine quinolinate to Trp (Q/T) ratio can be used as a biomarker of NAD+ biosynthetic derangement, with elevated ratios associated with kidney injury [10]. In this study, we used proton nuclear magnetic resonance (1H NMR) to characterize the urinary metabolic features of men in Nicaragua working as sugarcane harvest or seed cutters, job categories at very high risk for MeN based on prior research [20,21,22]. We compared this extreme risk group against three referent groups: Nicaraguan men who worked in sugarcane but not as sugarcane harvest or seed cutters; Nicaraguan men not working in agriculture; and men in Spain working in non-sugarcane agriculture. All individuals in this study had preserved kidney function, as evaluated by creatinine-based estimated glomerular filtration rate (eGFR) in order to minimize the impact of altered kidney function on urinary metabolite levels. In the primary analysis, we employed a non-hypothesis-based approach to evaluate differences in metabolic features between the high-risk sugarcane harvest/seed cutters and each referent group. In secondary analysis, we employed a complementary hypothesis-based approach, hypothesizing that NAD+ related metabolites would differ between the extreme risk group and referent groups. ## 2. Materials and Methods Research protocols were approved by the institutional review boards (IRBs) of Boston University Medical Campus (BUMC; Boston, MA, USA), Beth Israel Deaconess Medical Center (BIDMC; Boston, MA, USA), and the Parc de Salut Mar ethics committee (Barcelona, Spain). Participants in each of the four component studies contributing specimens for this analysis provided individual informed consent for adjunct specimen analysis related to kidney disease. ## 2.1. Study Design This is a cross sectional study using urine specimens from individuals in Nicaragua and Spain who were identified as having an eGFR > 75 mL/min/1.73 m2 based on the chronic kidney disease epidemiology consortium (CKD-EPI) 2021 serum creatinine equation without a race term, an equation shown to be accurate in MeN-affected populations [23,24]. Individual participants from the component studies in Nicaragua were selected to include only individuals where all available eGFR measurements were >75 mL/min/1.73 m2. Similar longitudinal creatinine data was not available for the Spanish population, so inclusion was based on a single eGFR measurement. The final sample included four distinct groups: Nicaraguan men working as sugarcane harvest or seed cutters (cut and seed, CS; $$n = 117$$); Nicaraguan men who work in sugarcane cultivation but not as sugarcane cutters (Other sugarcane workers, OW; $$n = 78$$); men who work in agriculture in Spain (Spanish workers, SW; $$n = 78$$); and Nicaraguan men who work in either the mining or brickmaking industry (non-agricultural workers, NW; $$n = 102$$). We tested voided urine specimens collected at the end of a work shift for the CS, OW, and SW groups, and at varying times during the day for the NW group. The CS and OW group specimens were collected in 2015 during an ongoing case-control study investigating risk factors for MeN in Nicaragua, as well as during follow-up from a previously published prevalence study in Nicaragua [25]. Specimens comprising the SW group were collected in 2018–2020 during a cross-sectional study, the “Acute Kidney Injury in Agricultural workers in Spain: risk factors and long term effects” (LeRAgs; https://www.isglobal.org/ca/-/lerags, accessed on 1 October 2022) study, in three provinces in Spain in which agricultural workers were recruited to study the association between environmental/occupational exposures and kidney disease. Specimens comprising the NW group were collected in 2016 and came from two previously published studies: one a case-control study among individuals working in mining-related activities, and one a prospective cohort study among individuals working as brickmakers [26,27]. All specimens were stored frozen at −80 °C from the time of collection until analysis. Pre-specified assessment of risk for each group is presented in Table 1. The CS group was considered highest risk, with each referent group considered to have lower but not necessarily equally low risk. Risk was categorized based on residence in a high-risk region; manual labor intensity, with more intense labor considered highest risk; and occupational environment, with agricultural work considered highest risk. ## 2.2. Laboratory Methods Urine specimens from all participants were analyzed using an AVANCE IIIHD (IVDr) 600 MHz Bruker NMR spectrometer equipped with a PA-BBI probe head with z-gradient coil and an automatic SampleJet sample changer operating at 300 K and using the standard operating procedures of the Phenome Center Consortium. For each sample, two different 1H NMR spectra were collected: a high-resolution 1D 1H spectrum to obtain quantitative metabolite data for statistical analysis and a 2D-Jres experiment for assistance in peak assignment and metabolite identification. Each spectrum was segmented into consecutive buckets (bins) of fixed 0.01 ppm width in the region between 9.5 and 0.5 ppm. Concentration for each metabolite was analyzed using the TSP signal in the urine spectra fitted to a generalized extreme value (GEV) distribution using a maximum—likelihood estimation (MLE) algorithm with Broyden–Fletcher–Goldfarb–Shanno (BFGS) optimization. ## 2.3. Data Analysis Data on demographics, anthropometry, and basic laboratory features of each of the CS, OW, NW, and SW populations were collected during the respective parent studies. Information on age, sex, medication use, and diagnosis of hypertension and diabetes was obtained in parent studies using participant questionnaires. Procedures for laboratory analyses were reported in the parent publications for the CS, OW, and NW populations [25,26,27]. For the SW cohort, urinalysis was conducted by dipstick and serum creatinine was measured using the Jaffe method. In non-hypothesis-based analyses, we compared levels of all measured metabolites between the CS and referent groups. We also analyzed levels of metabolites with groups pooled and compared by shared risk factors, as described in Table 1: Residence in a high-risk area (CS, OW, NW) or not (SW); work in higher (CS) versus lower (SW, NW, OW) physical intensity jobs; and work in agriculture (CS, OW, SW) or not (NW). Metabolites were analyzed both individually and grouped by metabolic pathway. Pathway analyses incorporated both differences in metabolite concentrations between groups and the impact of measured metabolites has on the overall activity of the pertinent metabolic pathway [28]. Pathways were defined using the Kyoto Encyclopedia of Genes and Genomes (KEGG) [29]. In our hypothesis-based approach, we compared urinary levels of Trp, KynA, NAD+, Nam, and 1-methylnicotinamide (MNA) to evaluate activity along the de novo and salvage pathways of NAD+ metabolism (Figure 1). To evaluate activity along different pathways of NAD+ biosynthesis, we compared ratios of concentrations of metabolites within each pathway. NAD+/Trp and KynA/Trp ratios were used as markers of activity favoring conversion of tryptophan to downstream metabolites, and NAD+/KynA as a marker of the relative concentrations of these downstream metabolites [19]. Similarly, NAD+/Nam and MNA/Nam ratios were used as markers of activity favoring conversion from Nam to downstream metabolites, and NAD+/MNA a marker of the relative concentration of downstream metabolites [30]. Quinolinate was not detected in the majority of samples using our 1H NMR methodology, so we were unable to evaluate the Q/T ratio as an indicator of NAD+ biosynthesis from Trp. Comparisons were made both across groups overall and between the CS and each referent group individually. We conducted a post-hoc analysis of the association between urine hippurate and KynA/Trp ratio. As a stability analysis, we repeated hypothesis-based analyses with the CS group divided into its component sugarcane harvest cutter and sugarcane seed cutter groups to determine whether differences exist between these two high-risk groups. We also repeated non-hypothesis-based analyses in the subgroup individuals with an eGFR ≥ 90 mL/min/1.73 m2. ## 2.4. Statistical Methods All metabolite concentrations were normalized to urine creatinine. Two extreme value outliers driven by very low urine creatinine were removed prior to analysis. Missing values were assumed to be below the threshold for detection by 1H NMR, and were imputed as $\frac{1}{5}$th the minimum positive value of that feature [31]. Metabolites with all concentration values below the threshold of detection were excluded from analysis. Comparisons between groups in non-hypothesis-based analyses were made using the false discovery rate (FDR) statistic to account for multiple comparisons. Metabolite concentrations were log-transformed and mean-centered divided by the standard deviation to achieve normal distribution prior to analysis. We performed supervised partial least squares discriminant analysis (PLS-DA) and a random forest analysis with out-of-bag (OOB) error calculation to determine how consistently patterns of metabolites were able to identify group alignment, and to determine important metabolites in creating this identifying pattern. PLS-DA models were validated using permutation tests based on the separation distance with 100 permutations. Significance cutoff for the non-hypothesis-based analysis was set as an FDR of <0.1 and, in the pathway analysis, with pathway impact of >0.1. Differences in NAD+-related metabolites and metabolite ratios, as well as the continuous normally-distributed baseline characteristics, were evaluated using Brown–Forsythe and Welch ANOVA with multiple comparisons with the p-value threshold set at 0.05. Categorical baseline characteristics were compared among groups using Fisher’s exact test. Urine specific gravity was compared among groups using the Kruskal–Wallis test with the p-value threshold set at 0.05. Urine hippurate was analyzed against KynA/Trp ratio using linear regression with the p-value threshold set at 0.05. One individual from Spain was excluded from the regression analysis as an outlier. Analyses were conducted using Metaboanalyst v. 5.0, Graphpad Prism v. 9, and R v. 4.1.0. ## 3. Results Demographic and laboratory features of each group are reported in Table 2. A total of 136 metabolites were identified by 1H NMR and are reported in Supplemental Table S1, with 78 metabolites included in the final analysis after excluding metabolites with >$50\%$ of values below the threshold for detection. ## 3.1. Non-Hypothesis-Based Explorations Comparisons in the urine metabolome across groups are shown in Figure 2. PLS-DA models used were all validated by permutation tests (Supplemental Figure S1). Random forest was able to correctly distinguish workers in the CS group and the OW group with $9\%$ ($\frac{11}{117}$ CS workers predicted to be OW) and $38\%$ ($\frac{30}{78}$ OW workers predicted to be CS) misclassification, respectively (overall OOB error $21\%$); the CS group and the SW group with $3\%$ and $8\%$ misclassification, respectively (overall OOB error $5\%$); and the CS group and the NW group with $10\%$ and $16\%$ misclassification, respectively (overall OOB error $13\%$). Metabolic pathways differing across all three comparisons with FDR < 0.1 and pathway impact >0.1 were phenylalanine, glyoxylate/dicarboxylate, and glycine/serine/threonine metabolism. Urinary creatinine-corrected hippurate was significantly higher in the CS group than in all other groups (mean mmol/mg creatinine [$95\%$ CI]: 0.85 [0.74, 0.96] in the CS group, 0.22 [0.18, 0.27] in the OW group, 0.22 [0.15, 0.28] in the SW group, 0.20 [0.18, 0.23] in the NW group; one-way ANOVA, FDR < 0.0001, $p \leq 0.0001$; Figure 3). Comparisons in the urine metabolome across groups when pooled by risk factor are shown in Figure 4. Random forest distinguished individuals residing in Nicaragua, designated as the high-risk region, and Spain, designated as the low-risk region, with <$1\%$ and $46\%$ misclassification, respectively (overall OOB error $10\%$); workers in high-intensity vs. lower intensity labor groups with $46\%$ and $4\%$ misclassification, respectively (overall OOB error $17\%$); and agricultural and non-agricultural workers with $1\%$ and $89\%$ misclassification, respectively (overall OOB error $25\%$). ## 3.2. Hypothesis-Based Explorations Levels of the metabolites NAD+, Trp, KynA, Nam, and MNA compared among groups are shown in Table 3. Comparison between the CS and OW and SW and NW groups reveals higher levels of NAD+ and KynA, although differences were not significant across all pairwise comparisons. Table 3 also shows relative levels of metabolites related to the de novo and salvage pathways of NAD+ metabolism. NAD+/Trp ratio was significantly higher in the CS group than in all other groups. KynA/Trp ratio was also higher in the CS group than in all other groups, although the difference was not significant in all pairwise comparisons. MNA/NAM ratio and NAD+/MNA ratio significantly differed among groups. NAD/MNA trended highest in the CS group, although it was significantly higher than only the OW group. Post-hoc, we analyzed the relationship between the urinary hippurate and Kyn/Trp ratio, which was significantly and positively correlated (log(KynA/Trp) = 0.205 * [log(Hip)] + 0.705, $95\%$ CI of slope = 0.119 to 0.291, $p \leq 0.0001$; Figure 5). ## 3.3. Stability Analyses Results of heatmaps and mean decrease accuracy assessment from random forest comparisons across groups are shown in Supplemental Figure S2 and corroborate patterns described here. When we compared metabolites related to NAD+ metabolism, along with hippurate, among occupational groups with sugarcane harvest cutters and seed cutters analyzed separately (Supplemental Table S2), seed cutters were either similar to harvest cutters or fell between harvest cutters and the lower-risk referent groups. When we repeated non-hypothesis based PLS-DA and pathway analyses in subset of individuals with an eGFR ≥ 90 mL/min/1.73 m2, findings were largely similar to the original analysis for the CS vs. OW and CS vs. NW comparisons (Supplemental Figure S3). In the CS vs. SW comparison, the list of important metabolites was also similar, but proline betaine replaced hippurate as the metabolite with the highest VIP score and betaine emerged as an important metabolite. ## 4. Discussion In this cross-sectional analysis of workers undertaking manual labor in Nicaragua and Spain, we observed that distinct urinary metabolic features distinguished our pre-specified high-risk group, Nicaraguan sugarcane harvest and seed cutters, from other occupational groups with respect to both the urinary metabolome as a whole and NAD+ metabolism in particular. One of the most striking differences between the high-risk CS group and other occupational groups was the degree of urinary hippurate elevation observed. Elevated hippurate may reflect increased gut permeability in the high-risk group. Prior study of the urine metabolome of heat-stressed goats demonstrated that elevated hippurate levels are a fundamental determinant of between-group differences, in conjunction with increases in other gut-related metabolites [32]. Our study also identified that increased levels of other gut-derived uremic metabolites, including 1-methylguanidine, 2-hydroxyphenylacetate, neopterin, and theobromine, were included among features important in distinguishing the CS group from referent groups. Elevated levels of these gut-related metabolites are in keeping with a proposed mechanism that increased gut permeability in response to heat stress may be a driver of MeN through increased inflammation [33]. Complementing these findings, in hypothesis-based analyses urinary KynA/Trp was increased in the CS group compared to referent groups, again consistent with a greater inflammatory state associated with high-risk work [18,34]. Prior studies have demonstrated increased Trp catabolism in association with intense exercise, with increased serum KynA/Trp ratio correlating with increased markers of inflammation [34,35,36]. Increased urinary values of KynA and KynA/Trp are observed in patients with AKI and are correlated with injury status [19]. The positive association observed between urinary hippurate and Kyn/Trp further supports the potential connection between increased gut permeability and inflammation in this population. Increased urinary hippurate could reflect other processes as well. Increased urinary hippurate is associated with increased renal blood flow [37]. Urinary hippurate is also affected by consumption of hippurate and its precursors. Of particular relevance to this study is bolis, the sugary rehydration packets sometimes used by sugarcane workers, that contain benzoic sodium which is metabolized to hippurate [38,39]. Benzoic sodium intake may also interact with Trp metabolism because it can be converted to anthranilic acid, an intermediary in the de novo pathway [38]. In our investigation of the NAD+ biosynthetic derangement, urinary NAD+ trended higher, rather than lower, in the high-risk CS occupational group, and urinary NAD+/Trp was increased rather than decreased. Unfortunately, the urinary Q/T ratio, a better validated marker of NAD+ biosynthetic derangement [10,11], was not calculable because quinolinate was not detected in the majority of specimens using our methodology. Moreover, NAD+ measurable in the urine has been shown to reflect extracellular immunomodulation rather than the altered intracellular energy metabolism characteristic of kidney injury [40,41]. Additionally, NAD+ can be sensitive to sample handling techniques, and measurement error may exist given specimens used in this study were not collected and processed specifically for NAD+ analysis. Further exploration of NAD+ biosynthetic derangement, including measurement of urinary quinolinate, is needed in populations at risk for MeN to draw any definitive conclusions regarding its role in disease pathogenesis. Patterns in TCA cycle intermediates, which tended to be lower in the CS group, further support the conclusion that NAD+ elevations in this study may not be a product of increased central energy metabolism. We observed decreased metabolites related to alanine/aspartate/glutamate metabolism, which is involved in the catabolism of proteins for energy generation by cellular mitochondria as an alternative input to the TCA cycle [42]. Similarly, glycine/serine/threonine metabolism and TCA—related metabolites themselves were generally decreased in the high-risk group. Creatine, which facilitates recycling of ATP, was also decreased in the high-risk group [43]. These findings are consistent with the overall impairment in central energy metabolism reported under states of injury and oxidative stress in the kidney [41]. TCA cycle components, such as citrate, 2-oxoglutarate, and fumarate are dicarboxylates, so decreased levels could alternatively reflect differences in sodium-dependent proximal tubular reabsorption, with increased sodium reabsorption associated with increased dicarboxylate reabsorption largely mediated through the sodium-dicarboxylate cotransporter NaDC1 [44]. Given MeN appears to be a tubulointerstitial kidney disease [2], further exploration of alterations in renal proximal tubular handling of metabolites in this population is merited. Analysis of the urine metabolome enabled us to distinguish the high-risk CS group from other groups with reasonable accuracy using random forest. This accuracy was generally lower when comparison groups were pooled to reflect shared risk based on region of residence, labor intensity, and work in agriculture. This suggests that metabolic elements defining the CS group are more distinct than metabolic elements defining any one shared risk factor. Increased hippurate as well as decreased TCA cycle intermediaries remained important features distinguishing groups, while features related to consumption, such as caffeine and proline betaine were key features distinguishing Spain and Nicaragua-based groups [45]. Overall, therefore, we were not able to make any strong conclusions about whether region of residence, labor intensity, or work in agriculture was the risk factor most likely to drive disease pathophysiology. Differences existed between the CS group and referent groups beyond the designed differences in work intensity, residence, and an agricultural work environment. These should be considered when assessing the findings presented here. The SW and NW groups were older on average than the CS group. Unlike for the CS group, specimens for the NW group were not universally collected at the end of a work day. The SW group also had worse kidney function on average than the CS group, and included more individuals with proteinuria and self-reported hypertension and fewer individuals with weekly NSAID use. Another important consideration in interpreting the results of this study is that differing urinary metabolite levels may result from alterations in metabolism, alterations in transport from intracellular to extracellular spaces, and alterations in the kidney’s handling of those metabolites, all of which we are unable to differentiate between due to our observational, cross-sectional design. We did not evaluate how strenuous each individual’s labor was on the day of specimen collection, and it likely differed among individuals within the same occupational groups, potentially blurring the distinction in intensity of manual labor among groups. All groups engaged in some amount of manual labor, further limiting differences in this exposure between comparators; the NW group was composed of brickmakers and miners, both occupational groups that are also considered to be at increased risk for MeN [26,27]. Participants were not fasting or on a standardized diet, and dietary differences are likely an unmeasured confounder contributing to metabolite differences between groups. Samples were spot, rather than 24-h, urine samples, which enables assessment of metabolism at a point in time of interest but which in turn requires correction for variation in urine concentration. In our study we standardized metabolites to urinary creatinine [46]. A concern could be that more intense work results in increased endogenous creatinine production from muscle breakdown, affecting the utility of creatinine as a standard, although labor appears not to significantly impact urinary creatinine excretion [47]. Additionally, participants were excluded who had elevated serum creatinine at the time of urine specimen collection, which should further minimize variation in daily creatinine excretion. Specimens analyzed were not freshly obtained but had been frozen at −80 °C for up to five years. Nevertheless, storage under these conditions has been shown to effectively maintain the integrity of urinary metabolites [48]. Sample sizes were relatively small and geographically limited, and may not reflect other populations at risk for MeN. Our findings suggest several areas for further exploration. These include future reevaluation of these study participants to determine who went on to develop chronic kidney disease, which can serve as a crucial additional comparison to understand whether certain metabolic features may either predispose to subsequent CKD development, or be biomarkers of early disease prior to decline in glomerular filtration rates. In addition, evaluating pre-, during-, and post-work specimens from high-risk groups would enable a more comprehensive determination of metabolic changes arising over the course of a work shift. ## 5. Conclusions Features in the urinary metabolome of Nicaraguan sugarcane harvest and seed cutters differentiated them from other groups of workers performing manual labor. A key distinguishing factor was their elevated levels of hippurate and other gut-derived uremic metabolites. 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--- title: PF127 Hydrogel-Based Delivery of Exosomal CTNNB1 from Mesenchymal Stem Cells Induces Osteogenic Differentiation during the Repair of Alveolar Bone Defects authors: - Longlong He - Qin Zhou - Hengwei Zhang - Ningbo Zhao - Lifan Liao journal: Nanomaterials year: 2023 pmcid: PMC10058633 doi: 10.3390/nano13061083 license: CC BY 4.0 --- # PF127 Hydrogel-Based Delivery of Exosomal CTNNB1 from Mesenchymal Stem Cells Induces Osteogenic Differentiation during the Repair of Alveolar Bone Defects ## Abstract Pluronic F127 (PF127) hydrogel has been highlighted as a promising biomaterial for bone regeneration, but the specific molecular mechanism remains largely unknown. Herein, we addressed this issue in a temperature-responsive PF127 hydrogel loaded with bone marrow mesenchymal stem cells (BMSCs)-derived exosomes (Exos) (PF127 hydrogel@BMSC-Exos) during alveolar bone regeneration. Genes enriched in BMSC-Exos and upregulated during the osteogenic differentiation of BMSCs and their downstream regulators were predicted by bioinformatics analyses. CTNNB1 was predicted to be the key gene of BMSC-Exos in the osteogenic differentiation of BMSCs, during which miR-146a-5p, IRAK1, and TRAF6 might be the downstream factors. Osteogenic differentiation was induced in BMSCs, in which ectopic expression of CTNNB1 was introduced and from which Exos were isolated. The CTNNB1-enriched PF127 hydrogel@BMSC-Exos were constructed and implanted into in vivo rat models of alveolar bone defects. In vitro experiment data showed that PF127 hydrogel@BMSC-Exos efficiently delivered CTNNB1 to BMSCs, which subsequently promoted the osteogenic differentiation of BMSCs, as evidenced by enhanced ALP staining intensity and activity, extracellular matrix mineralization ($p \leq 0.05$), and upregulated RUNX2 and OCN expression ($p \leq 0.05$). Functional experiments were conducted to examine the relationships among CTNNB1, microRNA (miR)-146a-5p, and IRAK1 and TRAF6. Mechanistically, CTNNB1 activated miR-146a-5p transcription to downregulate IRAK1 and TRAF6 ($p \leq 0.05$), which induced the osteogenic differentiation of BMSCs and facilitated alveolar bone regeneration in rats (increased new bone formation and elevated BV/TV ratio and BMD, all with $p \leq 0.05$). Collectively, CTNNB1-containing PF127 hydrogel@BMSC-Exos promote the osteogenic differentiation of BMSCs by regulating the miR-146a-5p/IRAK1/TRAF6 axis, thus inducing the repair of alveolar bone defects in rats. ## 1. Introduction The alveolar bone is defined as the component of the maxilla and mandible that provides support for the teeth, with undefined morphological changes and molecular mechanisms [1,2]. The disruption of “coupled” osteoclast–osteoblast actions by chronic periodontal inflammation can ultimately lead to alveolar bone destruction [3]. The regeneration of alveolar bone is pivotal for treating periodontal diseases [4]. Increasing attention has been paid to cell-based bone tissue engineering methods for reconstructing alveolar bone damage, which combines the use of stem cells and biocompatible scaffolds [5]. Hydrogels are known as water-swollen networks, formed from naturally derived or synthetic polymers, which hold a high potential for medical applications and play a crucial role in tissue repair and remodeling [6]. Reference [7] developed the supercritical gel drying of Ch/G mixtures to produce aerogels with improved structural organization and properties in regard to the starting single biopolymers [1,7]. In addition, reference [8] illustrated that the PTMC/PLA/HA and PTMC/HA scaffolds can be prepared utilizing PTMC/PLA/HA and PTMC/HA composite materials, respectively, via the biological 3D printing method and developed as potential biomaterials for bone repatriation and tissue engineering [8]. Nowadays, the thermo-responsive pluronic F127 (PF127) hydrogel has been highlighted to be effective in preserving alveolar bone, which can function as a local drug delivery system for clinical management of periodontitis and related pathologies [9]. It has been suggested that the use of mesenchymal stem cells (MSCs) can favor regeneration in experimental alveolar bone defects [10]. Bone marrow MSCs (BMSCs) are widely applied for bone regeneration because of their self-renewal and differentiating capacities into osteogenic or chondrogenic lineages [11]. Notably, the combination of BMSCs with PF127 was suggested as a promising novel approach to alveolar bone regeneration [12]. Exosomes (Exos) are identified as cell-secreted nanosized small extracellular vesicles (EVs) that can deliver bioactive substances to participate in physiological and pathological processes in the body [13]. A hydrogel loaded with BMSC-derived small EVs resulted in less alveolar bone loss to induce periodontal regeneration [14]. It should be noted that our bioinformatics analysis predicted beta-catenin (CTNNB1) as a pivotal gene both enriched in BMSC-Exos and upregulated in the osteogenic differentiation of BMSCs. As a multitasking and evolutionary conserved molecule, β-catenin (Armadillo in Drosophila) in metazoans plays a pivotal role in multiple developmental and homeostatic processes and functions as an important nuclear effector of canonical Wnt signaling in the nucleus [15]. Interestingly, upregulation of CTNNB1 by diosgenin could enhance bone formation to achieve anti-osteoporotic function [16]. CTNNB1, acting as a transcription factor, was reported to activate microRNA (miR)-146a transcription [17]. miR-146a-5p was identified as a key miR promoting osteogenic differentiation [18]. Human umbilical cord MSC-derived exosomal miR-146a-5p could repress the interleukin-1 receptor associated kinase 1 (IRAK1)/tumor necrosis factor (TNF) receptor associated factor 6 (TRAF6) axis to regulate neuroinflammation [19]. Of note, reference [20] demonstrated that more notable peri-implant bone loss and osteoclastogenesis were found in diabetic mice with glycemic fluctuation, and glycemic fluctuation could result in increases in the expression of IRAK1 and TRAF6 in peri-implant gingival tissues, which suggested that activation of the IRAK1/TRAF6 axis by glycemic fluctuation may contribute to the aggravation of bone loss [20]. Considering the aforementioned evidence, we proposed a hypothesis in this study that PF127 hydrogel loaded with BMSC-Exos (PF127 hydrogel@BMSC-Exos) overexpressing CTNNB1 might affect the repair of alveolar bone defects by regulating the miR-146a-5p-mediated IRAK1/TRAF6 axis (Figure 1). ## 2.1. Ethics Statement The current study was approved by the Animal Ethics Committee of our institute (protocol number: NO-SH1H-AE-20220127-012). Extensive efforts were made to minimize both the number of animals and their respective suffering in the experiments. ## 2.2. Bioinformatics Analysis Proteomics dataset PXD020948 related to human BMSC-Exos was obtained from the PRIDE partner database. Microarray GSE9451 (BMSCs group: $$n = 3$$; BMSCs osteogenesis group: $$n = 3$$) was obtained from the GEO database, with logFC > 1 and $p \leq 0.05$ used as screening criteria. Significantly upregulated genes were screened using the limma package in R language, and the heatmap was drawn using the pheatmap package in R language. Candidate genes were obtained using the jvenn tool. Protein interaction analysis of the candidate genes was performed in the STRING database and further imported into Cytoscape software (v3.8.2, National Institute of General Medical Sciences, Bethesda Softworks, Rockville, MD, USA) for visualization. The downstream target genes of miR-146a-5p were predicted using the miRDB, TargetScan, and DIANA TOOLS databases. ## 2.3. Culture of Rat BMSCs Rat BMSCs (R7500, ScienCell, Carlsbad, CA, USA) were cultured with proliferation medium (PM) containing DMEM (Gibco, Grand Island, NY, USA), $10\%$ (v/v) FBS, 100 U/mL penicillin G, and 100 mg/mL streptomycin (HyClone Company, Logan, UT, USA) in a $5\%$ CO2 incubator at 37 °C with $100\%$ relative humidity. In addition, BMSCs were seeded in a 6-well culture dish at the density of 2 × 104 cells/well. When the cell confluence reached $80\%$, cells were further cultured with PM supplemented with 5 mM β-glycerol phosphate (G9422, Sigma-Aldrich, St. Louis, MO, USA), 50 μg/mL ascorbic acid (BP461, Sigma-Aldrich, St. Louis, MO, USA), and 10 nM osteogenic medium (OM) containing dexamethasone for osteogenic induction. ## 2.4. Cell Grouping and Plasmid Transfection Plasmids were purchased from GenePharma (Shanghai, China). BMSCs were seeded in a 6-well plate, and 10 μL Lipofectamine™ 2000 (11068500, Invitrogen, Carlsbad, CA, USA) and 4 μg plasmids were diluted in 150 μL Opti-MEM (11058021, Thermo Fisher Scientific, Rockford, IL, USA) under $70\%$ cell confluence, followed by resting for 20 min and culture with $5\%$ CO2 at 37 °C. After 6 h of incubation, the cells were further cultured with complete medium for 48 h. Transfection efficiency was determined by RT-qPCR and Western blot analysis. Cells were transfected with overexpression vector of CTNNB1 (oe-CTNNB1), miR-146a-5p inhibitor, shRNA targeting IRAK1 (sh-IRAK1), and corresponding negative controls (NCs, oe-NC, inhibitor NC, or sh-NC) alone or in combination. The shRNA sequences are shown in Supplementary Table S1. ## 2.5. Isolation and Characterization of Exos from BMSCs Exos were isolated from the supernatant of BMSCs medium by differential centrifugation method [21]. Briefly, after incubation for 48 h in BMSCs medium containing Exos-free FBS, cell supernatants were collected and successively centrifuged at 800× g for 5 min to remove dead cells, at 1500× g for 15 min to remove cell debris, and at 15,000× g for 30 min to remove large EVs. The resulting supernatants were subsequently ultracentrifuged at 150,000× g for 2 h, followed by identification of purified Exos. The morphology of Exos was observed using a transmission electron microscope (TEM) (H-7650, HITACHI, Tokyo, Japan) [22]. The size of Exos was analyzed by nanoparticle tracking analysis (NTA) using a NanoSight LM10 instrument (NanoSight, Wiltshire, UK) [23]. Furthermore, the protein expression of Exos surface markers was assessed by Western blot analysis with such antibodies as rabbit polyclonal antibodies against TSG101 (ab125011, 1:1000, Abcam, Cambridge, UK), CD9 (CBL162, 1:500, Sigma-Aldrich, St. Louis, MO, USA) and Calnexin (ab133615, 1:1000, Abcam, Cambridge, UK) [24]. ## 2.6. Construction of Composite Material of Hydrogel Loading with Exos Pre-cooled PF-127 powder (P2443, Sigma-Aldrich, St. Louis, MO, USA) and 300 μg/mL of aforementioned BMSC-Exos suspension were mixed in a 1.5 mL centrifuge tube. The powder was fully dissolved by vortexing, followed by an ice bath and preservation in a 4 °C refrigerator. The centrifuge tube was checked for precipitation after 1 h. After the precipitation was completely dissolved, the complex of BMSC-Exos and PF-127 hydrogel, namely, PF127 hydrogel@BMSC-Exos, was finally generated. Since PF-127 has a unique temperature sensitivity, and its initial gelation temperature decreases with increasing concentration, we selected the appropriate concentration by determining the time required at both the initial gel temperature and 37 °C based on the 20–$32\%$ gradient concentration. At water bath temperature of 10 °C, the initial gelation temperature of PF127 hydrogel@BMSC-Exos solution at different concentrations ($10\%$, $24\%$, $28\%$, and $32\%$) was tested within the temperature range of 10–40 °C. The specific gelatinization time at 37 °C was determined with the concentration gradient of PF127 hydrogel@BMSC-Exos. The concentration was determined by adjusting another thermostat water bath to 37 °C and observing the specific gelation time of PF127 hydrogel@BMSC-Exos at 37 °C at different concentrations. ## 2.7. Uptake of Exos by BMSCs Exos were labeled with the PKH67 kit (MINI67-1KT, Sigma-Aldrich, St. Louis, MO, USA), in accordance with the instructions of the manufacturer, and restored at 4 °C for backup. Hydrogel at the above concentration was fully mixed with BMSC-Exos, and the mixture was stored at 4 °C. The BMSCs seeded in 12-well plates were treated with PF127 hydrogel, NC-Exos (BMSC-NC-Exos), PF127 hydrogel@BMSC-NC-Exos), or PF127 hydrogel@BMSC-Exos overexpressing CTNNB1 (PF127 hydrogel@BMSC-CTNNB1) and then cultured with $5\%$ CO2 in the incubator for 12 h. After nuclear staining with DAPI (1:1000, Beyotime, Beijing, China), images were captured using a fluorescence microscope. ## 2.8. Alkaline Phosphatase (ALP) Activity Assessment BMSCs were seeded in a 96-well plate at a density of 1 × 105 cells/well. After 7 d of PM or OM induction, ALP activity was measured at 405 nm using ALP detection kits (A059-3-1, Nanjing Jiancheng Bioengineering Institute, Nanjing, China). The ALP in the cells was also colorized using a color development kit. ## 2.9. Alizarin Red Staining The BMSCs were transferred to a 24-well plate at a density of 2 × 105 cells/well. At 14 d after PM or OM induction, Alizarin red staining was performed, in accordance with the protocol of the kit (A5533, Sigma-Aldrich, St. Louis, MO, USA). Alizarin red ($0.2\%$, pH = 8.3, Sigma-Aldrich) staining was performed for 10 min at 24–26 °C, and the matrix mineralization level was observed under an inverted microscope. To evaluate the concentration of calcium deposition, Alizarin red dye in BMSCs was extracted with 400 μL $10\%$ (w/v) sodium chloride solution in 10 mM sodium phosphate solution for 10 min, followed by quantification on a UV visible spectrometer at 562 nm. ## 2.10. Chromatin Immunoprecipitation (ChIP) Two CTNNB1 shRNA sequences were designed, and the one with optimal knockdown efficiency was selected by RT-qPCR for ChIP. The enrichment of CTNNB1 at the promoter region of miR-146a-5p was detected using the ChIP kit (KT101-02, Saicheng Biotech Co., Ltd., Guangzhou, China). Briefly, under cell confluence of 70–$80\%$, $1\%$ formaldehyde was added to fix the cells at room temperature for 10 min, and the intracellular DNA was crosslinked with protein. Sonication was performed to produce DNA fragments of 300–1000 bp. Immunoprecipitation was performed with the target protein-specific rabbit antibody against CTNNB1 (ab32572, 1:250, Abcam) and with Protein G Dynabeads (Invitrogen). The endogenous DNA–protein complex was precipitated using Protein Agarose/Sepharose, and the supernatant was aspirated after brief centrifugation. After de-crosslinking at 65 °C overnight, the DNA fragments were retrieved through phenol/chloroform purification for reverse transcription-quantitative polymerase chain reaction (RT-qPCR) detection of the miR-146a-5p gene promoter fragment. The primer sequences specific for the promoter region of miR-146a-5p are shown in Supplementary Table S2. ## 2.11. Dual-Luciferase Reporter Gene Assay The binding sites of miR-146a-5p to IRAK1 and TRAF6 were predicted through an online database. The gene fragment of the 3′UTR region of IRAK1 was subjected to clonal amplification, and the PCR product was cloned into pmirGLO (E1330, Promega, Madison, WI, USA) at the polyclonal sites downstream of the luciferase gene (luc2) and named pIRAK1-WT (AGUUCUC). Site-directed mutagenesis was performed on the binding site between miR-146a-5p, and the target genes were predicted through bioinformatics analysis, followed by construction of the pIRAK1-MUT (UCAAGAG) vector. The steps were also applicable for TRAF6. miR-146a-5p mimic and NC were co-transfected with the luciferase reporter vector into human embryonic kidney HEK293T cells (iCell-h237, iCell Bioscience Inc., Shanghai, China). Using a luciferase assay kit (E1900, Promega, Madison, WI, USA), luciferase activity, as normalized to renilla luciferase, was detected by dual-luciferase reporter gene assay system (Dual-Luciferase® Reporter Assay System, E1910, Promega, Madison, WI, USA). ## 2.12. RT-qPCR Trizol (16096020, Invitrogen) was used for total cellular RNA extraction. For mRNA detection, a reverse transcription kit (11483188001, Roche, Basel, Switzerland) was used to obtain cDNA. For miRNA, a Polyad tailing kit (B532451, Sangon, Shanghai, China) was used to obtain the cDNA of miRNA containing PolyA tail. The PCR was carried out using the LightCycler 480 SYBR Green I Master. With GAPDH and U6 as the internal references of mRNA and miRNA, respectively, 2−ΔΔCt method was adopted for quantitative analysis for gene expression. The primer sequences are shown in Supplementary Table S3. ## 2.13. Western Blot Analysis Total protein of tissue or cells was extracted from a high-efficiency RIPA lysis buffer (Sigma Aldrich) containing $1\%$ protease inhibitor and $1\%$ phosphorylase inhibitor (Beyotime, Shanghai, China). Concentration of the extracted protein was determined using a BCA kit (Thermo Fisher Scientific, Waltham, MA, USA). The proteins were separated by polyacrylamide gel electrophoresis, then transferred to PVDF membranes (Millipore, Billerica, MA), and blocked with $5\%$ BSA for 1 h at room temperature. The membranes were incubated with rabbit anti-mouse primary antibodies against CTNNB1 (1:500, ab68183, Abcam) and GAPDH (1:500, ab8245, Abcam) at 4 °C overnight. The next day, the membranes were further incubated with horseradish peroxidase-labeled goat anti-rabbit IgG (1:20,000, ab205718, Abcam) or goat anti-mouse IgG (1:20,000, ab197767, Abcam) diluent for 1.5 h at room temperature, followed by development using developing solution (NCI4106, Pierce, Rockford, IL, USA). Protein quantification analysis was performed by ImageJ 1.48 u software (2014, Bio-Rad Laboratories, Hercules, CA, USA) with an internal reference GAPDH. ## 2.14. Rat Model of Alveolar Bone Defects and In Vivo Experiment Protocols In total, 48 male Wistar rats (6 weeks old, Vital River Laboratory Animal Technology Co., Ltd., Beijing, China) were raised under SPF environment, with laboratory humidity of 60–$65\%$, temperature of 22–25 °C, and free access to food and water under 12 h light/dark cycles. The experiment was started after the rats were acclimatized for one week. After general anesthesia in rats, the alveolar bone was exposed by medical incision, and the model of alveolar bone defects was established in the second mandible molar (length: 3 mm; width: 1.5 mm; depth 1.5 mm) [25]. PKH26 was used to label Exos. Except for the rats without any treatment in the blank group, the alveolar bone defects of model rats were implanted with scaffolds of PF127 hydrogel, PF127 hydrogel@BMSC-NC-Exos (PF127 hydrogel loaded with BMSC-NC-Exos), or PF127 hydrogel@BMSC-CTNNB1-Exos (PF127 hydrogel loaded with BMSC-Exos containing CTNNB1). Rats were sacrificed with CO2 asphyxiation at 8 weeks after surgery, with the entire alveolar removed for micro-CT scanning. All specimens were fixed with $4\%$ paraformaldehyde solution for 48 h. ## 2.15. Two-Photon Excited Fluorescence (TPEF) Imaging To check the defect site for the presence of Exos, we randomly anesthetized three rats on day 3, day 14, day 28, and day 56 after the PF127 hydrogel@BMSC-Exos implantation. Next, we collected the alveolar bone tissue specimens from the implant site, and fluorescence was collected using the TPEF (Ni-E-A1RMP) superimposed scanning method with a 14 laser at wavelength of 1080 nm for PKH26 imaging. Finally, the signal intensities were analyzed using Image J software. ## 2.16. Immunohistochemistry After antigen retrieval and normal goat serum blocking, the sections of rat alveolar bone tissues were incubated at 4 °C overnight with rabbit anti-mouse primary antibodies against RUNX2 (SAB1403638, 1:500, Sigma-Aldrich, St. Louis, MO, USA), OCN (AB10911, 1:500, Sigma-Aldrich), IRAK1 (SAB4504245, 1:200, Sigma-Aldrich, St. Louis, MO, USA), and TRAF6 (ab137452, 1:100, Abcam). The next day, the sections were incubated with goat anti-rabbit IgG (ab6721, 1:1000, Abcam) at 37 °C for 20 min and then with horseradish peroxidase-labeled streptomyces ovalbumin working solution (Imunbio, Beijing, China) at 37 °C for 20 min, followed by DAB (Whiga, Guangzhou, China) color development. Hematoxylin (Shanghai Bogoo Biological Technology Co., Ltd., Shanghai, China) was applied for counterstaining the sections. Images were finally observed and photographed under a microscope. ## 2.17. Micro-CT Scanning of Newly Formed Bone Tissue Newly formed bone tissue at the rat alveolar bone defect was detected using a micro-CT scanner (SCANCO μCT50, Muttenz, Switzerland). Mimics software (Mimics 17.0, 2017, Materialise, Leuven, Belgium) was used to obtain 3D images and to calculate the bone mineral density (BMD) of the new bone-like tissue, and the relative trabecular bone volume [(bone volume (BV)/tissue volume (TV)] represented by the ratio between bone surface area and TV. ## 2.18. Statistical Analysis Statistical analysis of the study data was performed using SPSS 21. 0 (IBM Corp. Armonk, NY, USA). Measurement data were expressed as mean ± standard deviation. Firstly, normality and homogeneity of variance were tested. Data between two groups obeying normal distribution and homogeneity of variance were compared with unpaired t-tests and those among multiple groups were compared by one-way ANOVA or repeated measures of ANOVA at different timepoints, followed by Tukey’s post hoc test. $p \leq 0.05$ indicated a statistically significant difference. ## 3. Results and Discussion MSCs are widely used in bone tissue engineering due to their multipotential differentiation ability [26]. In recent years, increasing evidence has shown that transplanted MSCs exert their therapeutic effects through paracrine cytokines, rather than through direct cellular replacement, with Exos playing an important role [27]. The application potential of BMSC-Exos in bone regeneration was demonstrated by several studies, but the specific molecular mechanisms remain unclear [28,29]. Therefore, this study aimed to screen out BMSC-Exos-regulated key molecules in promoting bone regeneration and to further explore the downstream molecular mechanisms. The PF-127-containing scaffold is a promising candidate to accelerate bone tissue growth into the porous scaffold with good biocompatibility, which can provide a selection for bone regeneration in bone defects in the dental field [30]. Understanding the molecular mechanisms underlying the effect of PF127 hydrogel loaded with BMSC-Exos on bone regeneration provides novel strategies for alveolar bone defects. ## 3.1. CTNNB1 Might Be the Key Gene for BMSC-Exos to Promote the Differentiation of BMSCs into Osteoblasts We retrieved proteomic data related to BMSC-Exos through the PRIDE partner database and obtained the PXD020948 project, which used ultracentrifugation to isolate Exos from MSCs and detect proteins using a marker-free method. Next, we extracted 771 BMSC-Exos-contained proteins in this project. In addition, the osteogenic differentiation of BMSCs-related expression profile data was retrieved through the GEO database, and the GSE9451 dataset was downloaded; 1151 genes significantly upregulated in the osteogenic differentiation of BMSCs were then screened using logFC > 1 and $p \leq 0.05$ as the thresholds (Figure 2A,B). The results from the PXD020948 and GSE9451 datasets were further intersected to obtain 54 intersecting genes (Figure 2C). The above intersecting genes were imported into the STRING database for protein interaction analysis and visualization and were sorted according to the number of intergenic connections (Degree value), which found that CTNNB1 ranked first (Figure 2D,E). In addition, evidence existed reporting that upregulated CTNNB1 expression promotes the osteogenic differentiation of MSCs [31,32]. Therefore, we speculated that CTNNB1 might be a key gene for BMSC-Exos in promoting the differentiation of BMSCs to osteoblasts. ## 3.2. Characterization of BMSC−CTNNB1−Exos To explore the role of CTNNB1 in promoting bone regeneration by BMSC-Exos, we first constructed BMSCs with stable overexpression of CTNNB1. The transfection efficiency of CTNNB1 was verified by RT-qPCR and Western blot analysis (Figure 3A,B). The BMSC-NC-Exos and BMSC-CTNNB1-Exos extracted by overspeed centrifugation showed typical cup morphology (Figure 3C). NTA found that the sizes of MSC-NC-Exos and BMSC-CTNNB1-Exos were mainly around 105 nm (Figure 3D), consistent with the diameters of Exos that were previously reported [33,34]. In addition, Western blot analysis found positive expression of TSG101 and CD9 on the surface of MSC-NC-Exos and BMSC-CTNNB1-Exos, while the calnexin was hardly expressed, indicating successful isolation of Exos (Figure 3E). The Western blot analysis results showed that the expression of CTNNB1 was significantly increased after co-culture with BMSC-CTNNB1-Exos (Figure 3F), demonstrating that BMSC-CTNNB1-Exos with high CTNNB1 expression were successfully obtained. ## 3.3. PF127 Hydrogel Loaded with BMSC-Exos Efficiently Delivered CTNNB1 to BMSCs Despite the great potential of MSC-derived Exos for therapeutic administration, there remains the problem of its low delivery efficiency and limited use in clinical research. In recent years, several strategies to promote the release of Exos have been developed, among which the loading of Exos by hydrogel is a safe and effective new treatment method [35]. PF-127 has a unique thermal sensitivity, in that it exists as a liquid at low temperatures and as a semi-solid gel at high temperatures [36]. For example, PF-127, which could gelate within a short response time and control drug release, was suggested as a novel approach for treating chronic periodontitis [37]. Due to this reversible thermal response behavior, PF-127 is able to adapt to a complex trauma environment, enabling the bioactive agent to adhere to the target and exert its biological effects [33]. Therefore, we attempted to load the BMSC-Exos with PF127 to form a complex, namely, PF127 hydrogel@BMSC-Exos. The temperature sensitivity results showed that the initial gelation temperature of PF127 hydrogel@BMSC-Exos decreased as the PF127 concentration increased. Moreover, $20\%$ PF127 hydrogel@BMSC-Exos composite was initially gelated at 18.1 °C, and $32\%$ PF127 hydrogel@BMSC-Exos composite was initially gelated at 12.0 °C. Inversely proportional to the concentration, the gelation time of the $8\%$ composite was only slightly different from that of the $32\%$ composite at 37 °C. Therefore, we chose the $28\%$ PF127 hydrogel@BMSC-Exos composite, which was liquid at 4 °C, was in a semi-solid colloid state at 37 °C, and could be gelated at 37 °C in about 43 s. An increasing number of studies have reported the role of BMSC-derived Exos in bone repair or regeneration [28,29]. Exos from human gingiva-derived MSCs treated with TNF-α were reported to result in the inhibition of periodontal bone loss [38]. Exos secreted by human exfoliated deciduous teeth-derived stem cells could promote the repair of alveolar bone defects partially by regulating osteogenesis [39]. BMSC-derived small EVs hydrogel facilitated periodontal regeneration, as evidenced by the resultant less alveolar bone loss [14]. Intriguingly, a bioglass scaffold loaded with MSCs could facilitate alveolar bone repair in rhesus monkeys [40]. Simvastatin-loaded PF127 hydrogel had therapeutic efficacy on periodontal bone preservation in rats with ligature-induced periodontitis [41]. Subsequently, as observed by scanning electron microscopy (SEM), the loading of CTNNB1 did not significantly alter the morphology of PF127 hydrogel@BMSC-Exos, suggesting a relatively stable morphology of PF127 hydrogel@BMSC-Exos (Figure 4A). In addition, for further detection of the long-term stability of PF127 hydrogel@BMSC-CTNNB1-Exos and PF127 hydrogel@BMSC-Exos, we observed the morphological changes in the two after storage at −80 °C for 15 days and 30 days by SEM (Supplementary Figure S1). The results showed that both PF127 hydrogel@BMSC-CTNNB1-Exos and PF127 hydrogel@BMSC-Exos maintained a good morphology at 30 days, which did not differ significantly from the morphology on the first day. The above results confirmed the good stability of the prepared PF127 hydrogel@BMSC-CTNNB1-Exos and PF127 hydrogel@BMSC-Exos. To observe the uptake of PF127 hydrogel@BMSC-Exos by BMSCs, we used PKH67 (green fluorescence)-labeled Exos, with PF127 hydrogel as an NC and BMSC-Exos as a positive control. After 12 h of incubation with BMSCs, green fluorescence was shown in the presence of BMSCs but was not detected in response to PF127 hydrogel in the absence of BMSCs, suggesting the existence of Exos signal in the cytoplasm and the enrichment of it in the nucleus. Moreover, PF127 hydrogel brought about more enriched PKH67 green fluorescence in the presence of BMSC-NC-Exos or BMSC-CTNNB1-Exos (Figure 4B). These data suggest that the loading of Exos by PF127 hydrogel increased the uptake of Exos by BMSCs at the same concentration of Exos. The Western blot analysis results revealed that the expression of CTNNB1 in response to PF127 hydrogel@BMSC-NC-Exos or PF127 hydrogel@BMSC-CTNNB1-Exos was significantly increased when compared with that after treatment with PF127 hydrogel. The CTNNB1 expression was also notably elevated by PF127 hydrogel@BMSC-NC-Exos. The upregulation of CTNNB1 was particularly significant in the presence of PF127 hydrogel@BMSC-CTNNB1-Exos (Figure 4C,D). Collectively, PF127 hydrogel loaded with BMSC-Exos could better deliver the CTNNB1 to the BMSCs. ## 3.4. PF127 Hydrogel Loaded with BMSC-CTNNB1-Exos Promoted the Osteogenic Differentiation of BMSCs Next, we further evaluated the effect of PF127 hydrogel-loaded BMSC-CTNNB1-Exos on the osteogenic differentiation of BMSCs. ALP staining (Figure 5A), Alizarin red staining (Figure 5B), and RT-qPCR (Figure 5C,D) illustrated that in both the PM and the OM, BMSC-NC-Exos or BMSC-CTNNB1-Exos enhanced ALP staining intensity and activity and extracellular matrix mineralization based on PF127 hydrogel treatment, accompanied by upregulated RUNX2 and OCN expression. The application of PF127 hydrogel augmented the ALP staining intensity and activity and extracellular matrix mineralization, while upregulating RUNX2 and OCN expression in BMSCs co-cultured with Exos, whether carrying CTNNB1 or not. This might be attributed to the elevated release of Exos by PF127 hydrogel. Compared to PF127 hydrogel@BMSC-NC-Exos, PF127 hydrogel@BMSC-CTNNB1-Exos resulted in increases in ALP staining intensity and activity and extracellular matrix mineralization of BMSCs as well as increases in RUNX2 and OCN expression. The changes in the above indicators were found to be more significant in the OM, indicating that overexpression of CTNNB1 significantly increased the osteogenic differentiation of BMSCs (Figure 5A–D). Therefore, PF127 hydrogel loaded with BMSC-CTNNB1-Exos could induce the osteogenic differentiation of BMSCs. The increased expression of CTNNB1 by diosgenin could augment bone formation to exert anti-osteoporotic function [16]. CTNNB1 signaling regulated by iPTH enhanced osteoblastic differentiation to diminish alveolar bone loss during orthodontic tooth movement in a rat model of periodontitis [42]. The activated Wnt/CTNNB1 pathway by human amnion-derived MSCs promoted the osteogenic differentiation of BMSCs [43]. These studies concur with our finding regarding the role of CTNNB1 in the osteogenic differentiation of BMSCs and repair of alveolar bone defects; however, they failed to explore the related downstream regulatory mechanism of CTNNB1. ## 3.5. CTNNB1 Activated the Transcription of miR-146a-5p and Further Targeted Inhibited IRAK1 and TRAF6 during Osteogenic Differentiation of BMSCs CTNNB1, which functions as a transcription factor, was suggested to activate the transcription of miR-146a [17]. It was also reported that miR-146a-5p is involved in the osteogenic differentiation of MSCs [18]. We designed two CTNNB1 shRNA sequences, and sh-CTNNB1-2 with optimal knockdown efficiency as determined by RT-qPCR was used for the subsequent ChIP assay (Supplementary Figure S2A). The ChIP results showed that the enrichment of CTNNB1 at the miR-146a-5p promoter region was significantly reduced after CTNNB1 knockdown (Figure 6A). The RT-qPCR results displayed that the expression of CTNNB1 and miR-146a-5p gradually increased on day 0, 7, and 14 (Figure 6B). Moreover, CTNNB1 and miR-146a-5p expression was upregulated by treatment with oe-CTNNB1 (Figure 6H). The above results indicated that CTNNB1 might act as a transcription factor to activate the transcription of miR-146a-5p and then promote its expression during the osteogenic differentiation of BMSCs. We further explored the downstream pathway of miR-146a-5p and predicted the downstream target genes of miR-146a-5p using the miRDB (Target Score ≥ 90), TargetScan (Total context++ score ≤ −0.30), and DIANA TOOLS (miTG score ≥ 0.95) databases. The results of the three databases were intersected, obtaining 10 genes (TRAF6, IRAK1, ZBTB2, SLC10A3, CD80, EIF4G2, SIAH2, SEC23IP, BCORL1, and WWC2) (Figure 6C). Among them, only IRAK1 and TRAF6 had significantly differential expression during the osteogenic differentiation of BMSCs, both with a trend of gradual decrease (Figure 6D). Evidence was previously demonstrated suggesting that BMSC-Exos-derived miRNA delays the development of the intervertebral disc degeneration by targeting TRAF6 [44]. Another prior study indicated that miR-146a-5p overexpression inhibited the IRAK1/TRAF6/NF-κB pathway in acute pancreatitis [45]. miR-146a-5p could simultaneously target IRAK1 and TRAF6 to inhibit their expression [19], but its role in the osteogenic differentiation of BMSCs has been rarely explored. According to the specific binding sites predicted by the TargetScan database (Figure 6E), the targeted binding relationships between miR-146a-5p and IRAK1 and between miR-146a-5p and TRAF6 were further verified by a dual-luciferase reporter gene assay. The results revealed that miR-146a-5p had a relatively good targeting relationship with IRAK1 and TRAF6 (Figure 6F,G, respectively). Thus, we propose that miR-146a-5p may specifically inhibit both IRAK1 and TRAF6 expression during the osteogenic differentiation of BMSCs. To elucidate the regulatory relationship of the CTNNB1-miR-146a-5p/IRAK1/TRAF6 signaling axis during the osteogenic differentiation of BMSCs, we interfered CTNNB1 and miR-146a-5p expression in BMSCs and examined the downstream factor expression changes by RT-qPCR. The results showed that the expression of IRAK1 and TRAF6 was significantly downregulated in the presence of CTNNB1 overexpression; additional treatment with miR-146a-5p inhibitor failed to alter CTNNB1 expression but diminished the expression of miR-146a-5p while upregulating that of IRAK1 and TRAF6 (Figure 6H), indicating that the knockdown of miR-146a-5p expression restored the inhibition of IRAK1 and TRAF6 expression by CTNNB1 overexpression. Collectively, both CTNNB1 and miR-146a-5p were upregulated, while IRAK1 and TRAF6 were downregulated, during the osteogenic differentiation of BMSCs. CTNNB1 might further target and inhibit the expression of IRAK1 and TRAF6 by activating the transcription of miR-146a-5p. ## 3.6. CTNNB1 Induced the Osteogenic Differentiation of BMSCs by Regulating the miR-146a-5p/IRAK1/TRAF6 Axis We then explored whether CTNNB1 promoted the osteogenic differentiation of BMSCs through the subsequent targeted inhibition of IRAK1 and TRAF6 expression by activating the transcription of miR-146a-5p. Two different shRNA sequences, targeting IRAK1 and TRAF6, respectively, were designed, with sh-IRAK1-1 and sh-TRAF6-2 showing optimal knockdown results by RT-qPCR (Supplementary Figure S2B,C) and, thus, being selected for further analyses. The ALP staining (Figure 7A), Alizarin red staining (Figure 7B), and RT-qPCR (Figure 7C,D) results showed that, in both PM and OM, overexpression of CTNNB1 led to enhanced ALP activity and extracellular matrix mineralization, accompanied by upregulated RUNX2 and OCN, indicating that overexpression of CTNNB1 induced the osteogenic differentiation of BMSCs. In contrast to CTNNB1 overexpression alone, CTNNB1 overexpression combined with miR-146a-5p inhibition contributed to notably reduced ALP activity and extracellular matrix mineralization and downregulated RUNX2 and OCN expression, suggesting that knockdown of miR-146a-5p could restore the induction of the osteogenic differentiation of BMSCs by CTNNB1 overexpression. Moreover, additional knockdown of IRAK1/TRAF6 restored the inhibitory effect of knockdown of miR-146a-5p on the osteogenic differentiation of BMSCs, as evidenced by the increased ALP activity and extracellular matrix mineralization and upregulated RUNX2 and OCN expression vs. those in response to CTNNB1 overexpression combined with miR-146a-5p inhibition (Figure 7A–D). The above results suggested that CTNNB1 might activate the transcription of miR-146a-5p and then inhibit IRAK1 and TRAF6 expression, ultimately promoting the osteogenic differentiation of BMSCs. ## 3.7. PF127 Hydrogel Loaded with BMSC-CTNNB1-Exos Induced Alveolar Bone Regeneration in Rats We have already confirmed that PF127 hydrogel loaded with BMSC-CTNNB1-Exos had a good temperature sensitivity and release efficiency and could significantly promote the osteogenic differentiation of BMSCs. Therefore, we further explored the role of PF127 hydrogel loaded with BMSC-CTNNB1-Exos in the repair of alveolar bone defects in rats. We successfully constructed a rat model of alveolar bone defects. First, we implanted PKH26-labeled PF127 hydrogel@BMSC-Exos into the defect site. The in vivo TPEF imaging results showed that the Exos were distributed in the defect site 3 d after PF127 hydrogel implantation and lasted for at least 14 d (Figure 8A), demonstrating a good implantation effect. The micro-CT scanning images and the quantitative results showed no significant difference in the new bone formation, BV/TV ratio, or BMD after treatment with PF127 hydrogel. In contrast to PF127 hydrogel, PF127 hydrogel@BMSC-NC-Exos led to increased new bone formation, accompanied by an elevated BV/TV ratio and BMD, which could be further elevated in the presence of CTNNB1 overexpression (Figure 8B). In addition, the immunohistochemical staining results showed no significant difference in the positive expression of RUNX2, OCN, IRAK1, and TRAF6 after treatment with PF127 hydrogel. In contrast, treatment with PF127 hydrogel@BMSC-NC-Exos resulted in a higher staining particle range and intensity for RUNX2 and OCN around the nucleus and within the cytoplasm of the osteoblasts, while IRAK1 and TRAF6 displayed lower intensity; these effects could be furthered in response to additional CTNNB1 overexpression (Figure 8C). Therefore, PF127 hydrogel loaded with BMSC-CTNNB1-Exos could induce alveolar bone regeneration and promote the repair of alveolar bone defects in rats, which might be related to the downregulation of the downstream genes IRAK1 and TRAF6. CTNNB1, serving as a transcription factor, was previously revealed to activate miR-146a transcription [17]. Furthermore, overexpression of miR-146-5p activated Wnt/β-catenin in lung cancer cells [46]. As previously reported, the osteogenic Exos secreted by MSCs could deliver upregulated hsa-miR-146a-5p to induce osteogenic differentiation, presenting the potential of being applied in a bone regeneration strategy [47]. In addition, overexpression of miR-146a-5p could accelerate the osteogenic differentiation of human placenta-derived MSCs, which may improve the osteogenic efficacy in bone defect repair using scaffold materials [48]. Exosomal miR-146a-5p from human urine-derived stem cells could target and downregulate IRAK1 to alleviate renal ischemia/reperfusion injury in rats [49]. Moreover, miR-146a-5p delivered by human umbilical cord MSCs repressed TRAF6 signaling to augment protection against rat diabetic nephropathy via M2 macrophage polarization [50]. Of note, previous research also unfolded the involvement of the IRAK1-TRAF6 in bone-related diseases. For instance, the activated TLR$\frac{2}{4}$-IRAK1/TRAF6 axis due to glycemic fluctuation aggravated bone loss [20]. Additionally, TRAF6 inhibition by treatment with astragalus polysaccharide aided in protecting the alveolar bone, which is involved with the decline in local osteoclasts [51]. Therefore, it is suggested in our study that CTNNB1 activated the transcription of miR-146a-5p and then downregulated the expression of IRAK1 and TRAF6 during the osteogenic differentiation of BMSCs. ## 4. Conclusions To conclude, this study demonstrated that CTNNB1 overexpression inhibits IRAK1 and TRAF6 expression by activating miR-146a-5p transcription, which makes it possible for PF127 hydrogel loaded with BMSC-CTNNB1-Exos to promote the osteogenic differentiation of BMSCs, thereby facilitating the repair of alveolar bone defects in rats (Figure 1). This finding may provide a promising technical means for the repair of alveolar bone defects and further the understanding of the molecular mechanism of alveolar bone regeneration. 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--- title: 'Shared Genes of PPARG and NOS2 in Alzheimer’s Disease and Ulcerative Colitis Drive Macrophages and Microglia Polarization: Evidence from Bioinformatics Analysis and Following Validation' authors: - Longcong Dong - Yuan Shen - Hongying Li - Ruibin Zhang - Shuguang Yu - Qiaofeng Wu journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10058634 doi: 10.3390/ijms24065651 license: CC BY 4.0 --- # Shared Genes of PPARG and NOS2 in Alzheimer’s Disease and Ulcerative Colitis Drive Macrophages and Microglia Polarization: Evidence from Bioinformatics Analysis and Following Validation ## Abstract Emerging evidence shows that peripheral systemic inflammation, such as inflammatory bowel disease (IBD), has a close even interaction with central nervous disorders such as Alzheimer’s disease (AD). This study is designed to further clarify the relationship between AD and ulcerative colitis (UC, a subclass of IBD). The GEO database was used to download gene expression profiles for AD (GSE5281) and UC (GSE47908). Bioinformatics analysis included GSEA, KEGG pathway, Gene Ontology (GO), WikiPathways, PPI network, and hub gene identification. After screening the shared genes, qRT-PCR, Western blot, and immunofluorescence were used to verify the reliability of the dataset and further confirm the shared genes. GSEA, KEGG, GO, and WikiPathways suggested that PPARG and NOS2 were identified as shared genes and hub genes by cytoHubba in AD and UC and further validated via qRT-PCR and Western blot. Our work identified PPARG and NOS2 are shared genes of AD and UC. They drive macrophages and microglia heterogeneous polarization, which may be potential targets for treating neural dysfunction induced by systemic inflammation and vice versa. ## 1. Introduction Nowadays, more and more evidence shows the importance of communication between the gut and the central nervous system through the brain–gut axis. For example, inflammatory bowel disease (IBD) is a peripheral inflammatory disease that can lead to mental disorders and cognitive disorders, showing symptoms similar to Alzheimer’s disease (AD) and Parkinson’s disease (PD) [1,2,3,4,5] and even affect the hippocampal neurogenesis of the brain [6]. In a longitudinal study, it was found that there was a significant correlation between IBD and the subsequent development of dementia [7], which was consistent with the results of another Danish national cohort study from 1977 to 2018, which revealed the potential role of the gut in the development of AD [8]. On the other hand, in patients with IBD, dementia is usually diagnosed at an early stage, and the risk of the disease seems to increase with the chronicity of IBD [7]. For example, a national population-based cohort study showed that the risk of neurodegenerative diseases in IBD patients was higher than that in non-IBD patients [9]. Therefore, it is necessary to study the relationship between IBD and dementia. AD usually impairs cognition, memory, and language. The causes of AD including pathologically amyloid-β (Aβ) accumulation, neurofibrillary tangle formation, extensive neuroinflammation, synaptic toxicity, neurodegeneration, and brain dysfunction [10,11]. It is a progressive neurodegenerative disorder, with increased incidence worldwide, imposing significant economic and social burdens [12,13]. Recently, it has been discovered that AD pathogenesis and progression were influenced by immune system processes because of the genetic overlap between AD and immune-mediated diseases [14,15]. IBD, including Crohn’s disease (CD) and ulcerative colitis (UC), is characterized by abnormal immune control and the imbalance of gut microbiota [8,16,17]. Evidence shows that AD and IBD may have common pathological changes and interrelated. Our previous studies also demonstrated that in the cerebral cortex and hippocampus of dextran sulfate sodium salt (DSS)-induced colitis model mice, the activities of astrocyte and microglia have changed significantly, and the secretion of cytokines and hormones of the HPA axis abnormally changed, indicating that peripheral inflammation is significantly related to the abnormalities of the central nervous system [18,19]. However, the exact association mechanism between AD and IBD is still unclear. In recent years, advances in sequencing technology and bioinformatics have enabled us to explore the pathogenesis of disease–disease interaction at the genetic level [20]. In our study, the published gene expression data from the GEO was used to identify the common differential expression genes (co-DEGs) in AD and UC. Bioinformatics Analysis (GSEA, GO analysis, WikiPathways analysis, PPI network analysis, and cytoHubba.) revealed peroxisome proliferator-activated receptor gamma (PPARG) and nitric oxide synthase 2 (NOS2) presented a high relationship between AD and UC. Then, the result was verified in APP/PS1 mice for AD and DSS-induced mice for UC, which improved the credibility of the hypothesis. The shared gene signatures identified here between AD and UC are expected to provide new insights into the biological mechanisms of disease association. ## 2.1.1. GSEA Analysis in AD and UC The GSEA KEGG pathway analysis showed that 50 pathways achieved statistically significant enrichment in AD, and 71 pathways achieved statistically significant enrichment in UC (Figure S1a,b). We further screened for the KEGG pathways with consistent trends in AD and UC, and 21 common pathways were found (Table S1). In the category of KEGG, metabolism accounted for the most significant proportion ($52.38\%$, $\frac{11}{21}$), during Human Diseases and Organismal Systems accounted for $14.29\%$ (Figure S1c). Interestingly, it was found that in “Human Diseases”, “Alzheimer’s disease”, “Parkinson’s disease”, and “Huntington’s disease” were significantly enriched, which belong to neurodegenerative diseases (Figure 1a,b). The categories of KEGG Metabolism include “Fatty acid metabolism”, “Phenylalanine metabolism”, “Arginine and proline metabolism”, “Valine, leucine and isoleucine degradation”, “Propanoate metabolism”, “Butanoate metabolism”, “Glycolysis/Gluconeogenesis”, “Citrate cycle (TCA cycle)”, “Pyruvate metabolism”, “Oxidative phosphorylation”, and “Terpenoid backbone biosynthesis” (Figure 1c–h). ## 2.1.2. Identified Co-DEGs in AD and UC Based on GSE5281, 2639 DEGs (1772 upregulated DEGs and 867 downregulated DEGs) were identified between AD patients and healthy controls (Figure 2a,b). Moreover, there were 735 DEGs identified between UC patients and healthy controls based on GSE47908 (479 upregulated DEGs, and 256 downregulated DEGs) (Figure 2c,d). Finally, we identified 61 co-DEGs with consistent trends in AD and UC ($p \leq 0.001$ using Fisher’s exact test) (Figure 2e). ## 2.1.3. Enrichment Analysis in Co-DEGs To further investigate the biofunctions of co-DEGs, GO and WikiPathways enrichment analysis was performed. For this set, the top 10 enriched BP GO terms were “Cell activation”, “Defense response”, “Leukocyte mediated immunity”, “Inflammatory response”, “Regulation of immune system process”, “Myeloid leukocyte activation”, “Immune response regulating signaling pathway”, “Myeloid leukocyte mediated immunity”, “Locomotion”, and “Immune effector process” (Figure 3a). With regard to CC GO terms, “Secretory vesicle”, “Secretory granule”, “Vesicle lumen”, “Perinuclear region of cytoplasm”, “Chaperone complex”, “Tertiary granule lumen”, “Tertiary granule”, “Ruffle”, “Specific granule lumen”, and “Ficolin-1-rich granule” were among the most highly enriched subcategories (Figure 3b). The top 10 GO terms in the MF category were “Nitric oxide synthase regulator activity”, “binding and transporter activity”, “Signaling receptor binding”, “Disordered domain specific binding”, “Protein folding chaperone”, “Ion channel binding”, “Cell-cell adhesion mediator activity”, “Protein homodimerization activity”, “Ligand-activated transcription factor activity”, and “Cysteine-type endopeptidase inhibitor activity” (Figure 3c). WikiPathways analysis of the 10 top ranked pathways included “Transcriptional cascade regulating adipogenesis”, “Airway smooth muscle cell contraction”, “16p 11.2 proximal deletion syndrome”, “Transcription factor regulation in adipogenesis”, “Circadian rhythm-related genes”, “White fat cell differentiation”, “Nuclear receptors”, “The influence of laminopathies on wnt signaling”, “Adipogenesis”, and “No-cgmp-pkg mediated neuroprotection” (Figure 3d). ## 2.1.4. Constructed PPI Network, Determined Hub Genes, and ROC Analysis In order to select and further understand the hub genes between AD and UC, we first constructed a PPI network using co-DEGs in STRING (Figure 4a). Then, we used Cytoscape plug-in cytoHubba to screen the top 10 candidate hub genes by the MCC algorithm. As shown in Figure 4b, PPARG, NOS2, SELE, CXCL1, FGR, HSP90AB1, CD38, EPHA2, NR2F1, and IGLL5 were picked out. Interestingly, it was found that NOS2, SELE, CXCL1, and HSP90AB1 were related to PPARG, which was the most intensive hub gene. In Figure 4c,d, we presented representative ROC curves for the genes identified as hubs (PPARG, NOS2, SELE, CXCL1, and HSP90AB1). We found that the AUCs for the responsiveness of PPARG, NOS2, SELE, CXCL1, and HSP90AB1 > 0.70 indicated moderate predictive power to AD and UC. ## 2.2.1. Induced of the Mouse Model and qRT-PCR Validation of RNA-Seq Data APP/PS1 mouse model for AD and DSS-induced mice model for UC were used in the following study (Figures S2 and S3). We examined the mRNA expression levels of PPARG, NOS2, SELE, CXCL1, and HSP90AB1 in the hippocampus of AD and colon of UC with qRT-PCR to verify the dataset’s reliability. Compared with the WT group, the expression levels of PPARG and HSP90AB1 were significantly decreased, while NOS2, SELE, and CXCL1 were significantly increased in the APP/PS1 group (Figure 5a–e). Moreover, the consistent trends were validated in the comparisons between the NC and DSS groups (Figure 5f–j). ## 2.2.2. Protein Expression of PPAR-γ and iNOS in Both Diseases Was Confirmed by Western Blot (WB) To further validate the hypothesis, we investigated the changes of PPAR-γ and iNOS in the colon, the hippocampus of DSS-induced mice, and the hippocampus of APP/PS1 mice by WB. Compared with the NC group, the expression levels of PPAR-γ both in colon and hippocampus tissues were significantly decreased, while iNOS in the DSS group were significantly increased (Figure 6A–F). Moreover, the consistent trends were validated in comparisons between the WT and APP/PS1 groups in hippocampus tissues (Figure 6G–I). ## 2.3. Macrophages and Microglia Tended to Be Inflammatory Polarization Both in AD and UC Immunofluorescence (IF) was used to confirm that PPAR-γ in the colon and hippocampus of the DSS group was significantly reduced than that of the NC group (Figure 7a,b). Similarly, the expression of PPAR-γ in the hippocampus of the APP/PS1 group was significantly reduced than that of the WT group (Figure 7c). PPAR-γ is considered to be closely related to the M2 polarization of macrophages and microglia in some studies, while iNOS is a surface marker of M1 polarization. Therefore, we further explored the consistency of the polarization direction of colon macrophages and hippocampal microglia in two diseases. Firstly, we measured the expression of F$\frac{4}{80}$+iNOS+ and F$\frac{4}{80}$+Arg1+ cells in the colon. The double staining results revealed that the number of F$\frac{4}{80}$+iNOS+ in the DSS group was increased compared with the NC group (Figure 8a). Moreover, compared with the NC group, the expression levels of F$\frac{4}{80}$+Arg1+ cells in the colon were significantly decreased in the DSS group (Figure 8b). Furthermore, we observed that the expression of Iba1+iNOS+ cells both in the DSS group and APP/PS1 group in the hippocampus was significantly higher than those in the NC group and WT group, respectively (Figure 9a and Figure 10a). Compared with the NC group and WT group, the expression levels of Iba1+Arg1+ cells in the hippocampus were significantly decreased in the DSS group and APP/PS1 group (Figure 9b and Figure 10b). ## 3. Discussion As shown in Figure 11, our work first confirmed that PPARG and NOS2 were the shared genes of AD and UC through bioinformatics analysis of GSE5281 (AD) and GSE47908 (UC) in the GEO database. Meanwhile, we have noticed that PPARG and NOS2 represent different directions in macrophages and microglia heterogeneous polarization. To further verify the results of bioinformatics analysis and explore the potential relationship between the two diseases, DSS-induced mice and APP/PS1 mice were used for our research. Interestingly, we confirmed that the expression level of Arg1 (a biomarker of M2-type polarization) in the macrophages of the colon and microglia of the hippocampus (DSS-induced mice), and microglia of the hippocampus (APP/PS1 mice) decreased significantly, while the expression level of iNOS (a biomarker of M1-type polarization) increased significantly. In recent years, along with deep ongoing research, more and more attention has been drawn to the connection between AD and UC [7,8,9,21]. AD, the most common cause of dementia, with misfolded proteins accumulating due to the activation of microglial, oxidative stress, and the secretion of multiple cytokines, is the result of neuroinflammation from chronic systemic inflammation [22,23,24]. IBD, a disease with complex pathology that easily causes systemic inflammatory responses, was speculated that result from dysregulation of the immune response when individuals with genetic susceptibilities experience changes in their gut microbiome [7,25]. Moreover, the gut–brain axis (GBA) appears to play a critical role in neurodegenerative diseases, including AD [26]. Researchers [10,27] have shown that preventing bowel inflammation via germ-free rearing and antibiotic treatment has a positive effect on the reduction of cerebral Aβ pathology and neuroinflammation in AD model mice. A link between IBD and dementia could aid in the early detection and intervention of dementia in IBD patients and contribute to a better understanding of the long-term effects of IBD [8,28]. However, the mechanism is complex, and the correlation between the two remains unclear. For this reason, we have attempted to study the correlation between the two diseases at the genetic level to reveal the key underlying mechanism. Global gene expression data from hippocampus tissues for AD and colon tissues for UC can help us better understand the specific pathobiology and potentially plausible biological link between the two different diseases. Firstly, the independent GSEA for GSE5281 (AD) and GSE47908 (UC) studies showed 21 common pathways between the two datasets. Interestingly, we found neurodegenerative diseases, including AD, PD, and Huntington’s disease, confirming our hypothesis that the two diseases are closely related. Meanwhile, we also found 11 pathways ($52.38\%$, $\frac{11}{21}$) related to metabolism, suggesting that the relationship between the two diseases may be due to changes in metabolic pathways. Next, we confirmed that 61 genes had the same tendency in the gene expression between AD and UC. The functional enrichment analysis of co-DEGs showed an inflammatory response in GO-BP and transcriptional cascade regulating adipogenesis, transcription factor regulation in adipogenesis, white fat cell differentiation, and adipogenesis in WikiPathways. To further detect the hub genes among co-DEGs, hub gene analysis was performed using the cytoHubba plug-in after constructing the PPI network. In our study, the cytohubba analysis showed that the top 10 hub genes were PPARG, NOS2, SELE, CXCL1, FGR, HSP90AB1, CD38, EPHA2, NR2F1, and IGLL5 after calculating. Moreover, the most connected hub was PPARG, which was related to NOS2, CXCL1, HSP90AB1, and SELE. An AUC value ≥ 0.7 of the ROC suggested that the prediction performance of those hub genes was acceptable [29]. In addition, the qRT-PCR was used to validate the mRNA expression level of the five hub genes in UC and AD, confirming the reliability of the study. Interestingly, the pair of genes PPARG (protein name PPAR-γ) and NOS2 (protein name iNOS) play a crucial role in modulating the M1/M2 polarization of microglia/macrophages. PPAR-γ is an isoform of peroxisome proliferator-activated receptor (PPAR) that belongs to the nuclear receptor family of transcription factors, whose expression is abundant in white adipose tissue, brown adipose tissue, and the large intestine and spleen [30,31]. Moreover, PPAR-γ is essential for adipogenesis, energy balance, lipid biosynthesis, and adipokine production, which also validates the results of bioinformatics analysis [32]. iNOS is an inducible form of NOS, which is induced under pathological conditions [33]. As PPAR-γ with, iNOS is a central regulator of several biochemical pathways and energy metabolism, including the metabolism of glucose and lipids, based on increasing evidence [34]. We further confirmed the same trend of PPAR-γ and iNOS expression in the hippocampus of DSS-induced mice and APP/PS1 mice by WB. Macrophages play an essential role in maintaining intestinal immune homeostasis and in the pathogenesis of IBD, and targeted therapy to them could maintain remission in IBD [35]. Macrophages are heterogeneous, plastic, and strongly influenced by the microenvironment [36]. Macrophages are classified into two major subtypes: M1 (proinflammatory or classically activated) and M2 (anti-inflammatory or alternatively activated) [37,38]. In the lamina propria of inflamed gut, M1 macrophages break down the tight junction proteins, damage the epithelial barrier, and induce epithelial cell apoptosis, leading to excessive inflammation by secreting cytokines such as IL-12, IL-23, IL-1β, TNF-α, and ROS and ultimately causing tissue damage [37,38,39,40]. Conversely, M2 macrophages promote inflammation resolution and tissue remodeling by upregulated factors such as IL-4, IL-10, CD163, CD206, and Arg1 [37,38,39,40]. According to these findings, macrophage polarization plays an increasingly important role in inflammation progression and prognosis. PPAR-γ plays a central role in promoting M2 macrophages, as demonstrated by the connection between PPAR-γ and Arg1 [40,41]. As for iNOS, it has been used to define classically activated M1 macrophages, and its associated metabolites are fundamentally involved in the intrinsic regulation of macrophage polarization and function with increasing evidence [42]. By IF, we confirmed the changes in PPAR-γ expression and macrophage polarization in colon tissues of DSS-induced mice. In addition, via IF, we also confirmed that the trends in microglia polarization in the hippocampus of both disease mouse models were also consistent. As resident macrophages of central nervous system (CNS), microglia are thought to play a crucial role in maintaining a healthy state of the tissue environment and overcoming neuroinflammation [43,44]. The M1/M2 classification system has also emerged as a common language to discuss microglia heterogeneity across different fields, similar to macrophages [45]. It has been demonstrated that peripheral macrophages enhance infiltration of the hippocampus in DSS-induced mice, along with the increased frequency of M1-like microglia and increased release of proinflammatory cytokines [6]. Several studies have shown that in the disease process of AD, PPAR-γ plays an essential role in inhibiting the M1 polarization of microglia and promoting M2 polarization [46,47,48]. Like macrophages, iNOS is also a marker of M1 polarization in microglia and is widely recognized [49,50,51]. Moreover, lipid metabolism imbalance plays a critical role in AD pathogenesis [52]. ROS damaged lipids when pathological AD conditions, resulting in lipid peroxidation, and lipid peroxidation products were co-localized with Aβ in the brain [52]. Researchers validated 10 lipid metabolites derived from lipidomic approaches to distinguish cognitively normal individuals from those with preclinical AD in blood with an accuracy of more than $90\%$ [53]. By causing high levels of fecal deoxycholic acid (DCA) in the colon, high fat diet (HFD) may generate macrophage activation and colonic inflammation [54]. Additionally, HFD also impaired the bioenergetics of mitochondria in the colonic epithelium, disrupted the gut epithelial barrier, and increased susceptibility to colitis [55]. Furthermore, it has been widely confirmed that lipid metabolism disorder is an important reason for the activation of macrophages/microglia [56,57,58]. In view of these, we have reason to believe that PPARG and NOS2 are important biomarkers for the association of AD with UC. In conclusion, our study proposes shared genetic signatures to illustrate the possible mechanism of AD and UC interconnection, revealing that PPARG and NOS2 are shared genes of AD and UC. They drive macrophages and microglia heterogeneous polarization, which may be potential targets for treating neural dysfunction induced by systemic inflammation and vice versa. ## 4.1. GEO Dataset Selection The hippocampus data for AD and the colonic mucosa biopsy for UC were downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo, accessed on 5 September 2022). To better understand the mechanistic link between AD and UC, the independent datasets of GSE5281 for AD, including 10 AD tissues and 13 healthy tissues from the human hippocampus, and GSE47908 for UC, including 19 UC tissues and 15 healthy tissues from human colonic mucosa biopsies. ## 4.2. Gene Set Enrichment Analysis (GSEA) The Kyoto encyclopedia of genes and genomes (KEGG) pathway was analyzed using the GSEA R package run in R 4.0.3 by the Molecular Signatures Database (MSigDB, v7.4, http://software.broadinstitute.org/gsea/msigdb/collections.jsp#H, accessed on 5 September 2022) [59,60]. ## 4.3. Identification and Enrichment Analyses of DEGs, PPI Network Construction, and Selection of Hub Genes DEGs were defined with a p-value < 0.05 and \|log2 (fold change)\| > 1 using the limma package [61]. To evaluate the significance of the overlap between the DEGs belonging to the AD and UC signatures, Fisher’s exact test was performed [62]. Enrichment analysis included terms from the WikiPathways database and The Gene Ontology (GO) [63,64,65]. A human PPI network was constructed based on the STRING database (medium confidence, https://string-db.org, version 11.5, accessed on 5 September 2022) [66]. Then, a cytoHubba plug-in (http://apps.cytoscape.org/apps/cytohubba, accessed on 5 September 2022) in Cytoscape (version 3.9.1) was applied to identify the top ten hub genes in the PPI network through the MCC algorithm [67,68]. ## 4.4. Animals Male 6-month-old APP/PS1 double-transgenic mice were selected as the AD mice model for verification of AD data from human samples, and the same-age C57BL/6J (wild-type, WT) mice were used as a negative control. All mice were obtained from Beijing Weishang Lituo Technology Co., Ltd. (Beijing, China, SCXK (Jing) 2016-0009). At the same time, male C57BL/6J mice (26 ± 2 g) were obtained from GemPharmatech Co., Ltd. (Chengdu, China, SCXK (Chuan) 2020-034) for verification of UC data from human samples. The mice were randomized into the normal control (NC) and DSS groups. Mice in the DSS group received $2.5\%$ DSS (MP Biomedicals, Santa Ana, CA, USA) for seven days, while mice in the NC group received distilled water only [69]. In addition to body weight, food intake, water intake, rectal bleeding, survival, and stool consistency were monitored daily in the mice. In a pathogen-free enclosure, all animals were fed standard rodent chow and water ad libitum at ambient temperature (23 ± 1 °C). ## 4.5. Morris Water Maze (MWM) Test It has been widely used to assess spatial learning and memory in mouse models of neurological disorders. Three parts were included in this test: the visible platform, the hidden platform, and the space exploration. A circular water tank (diameter × height, 90 cm × 50 cm) was filled with water at 22 ± 1 °C and divided equally into four quadrants (Chengdu Techman Software Co., Inc., Chengdu, China). About 1.5–2 cm below the water’s surface, the escape platform (which had a diameter of 9 cm and a height of 28 cm) was located on the constant quadrant. Mice were placed in a quiet environment before the formal test for at least 0.5 h to acclimatize to the environment in advance. They were trained once in each quadrant for 90 s, 4 times a day. If they did not find the platform within the 90 s trial limit, they were guided to the platform for 5–10 s. There were two days of visible platform testing, while four days of hidden platform testing were conducted with white water and an invisible platform. A record of each mouse’s escape latency and swimming distance was taken. On the seventh day, mice were placed in a random quadrant without the platform for a space exploration test. The ability to learn and memory was evaluated by the time it took to cross the platform, the distance swam, and the time swam in the target quadrant in 90 s. ## 4.6. Disease Activity Index (DAI) Colitis DAI was calculated based on body weight loss, occult blood, and stool consistency for each mouse on a basis. Table S2 shows the scores for each subscale. ## 4.7. Hematoxylin and Eosin (HE) Staining and Periodic Acid Schiff (PAS) Staining The colon tissues in the NC and DSS groups were collected and fixed with buffered $4\%$ formalin for two days. The samples were sectioned at a thickness of 5 μm and stained with HE and PAS for histopathological examination using a light microscope (Olympus Corporation, Tokyo, Japan). ## 4.8. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) Total mRNA was extracted from colon and hippocampus tissues using MolPure® TRIeasyTM Plus Total RNA Kit (YEASEN, Shanghai, China), and cDNA was prepared using Hifair®III 1st Strand cDNA Synthesis SuperMix for qPCR (YEASEN, Shanghai, China) as directed. After then, RT-qPCR analysis of the resulting cDNA was performed using Hieff UNICON Universal Blue qPCR SYBR Green Master Mix (YEASEN, Shanghai, China). Primer sequences are shown in Table S3. In this study, the relative expression levels of target genes were normalized to β-actin and calculated using the 2−∆∆Ct method. ## 4.9. Western Blot (WB) WB analysis was performed as previously described [70]. In order to obtain the protein extracts, mice’s colon and hippocampus tissues were treated with a lysis buffer containing ethylenediaminetetraacetic acid (EDTA)-free complete protease inhibitors. Then, proteins were subjected to $10\%$ sodium dodecyl sulfate-polyacrylamide gels (SDS-PAGE). For the transfer of the bands, a polyvinylidene difluoride membrane was used. Membranes were blocked in $0.1\%$ Tween-20 Tris-buffered saline (TBST) containing $5\%$ nonfat dry milk for 2 h. The membranes were then incubated with the anti-PPAR-γ antibody (1:2000, Proteintech, Wuhan, China) or anti-iNOS antibody (1:500, Proteintech, Wuhan, China) overnight at 4 °C. Subsequently, membranes were incubated with a secondary antibody (1:5000, TRAN, Beijing, China) for 2 h at 37 °C. Normalization was performed by blotting the same membranes with an antibody against GAPDH (1:50,000, Proteintech, Wuhan, China). ## 4.10. Immunofluorescence (IF) Sections were deparaffinized in xylene and rehydrated through graded alcohol series. After that, sections were washed three times in phosphate-buffered saline (PBS) for 5 min each, then incubated with $5\%$ goat serum for 1 h at 37 °C. Sections were incubated with the rabbit anti-PPAR-γ, anti-iNOS (1:100, Proteintech, Wuhan, China), rabbit anti-Arg1 (1:200, Bioss, Beijing, China), rabbit anti-Aβ1–42, anti-P-Tau (1:200, Abcam, Waltham, MA, USA), mouse anti-Iba1 and anti-F$\frac{4}{80}$ (1:200, Bioss, Beijing, China) overnight at 4 °C. The sections were incubated with Cy3-conjugated Affinipure Goat Anti-Rabbit IgG (1:200, Proteintech, Wuhan, China) or Alexa Fluor 488-conjugated goat anti-rabbit IgG (1:200, Bioss, Beijing, China) at 37 °C for 2 h in a dark room after being washed 3 times with PBS. In the final step, the sections were rinsed 3 more times before being stained for 5 min with DAPI (Biyuntian, Shanghai, China). The sections were imaged using Pannoramic MIDI (3DHISTECH, Budapest, Hungary). ## 4.11. Statistical Analysis Statistical analysis was performed using R (version 4.2.1; RStudio Inc., Boston, MA, USA), GraphPad Prism (version 8.0; GraphPad Software Inc., San Diego, CA, USA), and IBM SPSS Statistical Software (version 27.0; IBM SPSS Inc., Armonk, NY, USA). For correlation analysis, Spearman’s correlation was used to analyze the relationship between hub genes and immune cells. The receiver operating characteristic (ROC) curves and the curve (AUC) values were computed using the pROC R package. The Shapiro-Wilk normality test was used for the normality test. Variance homogeneity was evaluated with Levene’s test. 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--- title: Impaired Cardiovascular Parameters in Resistance Training Practitioners Who Take Ergogenic Aids authors: - Bruno Bavaresco Gambassi - Daniela Conceição Gomes Gonçalves e Silva - Camila Almeida Sá - Roberto Rodrigues Bezerra - Cleilson Barbosa de Freitas - Marcelo Silva Costa - Paulo Roberto da Silva Marques - Pedro Paulo Ramos da Silva - Manoel Pereira Guimarães - Fabiano de Jesus Furtado Almeida - Richard Diego Leite - Dário Celestino Sobral Filho - Paulo Adriano Schwingel journal: Journal of Cardiovascular Development and Disease year: 2023 pmcid: PMC10058636 doi: 10.3390/jcdd10030113 license: CC BY 4.0 --- # Impaired Cardiovascular Parameters in Resistance Training Practitioners Who Take Ergogenic Aids ## Abstract Background: Although there are studies on blood pressure (BP) and autonomic cardiac control (ACC) impairments caused by ergogenic aids, research has scarcely addressed this analysis during sleep. This study analyzed BP and ACC during sleep and wake periods in three groups of resistance training (RT) practitioners: ergogenic aid non-users, thermogenic supplement (TS) self-users, and anabolic-androgenic steroid (AAS) self-users. Methods: RT practitioners were selected for the Control Group (CG; $$n = 15$$), TS self-users Group (TSG; $$n = 15$$), and AAS self-users Group (AASG; $$n = 15$$). All individuals underwent cardiovascular Holter monitoring (BP, ACC) during sleep and wake periods. Results: The maximum systolic BP (SBP) during sleep was higher in AASG ($p \leq 0.01$) than CG ($p \leq 0.001$). CG had lower mean diastolic BP (DBP) than TSG ($p \leq 0.01$) and lower mean SBP ($$p \leq 0.009$$) than the other groups. Additionally, CG had higher values ($p \leq 0.01$) than TSG and AASG for SDNN and pNN50 during sleep. HF, LF, and LF/HF ratio values during sleep were statistically different in CG ($p \leq 0.001$) from the other groups. Conclusions: Our findings demonstrate that high doses of TS and AAS can impair cardiovascular parameters during sleep in RT practitioners who take ergogenic aids. ## 1. Introduction The increasing self-use of thermogenic supplements (TS) and anabolic-androgenic steroids (AAS) among young people who exercise regularly has been a concern among health professionals. Many resistance training (RT) practitioners try a variety of strategies to increase muscle mass and/or decrease body fat without solid scientific knowledge about such practices. In this sense, Araújo, Andreolo, and Silva [1] observed that $34\%$ of interviewed bodybuilders used supplements and $9\%$ used AAS. Another piece of research demonstrated that $24\%$ of interviewees used supplements, and $19\%$ reported regular use of AAS [2]. Additionally, a study with 510 physically active people found that $76.1\%$ of interviewees used supplements and/or AAS [3]. Given such a prevalence, it is crucial to verify the effects of TS and/or AAS self-medication on the risk of cardiovascular death. According to some studies, high TS doses cause negative changes in cardiovascular parameters [4,5,6]. In research conducted by Gomes Gonçalves e Silva et al. [ 7], significant differences in systolic BP (SBP) were observed comparing TS users with non-users. Additionally, abuse of AAS is also associated with cardiac arrhythmia, systemic arterial hypertension, cardiac hypertrophy, myocardial infarction, and sudden death [8,9,10,11,12,13,14,15,16,17]. Besides BP and ACC changes with a risk of cardiovascular death, there may also be an increased risk of complications depending on the period (e.g., sleep) when they are investigated. In this sense, O’Brien, Sheridan & O’Malley [18] have demonstrated that hypertensive patients with a lower nocturnal drop in BP had a higher prevalence of strokes, calling them “non-dippers”. In a recent study, Nakanishi et al. [ 19] observed that changes in nocturnal SBP may be associated with an increased risk of hypertensive brain injury. Zhang et al. [ 20] retrospectively assessed polysomnography data from 2111 volunteers and found worse ACC during sleep in patients with cardiovascular diseases than in individuals without them. Although there are studies on BP and ACC impairments in ergogenic aid users, research has scarcely addressed this analysis during sleep. Given this and the health risks, the present study is necessary. Thus, the objective of this study was to analyze BP and ACC during sleep and wake periods in three groups of RT practitioners: ergogenic aid non-users, TS users, and AAS users. ## 2.1. Design This analytical cross-sectional study was conducted upon approval by the Ethics Committee at the University of Pernambuco (CEP-UPE) and followed the ethical guidelines for human research according to the Declaration of Helsinki (1964, revised in 2013). ## 2.2. Participants The sample comprised 346 physically active males, aged 18 to 50 years, recruited among RT practitioners at fitness centers in the Integrated Economic Development Region of Petrolina/PE and Juazeiro/BA in Brazil. Symptomatic volunteers with heart diseases ($$n = 33$$), diabetes ($$n = 11$$), competitive bodybuilders ($$n = 13$$), narcotic users ($$n = 43$$), smokers ($$n = 15$$), cosmetic doping self-users ($$n = 7$$), and excessive alcohol drinkers ($$n = 67$$) were excluded. The initial sample ($$n = 157$$) comprised 15 RT practitioners using AAS during data collection without professional guidance (self-medication), 92 using TS without professional guidance (self-medication), and 50 ergogenic aid non-users. A total of 30 individuals were randomly selected among ergogenic aid non-users (control group [CG]; $$n = 15$$) and TS self-users group (TSG; $$n = 15$$) for comparison with the AAS self-users group (AASG; $$n = 15$$). The CG comprised RT practitioners who reported not having ever used dietary supplements and/or AAS in their lives. TSG comprised regular users who had been taking, for at least 6 months, dietary supplements containing 1.3-dimethylamylamine (DMAA) or other ergogenic resources of the thermogenic type. AASG comprised users of testosterone and its synthetic derivatives. AASG participants did not have any medical prescriptions, and the substances were illegally acquired by users. Likewise, dietary supplements were used without any nutritional and/or medical prescription, and the compounds were purchased by users at registered stores. Participants were not offered any legal or illegal substances in this or any other phase of the research. ## 2.3.1. Anthropometric Their height was measured with a portable scientific stadiometer (Seca, Hamburg, Germany) placed on the wall, with 0.1-cm accuracy. Total body mass was evaluated with a properly calibrated (ISO/IEC 17025: 2005) electromechanical scale W$\frac{200}{5}$ (Welmy Indústria e Comércio Ltda, Santa Barbara d’Oeste, SP, Brazil) with 50-g accuracy. Body mass index (BMI) was obtained by dividing the body weight in kilograms by the square of the body height in meters. ## 2.3.2. Cardiovascular Parameters BP and ACC were evaluated for 24 h with an electrocardiography Holter monitor and an ambulatory BP monitor (CardioMapa, Cardios, São Paulo, SP, Brazil). The most stable data in the 4-h sleep and wake period were used. Participants were instructed to maintain normal daily activities and record them in a personal diary. R-R intervals (RRi) were recorded with a 3-channel ECG recorder (Cardiomapa, Cardios, São Paulo, SP, Brazil) at an 800-Hz sampling frequency in the supine position. After data collection, raw RRi data from ECG were exported in ASCII format to software supplied by the manufacturer. Each participant’s skin was cleaned and prepared to fix surface electrodes (Red Dot™ 2560, 3M, Sumaré, SP, Brazil) before recording, following the manufacturer’s instructions. The white electrode was placed on the center of the manubrium; the red electrode, on the xiphoid process; the black electrode, on the left anterior axillary line on the sixth rib; and the green electrode, on the right anterior axillary line on the sixth rib. For time-domain analysis, the standard deviation of all NN intervals (SDNN) and the percentage of consecutive RRi with differences greater than 50 ms (pNN$50\%$) were calculated. The frequency domain was analyzed with the Fast Fourier Transform test for previously selected RRi sequences with 4-Hz interpolation and $50\%$ overlap. Two main spectral components were selected for analysis: low frequency (sympathetic and parasympathetic components [LF, from 0.04 to 0.15 Hz]) and high frequency (parasympathetic component [HF, from 0.15 to 0.50 Hz]). Normalized spectral components (LF, HF, and LF/HF ratio) were expressed in normalized units (nu). Normalization consisted of dividing the power of a given spectral component (HF or LF) by the total power minus the power below 0.04 Hz and multiplying this ratio by 100. ## 2.4. Data Processing and Statistical Analyses Data were processed and analyzed in SPSS software (SPSS Inc., Chicago, IL, USA, Release 16.0.2, 2008). Descriptive statistics were made with the Shapiro–Wilk test and Bartlett’s criteria. Continuous variables were summarized with means and standard deviations (SD), while categorical variables were presented in frequencies and percentages. Comparisons between the means of the different conditions were made with ANOVA and Tukey’s post hoc test. All statistical methods were two-tailed, p-value calculations were exact, and the significance level was set to $5\%$. ## 3.1. Blood Pressure TS and/or AAS are generally used in defined periods, often with non-use intervals. The study considered TS or AAS consumption in the 30 days before the evaluation. The mean (±SD) length of self-reported TS use by the TSG was 3.0 (±1.5) months, with a weekly frequency of 5 to 7 days. TSG reported a concomitant self-consumption of 6.0 (±1.5) grams of caffeine and 1.2 (±0.6) grams of DMAA in the preceding month. AASG reported a combination of intramuscular and oral AAS self-use with a mean of 3.6 g (±1.2) of testosterone or equivalent in the same period. Reported intramuscular AAS injections contained testosterone or derivatives, while combined oral preparations contained oxymetholone and oxandrolone. The mean length of self-reported AAS use by the AASG was 4.0 (±1.0) years. Table 1 shows statistically similar demographic characteristics ($p \leq 0.05$) between the groups. Significant statistical differences ($p \leq 0.05$) for systolic BP (SBP) and diastolic BP (DBP) were observed between the groups in both wake and sleep periods, except for the maximum DBP during sleep (Table 2). The mean SBP during sleep was statistically different between the three groups ($$p \leq 0.009$$), with CG presenting lower mean values than the others (Δ = −13.7 mmHg in comparison with TSG [$p \leq 0.01$]; Δ = −23.0 mmHg in comparison with AASG [$p \leq 0.01$]). During sleep, the maximum SBP was higher in AASG than CG (Δ = 17.8 mmHg; $p \leq 0.01$), and the mean DBP was higher in TSG than CG (Δ = 8.5 mmHg; $p \leq 0.01$). In addition, TSG had lower values for mean SBP during sleep than AASG (Δ = −9.3 mmHg; $p \leq 0.01$). In the same way, maximum SBP, maximum DBP, mean SBP, and mean DBP in wake periods had lower mean values in CG than in the other groups ($p \leq 0.01$). The mean SBP in wake periods was statistically higher in AASG than TSG (Δ = 9.6 mmHg; $p \leq 0.05$). ## 3.2. Autonomic Cardiac Control The results of ACC analysis in RT practitioners for the wake and sleep periods using time-domain methods showed higher pNN50 values in the CG during wake periods ($p \leq 0.01$) and in SDNN and pNN50 values during sleep periods ($p \leq 0.01$) in comparison with TSG and AASG (Table 3). Likewise, frequency-domain ACC analysis showed the same trend with good CG scores (Table 4). CG had statistically lower ($p \leq 0.001$) LF values and LF/HF ratio during sleep and wake periods than TSG and AASG ($p \leq 0.001$). In addition, HF values during sleep and wake periods were statistically higher in the CG than in the other groups ($p \leq 0.001$). Except for HF in wake periods, all other variables had values with statistical differences in AASG in comparison with TSG ($p \leq 0.05$). ## 4. Discussion The main findings of the present study are the changes in mean systolic and mean diastolic BP and ACC (SDNN; pNN50; HF; LF; LF/HF ratio) during sleep, comparing RT practitioners who do not take ergogenic aids with TS self-users and AAS self-users. In addition, this is the first study to analyze BP and ACC during sleep in this population. These findings have important clinical and public health implications since increased SBP during sleep strongly predicts cerebrovascular disease [18,21]. Also, a decline in BP (<$10\%$) during sleep is associated with a lower risk of morbidity and mortality from cerebrovascular disorders [22,23]. High BP during sleep may indicate persistent sympathetic hyperactivity, thus contributing to cardiovascular disease onset [21,22,23,24]. Changes in BP were also observed in the wake period for all groups. Corroborating these findings, a previous study by Gomes Gonçalves e Silva et al. [ 7] has demonstrated an increase in SBP in RT practitioners who took AAS or TS, in comparison with those who had never taken them. In line with the findings, research points out that supplement use (dimethylamine, alone or in combination with caffeine), can damage SBP and DBP control and mean BP [4,25,26]. In addition, AAS abuse is associated with cardiovascular impairments (cardiac arrhythmia, systemic arterial hypertension, cardiac hypertrophy, myocardial infarction) and sudden death [8,9,10,11,12,13,14,15,16,17]. According to Urhausen, Albers, and Kindermann [9], several years after discontinuing AAS abuse, RT athletes still have slightly concentric left ventricular hypertrophy compared to athletes who had never taken them. Additionally, chronic AAS use changes the tonus and reflex control of the cardiovascular system [10]. In this sense, cardiac receptors and BP receptors changes are essential factors to consider in cardiovascular AAS actions, according to Beutel et al. [ 10]. In addition to these impairments, AAS is associated with endothelial dysfunction with a consequent increase in the risk of atherosclerosis [8]. Hence, studies have shown an increase in BP with TS use and/or AAS self-medication. However, the time (duration) and/or amount per cycle necessary to cause such changes remain poorly understood. As previously mentioned, findings on long-term caffeine intake and changes in BP are conflicting. Another important finding in the present study is the worse ACC during sleep in AASG and TSG than in CG. SDNN, pNN50, HF, LF, and LF/HF ratio values were statistically different ($p \leq 0.001$) between CG and the other groups during sleep. These findings also have important clinical implications since reduced heart rate variability during sleep is associated with the risk of stroke [27]. Evidence has demonstrated that ACC during sleep was independently associated with an increased risk of cardiovascular disease and a higher risk of lethal events after myocardial infarction [20,28]. Additionally, an elegant study by Zhang et al. [ 20] has demonstrated that changes in heart rate variability during sleep might occur many years before the onset of cardiovascular diseases. Besides such damages, the present study also observed changes in ACC in wake periods in AASG, in contrast with CG and TS. Corroborating these findings, evidence has demonstrated cardiovascular impairment after AAS or TS use [4,5,6,8,9,10,11,12,13,14,15,16]. In this sense, in recent research on the effects of long-term AAS abuse on cardiac autonomic efficacy and cardiac adaptations in strength-trained athletes, impaired heart rate variability was associated with early left ventricular diastolic dysfunction [29]. 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--- title: Optimization, Probiotic Characteristics, and Rheological Properties of Exopolysaccharides from Lactiplantibacillus plantarum MC5 authors: - Xuefang Zhao - Qi Liang journal: Molecules year: 2023 pmcid: PMC10058658 doi: 10.3390/molecules28062463 license: CC BY 4.0 --- # Optimization, Probiotic Characteristics, and Rheological Properties of Exopolysaccharides from Lactiplantibacillus plantarum MC5 ## Abstract This study optimized the exopolysaccharides (EPS) production for Lactiplantibacillus plantarum MC5 (Lp. plantarum MC5) and evaluated the resistance to human simulated digestive juices, antioxidant activity in vitro, and rheological properties of EPS-MC5. The results showed that maximum EPS production of 345.98 mg/L (about 1.5-old greater than the initial production) was obtained at optimal conditions of inoculum size ($4.0\%$), incubation time (30 h), incubation temperature (34.0 °C), and initial pH value (6.40). Furthermore, the resisting-digestion capacity of EPS-MC5 after 180 min in α-amylase, simulated gastric juice (pH 2.0, 3.0, 4.0), and simulated intestinal juice (pH 6.8) was $98.59\%$, $98.62\%$, $98.78\%$, $98.86\%$, and $98.74\%$, respectively. In addition, the radical scavenging rates of DPPH•, ABTS•, •OH, and ferric-iron reducing power (OD700) of EPS-MC5 were $73.33\%$, $87.74\%$, $46.07\%$, and 1.20, respectively. Furthermore, rheological results showed that the EPS-MC5 had a higher apparent viscosity (3.01 Pa) and shear stress (41.78 Pa), and the viscoelastic modulus (84.02 and 161.02 Pa at the shear frequency of 100 Hz). These results provide a new insight into the application of EPS in human health and functional foods, which could also improve theoretical guidance for the industrial application of EPS. ## 1. Introduction Microorganisms producing bioactive exopolysaccharides (EPS) include archaea, bacteria, and fungi [1]. Lactic acid bacteria (LAB) are well-known EPS-producing bacteria, and their final metabolites are generally recognized as safe (GRAS). They can be applied to different industries, especially the food industry [2] and pharmaceutical industry [3]. As a starter, probiotics are reported to play an important role in the rheology and texture of fermented foods [4]. The widespread use of LAB in baked foods has been reported to improve texture properties, increase flavor and produce lactic acid [5]. EPS also plays an important role in protecting inter-and intra-microbial interactions, serving as a source of nutrients in times of hunger and resistance to virulence when pathogens attack [6]. More than 30 species of LAB have been reported to produce EPS [7], such as Lactobacillus plantarum [2], Lactobacillus rhamnosus [8], Streptococcus thermophilus [9], and so on. Reactive oxygen species (ROS) are used in immune mechanisms to prevent bacterial and viral infections [10]. However, excess ROS can oxidize important biological components such as DNA, lipids, and proteins. This oxidative damage is closely associated with accelerated aging and the development of various diseases, including cancer [11], diabetes [12], and hypertension [13]. Notably, the antioxidant is one of the important prebiotic effects of LAB. The cell surface itself contains antioxidants, and cells also produce antioxidants such as EPS, peptides, and lactic acid [14]. A previous study reported that EPS production and concentration can be affected by medium components (carbon and nitrogen sources) and culture conditions [15]. EPS from LAB can protect cells from desiccation [9], metal ions, antibiotics, bacteriophages, and cell wall-degrading enzymes [16]. Degeest et al. [ 17] reported that the EPS production and their monomer composition may be affected by the growth medium and culture conditions of laboratory-screened LAB. Likewise, EPS production varies widely (40–1000 mg/L) between strains [7]. Previous literature reported that some EPS-producing Lp. plantarum strains isolated from traditional fermented foods possess many functional properties, especially antioxidant activity [18]. Lp. plantarum is one of the probiotics that can be used in the food list. Its EPS has good biological activity and industrial application characteristics, but it faces the problem of low yield and instability, which limits its promotion and application. Lp. plantarum isolated from traditional fermented dairy products is rare, while Enterococcus faecalis is the main strain isolated from traditional fermented dairy products. To improve the commercial-scale production of EPS, response surface methodology was used to model and optimize the fermentation substrate and culture conditions for EPS production [2]. Therefore, it is particularly necessary to strengthen the screening of new strains or optimize EPS production conditions to improve the EPS production of Lp. plantarum, which is of great significance for the commercial development of EPS. In addition, although the research on the antioxidant activity of EPS produced by Lp. plantarum had some free radical models, they are not systematic and comprehensive. Lp. plantarum MC5 was isolated from traditional fermented yak milk in the Gansu Tibetan area, which was identified as Lactobacillus plantarum by 16S rRNA sequencing and whole genome sequencing technology. Lp. plantarum MC5 had better EPS-producing and fermentation capacity [19]. In this study, EPS culture conditions were optimized using response surface methodology (RSM) to increase EPS yield. EPS was prepared and purified under optimum conditions. The probiotic properties of the EPS were further investigated, including anti-α-amylase activity, simulated gastrointestinal fluid tolerance, and antioxidant activities (radical scavenging activity of DPPH•, ABTS•, •OH, and iron-reducing power). In addition, the rheological properties of the EPS were also investigated. ## 2.1. Identification of Strain MC5 and Culture Conditions Single Factor Test Based on the 16S rRNA sequence, the phylogenetic tree showed the strain MC5 was more similar to Lp. plantarum CIP 103151 and Lp. plantarum JCM 1149 than other species, so the MC5 was identified as Lp. plantarum. ( Figure 1). On an industrial scale, the use of microorganisms was beneficial because they can be cultured under controlled conditions and produce large amounts of EPS in a short time [20]. Therefore, culture conditions are important to increase EPS yield and productivity [21]. To improve the EPS production of Lp. plantarum MC5, the optimal culture conditions of this strain were studied in this paper (Figure 2). The results of inoculation size showed that the EPS-MC5 content increased from 91.98 to 175.45 mg/L at 1–$5\%$ ($p \leq 0.05$, Figure 2a). The maximum EPS content was 175.45 mg/L at $4\%$ inoculation size. Jiang et al. [ 22] reported that appropriate inoculation size was the prerequisite for high EPS production of microorganisms. The results of fermentation time showed that the EPS content first increased (12–24 h) and then decreased (24–36 h). ( Figure 2b). When the fermentation time was 24 h, the maximum EPS yield (164.65 mg/L) was obtained. At this time (24 h), the Lp. plantarum MC5 reached a stable stage, so the EPS content produced by metabolism was the largest. After 24 h, the EPS content decreased because the large number of metabolites accumulated in the fermentation broth inhibited the growth and reproduction of the strain. Fermentation temperature results showed that the EPS production increased significantly at the temperature of 31–37 °C ($p \leq 0.05$), and the EPS content varied in the range of 89.00–186.77 mg/L (Figure 2c). When the temperature was 37 °C, the EPS production reached a maximum of 186.77 mg/L, indicating that the activity of EPS-related enzymes in the cells of Lp. plantarum MC5 was the highest at this temperature. When the fermentation temperature continued to increase, the EPS production decreased significantly ($p \leq 0.05$), indicating that the increased temperature inhibited the activities of EPS-related enzymes. Although strain fermentation is a dynamic process, the initial pH of the fermentation broth is also important for EPS production [23]. The EPS production first increased and then decreased at the initial pH of 5.6–7.2 ($p \leq 0.05$, Figure 2d), indicating that the initial pH was too acidic or too alkaline, which would affect the EPS production of Lp. plantarum MC5. When the initial pH was 6.4, the highest EPS production was 169.27 mg/L, indicating that the strain was suitable for growth in a neutral acid environment, and the enzymatic reaction of the strain was more active in this environment. ## 2.2. Optimization of Fermentation Conditions for EPS-MC5 Based on the single factor test, four culture conditions were independent variables, and the EPS production was the response value. Response surface optimization and the test plans were designed by using Design-Expert 8. 0. 6.1 software (Table 1). The overall quadratic polynomial equation for EPS yield was established by multiple regression analysis on the inoculum size (A), the culture time (B), the culture temperature (C), and the initial pH (D) of Lp. plantarum MC5: EPS = 356.92 + 8.38A + 19.15B − 17.79C − 13.39D − 11.25AB + 17.22AC − 0.42AD − 55.91BC + 6.09BD + 4.69CD − 105.37A2 − 68.19B2 − 79.86C2 − 100.95D2. The regression model was analyzed by variance analysis and reliability analysis, and the results were shown in Table 2. The results were subjected to analysis of variance (ANOVA), and statistical tests were performed with the F test shown in Table 2. The F value of the model was 26.34, $p \leq 0.0001$, indicating that the regression model was statistically significant. The lack of fit term was not significant, indicating that the model had good simulation, and R2 and correction coefficient R2Adj were 0.9634 and 0.9268, respectively, indicating that the established regression equation had a good degree of fit and could successfully predict the response value. In addition, the coefficient of variation (C.V. = $10.00\%$) indicated that the experimental results had high precision and reliability. The model data showed that the primary term B, the interaction term BC, A2, B2, C2, and D2 had a very significant impact on the EPS yield of the fermentation broth ($p \leq 0.01$), and the primary term C and D had a significant impact on the EPS yield ($p \leq 0.05$). To sum up, the order of the significant differences in the influence of the four factors was culture time > culture temperature > initial pH > inoculation size. ## 2.3. Three-Dimensional Response Surfaces and Count Plots of Variables To visualize the effect of the interaction among the four factors of A, B, C, and D on the EPS yield of the strain, the three-dimensional response surface and contour plots between every two factors and EPS yield were drawn (Figure 3). Compared with other graphs, the contour line of the interaction term BC was elliptical, with the densest distribution and the steepest surface, followed by the interaction term AC, which showed that the interaction between culture time, culture temperature, and inoculum size had a more significant effect on EPS yield. This result corresponded to the results in Table 2. Therefore, culture time and temperature were key factors affecting EPS production. ## 2.4. Verification Test of EPS-MC5 Yield The optimal culture conditions for each factor were predicted as follows: the inoculation size, culture time, culture temperature, and initial pH were $4.24\%$, 30 h, 34.26 °C, and 6.42, respectively. The predicted EPS yield obtained under these conditions was 355.46 mg/L. In order to verify the effectiveness of the response surface model, considering the possibility of actual operation, the optimal culture conditions were adjusted as follows: the inoculum size was $4.0\%$, the culture time was 30 h, the culture temperature was 34.0 °C, and the initial pH value was 6.40. Under these culture conditions, the EPS content from Lp. plantarum MC5 was 345.81 mg/L (Table 3). The experimental results were in good agreement with the predicted results, indicating that the mathematical model was suitable for the simulation of the EPS production process in this study. We verified that the measured EPS yield was close to the EPS yield (356.92 mg/L) obtained by the five groups of parallel experiments at the center point of the response surface. In addition, the EPS production from other LAB was summarized and compared in Table 4. Many factors affect EPS yield [23,24]. EPS yield and the optimal EPS-producing conditions varied greatly (69–2767 mg/L), which may be due to differences in medium composition, isolation source, and strain species [25]. ## 2.5. Isolation and Purification of EPS-MC5 The EPS-MC5 was isolated under optimal culture conditions. The crude EPS-MC5 was separated by anion-exchange chromatography of DEAE Sepharose Fast Flow (Figure 4a). Fractions corresponding to the major peak eluted only with 0.05 Mol/L and 0.1 Mol/L NaCl were found to contain EPS, which showed that 0.05 and 0.1 Mol/L NaCl solution eluted almost all EPS. These fractions containing EPS were acidic EPS as they were eluted with NaCl [29]. The purified EPS eluate was subjected to UV full-wavelength scanning (Figure 4b). EPS-MC5 had no absorption peaks at 260 and 280 nm, indicating that the nucleic acid and protein in the EPS have been removed, and the EPS had high purity. ## 2.6. In Vitro Resisting-Digestion Capacity of EPS-MC5 to α-Amylase and Simulated Gastrointestinal Juices The premise of EPS from LAB to play a probiotic role in the human gastrointestinal tract is that it must have a strong anti-digestive ability. Studies have reported that EPS produced by probiotics plays an important role in the colonization of probiotics in the human gastrointestinal tract [30]. At 0–180 min, the α-amylase resisting-digestion capacity (αRC) of EPS-MC5 was significantly higher than fructooligosaccharides (FOS) ($p \leq 0.05$). At 0–80 min, the αRC of EPS-MC5 decreased significantly ($p \leq 0.05$), while at 80–180 min, the difference in αRC was not significant ($p \leq 0.05$), indicating that the structure of EPS-MC5 was stable. The αRC of EPS-MC5 at 180 min was $98.59\%$ (Figure 5a). The α-amylase can specifically hydrolyze the α-1,4 glucosidic bonds in starch or other polysaccharides. Due to the high αRC of the EPS, the EPS-MC5 could contain little or no α-1,4 glucosidic bonds. The resisting-digestion capacity (RC) of EPS-MC5 was significantly higher than that of FOS in simulated gastrointestinal juices at different pH values ($p \leq 0.05$), indicating that EPS-MC5 had a higher anti-digestive ability (Figure 5b,c). Within 0–120 min, the RC of EPS in four different pH simulated gastrointestinal juices decreased significantly ($p \leq 0.05$), while in 120–180 min, the RC decreased insignificantly ($p \leq 0.05$). In addition, the RC of the EPS-MC5 in the simulated gastric juice at pH 2.0 was significantly lower than those in pH 3.0 and pH 4.0 ($p \leq 0.05$). The results showed that the RC was inversely proportional to pH, with more glycosidic bonds cleavage at low pH. This may be due to that pH affected the RC of EPS by adjusting the enzymatic activity in simulated gastric juice. The RC of EPS-MC5 at different pH simulated gastrointestinal juices were 98.62–$98.86\%$. Caggianiello et al. [ 31] reported that EPS-producing strains are more likely to colonize the intestine because of the adhesion of EPS to intestinal epithelial cells. The results of Mao et al. [ 32] showed that the EPS produced by E. coli O157:H7 was resistant to bile salts, and simulated gastrointestinal juices. Devi [30] reported that the hydrolysis resistance of EPS from Weissella Confusa KR780676 to α-amylase, gastrointestinal juices was 99.1–$98.8\%$, which was close to that of EPS-MC5 in this study. Results have shown that EPS-MC5 has good stability to ensure that it works as intended once it enters the intestinal tract. ## 2.7. In Vitro Antioxidant Activity of EPS-MC5 The in vitro radical scavenging rate of EPS is a common method to evaluate the ability and mechanisms of antioxidants [33]. DPPH· is a stable radical with an unpaired electron on one atom of its nitrogen bridge and has a strong absorption band at approximately 517 nm [27,34]. Hydroxyl radical (•OH) has free access to cell membranes and causes tissue damage. Thus, scavenging ·OH may avoid tissue injury [4,35]. The DPPH·, ABTS·, and •OH RSR of the EPS and Vc significantly increased with increasing concentrations ($p \leq 0.05$, Figure 6a–c). The RSR (DPPH•, ABTS•, and •OH) of EPS increased from $37.12\%$ to $73.33\%$, $9\%$ to $87.74\%$, and $7.53\%$ to $46.07\%$ at 2–10 mg/mL concentrations. Miao et al. [ 36] reported that the RSR of DPPH· was $40\%$ for EPS at 5.0 mg/mL, which supported the results of this study. Results showed that the RSR of DPPH· and ABTS· was higher than that of OH. The FRP of EPS-MC5 significantly increased at 2–10 mg/mL ($p \leq 0.05$, Figure 6d). The highest FRP value of the EPS was 1.24 at 10 mg/mL, which suggested that the EPS not only acted as an electrons donor to directly react with free radicals but also performed antioxidant activity by other mechanisms, for instance, chelating with transition metal ion catalysts [37]. The FRP of EPS from L. plantarum LP6 was 0.632 [35], which was close to the EPS-MC5 in this study. The research results of Li [38] also showed that EPS may exert antioxidant activity through multiple mechanisms, such as blocking chain initiation, binding to the transition metal ion catalysts, and decomposing peroxides. ## 2.8.1. Apparent Viscosity of EPS-MC5 EPS concentration, processing temperature, pH, and metal ions all affect the rheological properties of EPS [39]. The apparent viscosity decreased gradually with increasing shear rate. When the shear rate increased from 3.24/s to 60/s, the apparent viscosity of the EPS decreased from 3.01 to 0.45 Pa (Figure 7a), which may be due to the disruption of intermolecular interactions and the breaking of bonds between various structural units with the increase of shear rate [39]. EPS from both L. plantarum C70 [40] and YW11 [26] also exhibited this shear thinning property. When the shear rate was greater than 60/s, the apparent viscosity decreased slowly and finally stabilized. In addition, the apparent viscosity of EPS-MC5 decreased rapidly with the increasing shear temperature (Figure 7b). When the shear temperature was 25–60 °C, the apparent viscosity of EPS decreased from 2.44 to 0.29 Pa, while when continuing to increase the temperature, the apparent viscosity of the EPS remained the same. The shear stress of EPS-MC5 formed a thixotropic ring, indicating that the EPS was a thixotropic system (Figure 7c). The thixotropic ring of the EPS was large, indicating that the EPS had large stress under the action of external force. When the shear rate was 3.24–200/s, the stress of EPS-MC5 increased from 9.93 to 41.78 Pa. ## 2.8.2. Viscoelastic Properties of EPS-MC5 Viscoelasticity is one of the important processing characteristics of EPS [40]. The elastic modulus (G’) was generally higher than the viscous modulus (G”, Figure 7d), indicating that the EPS itself formed a gel structure and had elastic and solid-like characteristics. With the increasing frequency (0.1–100 Hz), the viscoelasticity modulus of EPS-MC5 increased from 19.81 to 161.02 and 9.63 to 84.02 Pa, respectively. This showed that the work done by the outside world on EPS aggregates increased at high frequencies. However, the viscoelasticity of EPS-M41 at 0.1–10 Hz was 1.0 × 10−5–1.0 Pa [40], which was lower than that of EPS-MC5 in this study. These differences may be due to the different molecular weights, glycosidic bond type, monosaccharide composition, functional groups, and substituents [41]. ## 3.1. Materials The strain Lp. plantarum MC5 was isolated from traditional fermented yak milk samples, in Tibetan areas of Gansu, China. Strain MC5 was identified by 16S rRNA sequencing and whole genome sequencing. Lp. plantarum MC5 was maintained in MRS agar dishes at 4 °C for immediate use and prepared to skim milk and glycerol stocks for a long time of preservation in a deep freezer (−80 °C). α-amylase (8 U/mg) was supplied by Shanghai Macklin Biochemical Co., Ltd. (Shanghai, China). Pepsin and Trypsin were supplied by Beijing Solebro Science and Technology Co., Ltd. (Beijing, China). All reagents used were of analytical grade. MRS broth [42]: peptone (10 g/L), beef extracts (10 g/L), yeast extract (5 g/L), glucose (25 g/L), Tween 80 (1 mL/L), K2HPO4 (2 g/L), sodium acetate (5 g/L), diammonium hydrogen citrate (2 g/L), MgSO4 (0.2 g/L), MnSO4 (0.08 g/L), and agar (15 g/L). It was sterilized at 121 °C for 20 min. ## 3.2. Isolation and Determination of EPS-MC5 Lp. plantarum MC5 was cultured in MRS broth for 24 h, and the supernatant was collected after centrifugation. The supernatant was mixed with $80\%$ (w/v) trichloroacetic acid (TCA), allowed to stand at 4 °C for 24 h, and then centrifuged again. The supernatant was collected, mixed with $95\%$ alcohol (3:1 v/v), and allowed to stand again at 4 °C for 24 h. The mixture was centrifuged, and the pellet was suspended in deionized water and dialyzed at 4 °C for 2 days using dialysis bags (molecular weights of 8–14 kDa). The total sugar content was detected using phenol-sulfate acid method [28]. Briefly, 0.1 g EPS was dissolved in 100 mL of distilled water, and 1 mL EPS solution was mixed well with 1 mL $6\%$ (w/v) phenol solution and 5 mL $98\%$ (w/v) H2SO4, shaken for 10 min, and the absorbance was determined at 490 nm. 3,5-dinitro salicylic acid (DNS) method was utilized to detect the reducing sugar content [43]. A total of 2 mL distilled water and 1.5 mL DNS solution were added to 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, and 1.4 mL of 1.0 mg/mL glucose standard solution, respectively. They were shaken well and heated in a 100 °C water bath for 5 min. Then we adding distilled water to make up to 25 mL, and the absorbance was determined at 520 nm. EPS content (mg/L)=The total sugar content −The reducing sugar content ## 3.3. Purification of EPS-MC5 The EPS was purified by using the method of Zhang et al. [ 25]. The crude EPS solution (20 mg/mL, 5 mL) was fractionated with an anion exchange chromatography on a DEAE Sepharose Fast Flow column (16 mm × 25 cm), eluted with deionized water, 0.1, 0.2, 0.3, 0.4, and 0.5 Mol/L NaCl solution at a flow rate of 1 mL/min. Every 7 mL elution was collected automatically and the EPS content was determined by the phenol-sulfuric acid method. Peak fractions containing EPS were pooled, dialyzed, and lyophilized. ## 3.4.1. Effects of Inoculation Size on EPS Production from Lp. plantarum MC5 Lp. plantarum MC5 was inoculated in MRS broth (pH 6.4). The inoculation size of strains Lp. plantarum MC5 was $1\%$, $2\%$, $3\%$, $4\%$, and $5\%$, respectively. They were incubated at 37 °C for 24 h. EPS production was determined by the method in Section 2.2. ## 3.4.2. Effects of Culture Time on EPS Production from Lp. plantarum MC5 Lp. plantarum MC5 was inoculated into MRS broth (pH 6.4). The Lp. plantarum MC5 were incubated at 37 °C for 12, 18, 24, 30, and 36 h, respectively. The method of determining EPS production was the same as above. ## 3.4.3. Effects of Culture Temperature on EPS Production from Lp. plantarum MC5 Lp. plantarum MC5 was inoculated into MRS broth (pH 6.4). The Lp. plantarum MC5 were incubated at 31 °C, 34 °C, 37 °C, 40 °C, and 43 °C for 24 h, respectively. The method of determining EPS production was the same as above. ## 3.4.4. Effect of Initial pH Value on EPS Production from Lp. plantarum MC5 Lp. plantarum MC5 was inoculated into MRS broth. The initial pH values of the medium were adjusted to 5.6, 6.0, 6.4, 6.8, and 7.2, respectively, which were incubated at 37 °C for 24 h (inoculation size $4\%$). The method of determining EPS production was the same as above. ## 3.5. Optimization of Lp. plantarum MC5 EPS Culture Conditions by Response Surface Using Design Expert 8.0.6.1 Box–Behnken Design (BBD) software to design experiments and analyze the experimental data. The second-order response surface model was obtained by fitting, and the optimal conditions were determined. BBD was experimented to optimize the four variables (inoculation size, incubation time, incubation temperature, and initial pH) screened by single factor experiments and designed as A, B, C, and D. The four independent variables were investigated at three levels with 29 experimental runs and 5 repetitive central points. The experiments were carried out in triplicates. The 3D graphic plots obtained by the software would illustrate reciprocal interactions between each significant factor [4]. ## 3.6.1. The Resisting-Digestion Capacity of EPS-MC5 to α-Amylase (RCA) The RDCA of EPS-MC5 was performed as described by Al-Sheraji et al. [ 44]. A total of 500 mg EPS was dissolved with 50 mL PBS buffer (pH 6.8), and a-amylase was added to the EPS solution to a final concentration of 8 U/mL. The solution was reacted in a water bath at 37 °C for 180 min. The released reducing sugar content of EPS solution was determined every 30 min, which was detected by the DNS method. The initial total sugar was detected by the phenol-sulfuric acid method. The resisting-digestion capacity (RC) was calculated according to the formula:RC(%)=(1−Hydrolyzed reducing sugar contentTotal sugar content−Initial reducing sugar content)×$100\%$ ## 3.6.2. The Resisting-Digestion Capacity of EPS-MC5 to Simulated Gastric Juice Artificial simulated gastric juice [45]: 3.0 g pepsin was fully dissolved in 300 mL normal saline, and divided into 3 equal parts. Then, the three solutions were adjusted the pH to 2.0, 3.0, and 4.0 with HCl (2 Mol/L), respectively. Finally, the three solutions were filtered and sterilized by using a microporous membrane (0.22 μm). A total of 500 mg EPS-MC5 was added to 50 mL of simulated gastric juice with pH 2, 3, and 4, respectively. The three solutions were reacted in a water bath at 37 °C for 180 min. The released reducing sugar content of the EPS solution was determined every 30 min [30]. The calculation formula of the RC was the same as in Section 3.6.1. ## 3.6.3. The Resisting-Digestion Capacity of EPS-MC5 to Simulated Intestinal Juice Artificial simulated intestinal juice [46]: Ox bile salt (3.0 g), ox bile juice (1.0 g), and trypsin (2.0 g) were added in PBS buffer (500 mL pH 6.0). Then, the solution was adjusted the pH to 6.8 with NaOH (2 Mol/L). Finally, the solutions were filtered with a microporous membrane (0.22 μm) for later use. A total of 500 mg EPS-MC5 was added to 50 mL of simulated intestinal juice with pH 6.8. The solutions were reacted in a water bath at 37 °C for 180 min. The released reducing sugar content of the EPS solution was determined every 30 min [30]. The calculation formula of the RC was the same as in Section 3.6.1. ## 3.7.1. The Radical Scavenging Rate (RSR) of DPPH RSR of DPPH free radical was assayed by El-Dein’ method [28]. A total of 2 mL of EPS solution (2, 4, 6, 8, and 10 mg/mL) was mixed with 2 mL 0.1 mMol/L DPPH solution. Then, the mixture was placed in the dark at room temperature for 30 min. The absorbance of the supernatant was determined at 517 nm after centrifugation (Aj), and ascorbic acid was used as a positive control. The RSR of DPPH free radical was calculated by the equation as follows:Scavenging activity(%)=(1−Aj−AiA0)×$100\%$ Aj: Absorbance of EPS solution (2 mL) + $95\%$-DPPH ethanol solution (2 mL); Ai: Absorbance of EPS solution (2 mL) + $95\%$ ethanol solution (2 mL); A0: Absorbance of $95\%$-DPPH ethanol solution (2 mL) + $95\%$ ethanol solution (2 mL). ## 3.7.2. The Radical Scavenging Rate (RSR) of ABTS ABTS solution was prepared by mixing equal volumes of ABTS (7 mMol/L) and potassium persulfate solutions (2.45 mMol/L), and the mixture was placed in the dark for 16 h [4]. The ABTS solution was diluted by PBS solution (0.2 M, pH 7.4) to an absorbance of 0.70 ± 0.02 at 734 nm before use. A total of 600 uL of EPS solution (2, 4, 6, 8, and 10 mg/mL) was added into 3 mL ABTS solution. Then, the mixture was incubated for 10 min in dark at room temperature. The absorbance of the mixture solution was determined at 734 nm (Aj), and ascorbic acid was used as a positive control. The RSA of ABTS was calculated using:Scavenging activity(%)=(1−Aj−AiA0)×$100\%$ Aj: Absorbance of EPS solution (600 uL) + ABTS solution (3 mL); Ai: Absorbance of EPS solution (600 uL) + deionized water (3 mL); A0: Absorbance of deionized water (600 uL) + ABTS solution (3 mL). ## 3.7.3. The Radical Scavenging Rate (RSR) of Hydroxyl The RSR of Hydroxyl (OH) was investigated by the method of Zhang [25] with slight modifications. One mL of EPS solution (2, 4, 6, 8 and 10 mg/mL) was mixed with 1.8 mM FeSO4 (2 mL), 1.8 mM salicylic acid (1.5 mL) and $0.3\%$ H2O2 (2 mL). After 30 min of standing at 37 °C and centrifugation (8000 rpm, 5 min), the absorbance of the supernatant was measured at 510 nm. Ascorbic acid was used as a positive control. The RSA of OH was calculated using:Scavenging activity(%)=(1−Aj−AiA0)×$100\%$ Aj: Absorbance of EPS solution + H2O2; Ai: Absorbance of deionized water + H2O2; A0: Absorbance of salicylic acid was replaced by deionized water. ## 3.7.4. The Ferric-Iron Reducing Power (IRP) of EPS-MC5 The IRP of EPS was determined according to the method of Wang [47] with some modifications. Briefly, 1 mL of EPS solution (2, 4, 6, 8 and 10 mg/mL) was mixed with 2.5 mL phosphate buffer (0.2 Mol/L, pH 6.6) and 2.5 mL potassium ferricyanide ($1\%$, w/v), and the mixture was incubated at 50 °C for 20 min. After adding 2.5 mL trichloroacetic acid ($10\%$, w/v), the mixture was centrifuged at 8000 rpm for 5 min. A total of 2.5 mL of supernatant was collected and mixed with 2.5 mL distilled water and 0.5 mL FeCl3 ($0.1\%$, w/v). The absorbance was measured at 700 nm after 10 min. The IRP of EPS was calculated using:OD =Absorbance of sample ## 3.8.1. The Preparation of the EPS-MC5 Samples Lp. plantarum MC5 was cultured in MRS broth for 30 h, and the supernatant was collected after centrifugation. The supernatant was mixed with $80\%$ (w/v) trichloroacetic acid (TCA), and allowed to stand at 4 °C for 24 h. The supernatant was collected after centrifugation again, mixed with $95\%$ alcohol (3:1 v/v), and allowed to stand again at 4 °C for 24 h. The EPS-MC5 samples were obtained after centrifugation. ## 3.8.2. Apparent Viscosity and Flow Curves of EPS-MC5 The apparent viscosity and shear stress were determined according to Ayyash’s method [40]. Apparent viscosity and shear stress of the EPS-MC5 samples were determined using an MCR301 Rheometer. The samples were linearly sheared at a constant temperature of 25 ± 1 °C. They were performed in the shear rate range of 0.1 to 200/s. The measurement time was 1 min. In addition, the apparent viscosity of EPS-MC5 was analyzed as a function of temperature from 25 °C to 80 °C. The temperature ramp rate was 1 °C/min at a constant shear rate of 20/s. ## 3.8.3. Amplitude and Frequency Sweep Tests of EPS-MC5 The viscoelasticity of the EPS-MC5 samples was measured by using an MCR301 Rheometer [48]. The frequency sweep test was used to evaluate viscoelasticity of the EPS-MC5 under the condition of $5\%$ strain force and frequency of 0.1–100 Hz. ## 3.9. Statistical Analysis All the experiments were carried out in triplicate. The response surface analysis was obtained by using Design-Expert 8.0.6.1 software. The relative standard error and the mean values were calculated using SPSS 22.0 (Statistical Package for the Social Sciences, Chicago, IL, USA). ANOVA tests were done to a determination of significant differences between treatments with a level of significance of $p \leq 0.05$ by the SPSS 22.0 package program. The obtained pictures were carried out according to the Origin 8.0 software (Statistical Package for the Social Sciences, Northampton, MA, USA). ## 4. Conclusions In this study, the optimal EPS-producing conditions (the inoculum size of $4.0\%$, the culture time of 30 h, the culture temperature of 34.0 °C, and the initial pH value of 6.40) and the maximum EPS yield (345.81 mg/L) of Lp. plantarum MC5 were obtained. The resistance of EPS-MC5 to human simulated digestive juices (α-amylase, simulated gastric and intestinal juices) was significantly higher than FOS ($p \leq 0.05$), indicating that EPS-MC5 could reach the gastrointestinal tract smoothly when entering the human body. The EPS-MC5 also had high antioxidant activity and could scavenge a variety of radicals (DPPH•, ABTS•, and •OH), which indicated that it exerted antioxidant activity through multiple pathways. In addition, EPS demonstrated good apparent viscosity and viscoelasticity, indicating that it had good processing characteristics. In conclusion, the EPS-MC5 was a potential active polysaccharide that could regulate human health and can be used in the food processing industry. However, the structural characterization and beneficial nature in vivo of the EPS-MC5 need further study. ## References 1. Faghfoori Z., Gargari B.P., Gharamaleki A.S., Bagherpour H., Khosroushahi A.Y.. 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--- title: Application of Minimal Physiologically-Based Pharmacokinetic Model to Simulate Lung and Trachea Exposure of Pyronaridine and Artesunate in Hamsters authors: - Dong Wook Kang - Kyung Min Kim - Ju Hee Kim - Hea-Young Cho journal: Pharmaceutics year: 2023 pmcid: PMC10058671 doi: 10.3390/pharmaceutics15030838 license: CC BY 4.0 --- # Application of Minimal Physiologically-Based Pharmacokinetic Model to Simulate Lung and Trachea Exposure of Pyronaridine and Artesunate in Hamsters ## Abstract A fixed-dose combination of pyronaridine and artesunate, one of the artemisinin-based combination therapies, has been used as a potent antimalarial treatment regimen. Recently, several studies have reported the antiviral effects of both drugs against severe acute respiratory syndrome coronavirus two (SARS-CoV-2). However, there are limited data on the pharmacokinetics (PKs), lung, and trachea exposures that could be correlated with the antiviral effects of pyronaridine and artesunate. The purpose of this study was to evaluate the pharmacokinetics, lung, and trachea distribution of pyronaridine, artesunate, and dihydroartemisinin (an active metabolite of artesunate) using a minimal physiologically-based pharmacokinetic (PBPK) model. The major target tissues for evaluating dose metrics are blood, lung, and trachea, and the nontarget tissues were lumped together into the rest of the body. The predictive performance of the minimal PBPK model was evaluated using visual inspection between observations and model predictions, (average) fold error, and sensitivity analysis. The developed PBPK models were applied for the multiple-dosing simulation of daily oral pyronaridine and artesunate. A steady state was reached about three to four days after the first dosing of pyronaridine and an accumulation ratio was calculated to be 1.8. However, the accumulation ratio of artesunate and dihydroartemisinin could not be calculated since the steady state of both compounds was not achieved by daily multiple dosing. The elimination half-life of pyronaridine and artesunate was estimated to be 19.8 and 0.4 h, respectively. Pyronaridine was extensively distributed to the lung and trachea with the lung-to-blood and trachea-to-blood concentration ratios (=Cavg,tissue/Cavg,blood) of 25.83 and 12.41 at the steady state, respectively. Also, the lung-to-blood and trachea-to-blood AUC ratios for artesunate (dihydroartemisinin) were calculated to be 3.34 (1.51) and 0.34 (0.15). The results of this study could provide a scientific basis for interpreting the dose–exposure–response relationship of pyronaridine and artesunate for COVID-19 drug repurposing. ## 1. Introduction Drug repurposing is a rapid and safe method to determine a new usage of approved drugs in a cost-effective way [1]. In numerous cases, preclinical studies and clinical trials of repurposed drugs could be immediately started, thus accelerating drug approval with reduced time, costs, and risks [2]. The need for treatments against COVID-19 led researchers to utilize drug repurposing of approved drugs [3]. Artemisinin-based combination therapies (ACTs) are generally used to treat Plasmodium falciparum malaria, and World Health Organization (WHO) recommended ACTs as the first line of antimalarial therapy [4]. The fixed-dose combination of pyronaridine–artesunate which is one of the ACTs that was approved in Europe, Asia, and Africa for the treatment of uncomplicated malaria, and it is sold under the brand name Pyramax® and Artecom® with a 3:1 ratio of pyronaridine to artesunate. Recently, several articles have reported the antisevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) effect of antimalarial drugs including pyronaridine, artesunate, and dihydroartemisinin (the active metabolite of artesunate) in vitro and in vivo [5]. Gendrot et al. investigated the in vitro anti-SARS-CoV-2 activity of antimalarial drugs, and pyronaridine exhibited the most effective antiviral effect (EC50 = 0.72 μM; EC90 = 0.75 μM) [6]. Furthermore, the treatment of pyronaridine in SARS-CoV-2 infected mice showed significant inhibition of the viral load in the lungs and suggested that pyronaridine is a potential therapy for COVID-19 [7]. Cao et al. evaluated the in vitro anti-SARS-CoV-2 effect of nine compounds and artemisinin and showed the possibility of inhibiting SARS-CoV-2 replication in a dose-dependent manner [8]. In Call-3 cells, both pyronaridine and artesunate inhibited the growth and viral replication of SARS-CoV-2 and seasonal influenza A in a dose-dependent manner [9]. In addition, the combination therapy of pyronaridine–artesunate (including Pyramax® and Artecom®) has been also investigated to evaluate the efficacy and safety of pyronaridine–artesunate in COVID-19 patients [10]. Lately, several researchers have utilized the physiologically-based pharmacokinetic (PBPK) model for drug repurposing of antiviral agents [11,12,13,14,15]. The PBPK model is a mathematical model describing absorption, distribution, metabolism, and excretion (ADME) based on physiological, physicochemical, and biochemical parameters [16]. The structure of the PBPK model generally consists of multiple tissue compartments and each compartment was connected by organ blood flow [17]. In addition, physiological parameters (cardiac output, tissue volume, etc.), tissue-to-blood partition coefficient, and biochemical parameters (metabolic clearance, renal or biliary clearance, protein binding rate, transporter activity, etc.) were required for developing the PBPK model [16]. The developed PBPK model could be used for predicting PKs, tissue distribution, excretion, etc., and it could provide a scientific basis for performing various extrapolations (species, routes, and dose levels) [18]. Although the PBPK modeling and simulation can provide reasonable predictions, the disadvantage of PBPK modeling is its complexity and accessibility; it depends on the quality of disposition data of the target drug (measurements of numerous organs and tissue concentrations are required) and due to their complexity, PBPK models are difficult to implement rapidly [19]. Due to the limitations of conventional PBPK models, minimal PBPK modeling was proposed as an alternative approach. In the minimal PBPK model, nontarget organs and tissues were lumped together for reducing the complexity of the conventional PBPK model. [ 20]. Thus, a detailed explanation of drug exposures for specific target tissues is possible. Even if several articles have reported the in vitro or in vivo antiviral effects of pyronaridine and artesunate, there are limited data on the pharmacokinetics, lung, and trachea exposure that could be correlated with the antiviral effects. Thus, the purpose of the study was to evaluate the pharmacokinetics, lung, and trachea distribution of pyronaridine, artesunate, and dihydroartemisinin in golden hamsters for drug repurposing as an anti-SARS-CoV-2 treatment. The minimal PBPK models were developed and validated to predict the blood, lung, and trachea exposures of each compound, and the PBPK model was utilized for daily multiple-dosing simulation. The PK parameters, including elimination half-life, accumulation ratio, time to reach a steady state, and average blood, lung, and trachea concentration in the steady state, were evaluated for pyronaridine, artesunate, and dihydroartemisinin. The results of the study could be used as scientific evidence for interpreting the correlation between in vivo exposure and the anti-SARS-CoV-2 activity of pyronaridine and artesunate. ## 2.1. Chemicals and Reagents Pyronaridine tetraphosphate (Lot No. PPNPGA008), artesunate (Lot No. AASTGA006), and dihydroartemisinin (Lot No. ICRS1410) were provided by Shin Poong Pharm. Co., Ltd. (Seoul, Republic of Korea). Amodiaquine, artemisinin, sodium phosphate tribasic dodecahydrate buffer, formic acid, ether, $85\%$ ortho-phosphoric acid, ammonium acetate, and trifluoroacetic acid (TFA) were purchased from Sigma–Aldrich (St. Louis, MO, USA). Acetonitrile, methanol, water, and methyl-tert-butyl ether were purchased from J.T. Baker (Phillipsburg, NJ, USA). All other chemicals and reagents were HPLC or analytical grade. ## 2.2.1. Animals One hundred eight male golden hamsters were obtained from Janvier Lab. ( Le Genest-Saint-Isle, France). All hamsters were maintained on a 12-h dark–light cycle at a temperature of 23 ± 3 °C and relative humidity of 55 ± $15\%$. This study was conducted according to the Guidelines for Ethical Conduct in the Care and Use of Animals and the rules of Good Laboratory Practice and was approved by the Institutional Animal Care and Use Committee (IACUC, protocol number SP2021-14) at Shin Poong Pharm. Co., Ltd. (Seoul, Republic of Korea). ## 2.2.2. Study Design The hamsters (102.01 ± 5.72 g) were divided into two groups: a low-dose group ($$n = 60$$) and a high-dose group ($$n = 48$$). In the low-dose group and high-dose group, $\frac{180}{60}$ mg/kg and $\frac{360}{120}$ mg/kg of pyronaridine/artesunate were administered orally once a day for 3 days to the hamsters. Blood samples (0.5 mL) were drawn from the jugular vein into heparinized tubes at the following times: 0 (predose), 0.08, 0.25, 0.5, 0.75, 1, 2, 4, 8, 12, 24, 47, 48.08, 48.25, 48.5, 48.75, 49, 50, 52, 56, 60, and 72 h during oral administration for 3 days. The blood sampling was conducted 1–3 times per hamster within 72 h, and the tissues were collected after the last blood sampling. The number of animals was four per blood and tissue sampling time point, respectively (each $$n = 4$$). The lung and trachea tissues were immediately obtained after sacrificing hamsters, washed in normal saline, and dried with filter papers. The lung and trachea sampling times were as follows: 0.08, 0.25, 0.5, 0.75, 1, 4, 8, 24, 48.08, 48.25, 48.75, 52, and 72 h. Tissues were individually weighed and homogenized with water (lung or trachea tissue: water = 1:4 w/v). The lung and trachea tissue homogenate were stored at −70 °C until sample analysis. For pyronaridine quantification, whole blood samples were stored at −70 °C until sample analysis. For quantifying artesunate and dihydroartemisinin, blood samples were centrifuged at 4 °C and 3000 rpm for 15 min followed by being transferred into clean tubes to obtain plasma and stored at −70 °C until sample analysis. ## 2.2.3. LC-MS/MS Conditions Liquid chromatography was conducted on the Agilent 1290 Infinity II LC System (Agilent Technologies Inc., Santa Clara, CA, USA) coupled to a 6490 Triple Quad Mass Spectrometer (Agilent Technologies Inc., Santa Clara, CA, USA). A Synergi Max-RP column (2.0 × 75 mm, 4 μm particle size, Phenomenex, Torrance, CA, USA) was used at a temperature of 25 °C. The mobile phase consisted of $0.04\%$ TFA (mobile phase A) and methanol:acetonitrile (3:1 v/v, mobile phase B) with a flow rate of 0.2 mL/min. A gradient elution was used for the chromatographic separation of pyronaridine as follows: 0.0–1.5 min, $10\%$ B; 1.5–1.6 min, 10–$60\%$ B; 1.6–4.0 min, $60\%$ B; 4.0–4.1 min, 60–$10\%$ B; 4.1–50 min, $10\%$ B. The multiple reaction monitoring (MRM) mode was set with a positive electrospray ionization mode. The MRM transitions of pyronaridine and amodiaquine (internal standard, IS) were 518.2 > 447.1 and 356.2 > 283.0. The collision energy of pyronaridine and amodiaquine were 17 and 21 eV, and the cell accelerator voltage was 5 V for both compounds. The quantification of artesunate and dihydroartemisinin was conducted using the Nexera-X2 UPLC system (Shimadzu Corp., Tokyo, Japan) coupled with an LCMS-8040 mass spectrometer (Shimadzu Corp., Tokyo, Japan). Chromatographic separation was performed with an Inertsil ODS column (2.1 × 100 mm, 5 µm particle size, GL Sciences, Tokyo, Japan) column at a temperature of 25 ℃. The mobile phase consisted of 10 mM ammonium acetate (mobile phase A) and acetonitrile (mobile phase B) with an isocratic elution (A:$B = 10$:90, v/v), and a flow rate of 0.2 mL/min. The mass spectrometer was operated on electrospray ionization positive mode. MRM transitions were observed for artesunate (402.05 > 267.10), dihydroartemisinin (302.00 > 267.05), and artemisinin (IS, 299.95 > 283.15). The collision energy of artesunate, dihydroartemisinin, and artemisinin were 11, 9, and 7 eV. ## 2.2.4. Sample Preparation Fifty μL of hamster blood, lung, or trachea tissue homogenates were added with 10 μL of the IS solution (10 μg/mL of amodiaquine). Added to the mixed sample were 125 μL of 0.5 M sodium phosphate tribasic dodecahydrate buffer (pH adjusted to 10.3 with $85\%$ ortho-phosphoric acid) and 500 μL of ether, vortexed for 5 min and centrifuged at 21,130× g for 5 min. Then, 300 μL of supernatant were transferred to new microtubes and dried under nitrogen steam at room temperature. The dried residues were reconstituted with 100 μL of mobile phase ($0.04\%$ TFA:methanol:acetonitrile = 40:45:15, v/v/v) and vortexed for 5 min. After centrifugation at 21,130× g for 5 min, 5 μL of aliquot were injected into the UPLC-MS/MS system. Then, 50 μL of hamster plasma, lung, or trachea tissue homogenates were added with 10 μL of the IS solution (5 μg/mL of artemisinin). Next, 300 μL of acetonitrile were added to the mixture, vortexed for 5 min, and centrifuged at 21,130× g for 5 min. Then, 325 μL of supernatant were transferred to clean microtubes and dried under nitrogen steam at room temperature. The dried residues were reconstituted with 75 μL of mobile phase (10 mM ammonium acetate:acetonitrile = 10:90, v/v) and vortexed for 5 min. After centrifugation at 21,130× g for 5 min, 5 μL of supernatant was injected into the UPLC-MS/MS system. ## 2.3. Development of Minimal Physiologically-Based Pharmacokinetic Models The dispositions of pyronaridine and artesunate in hamsters were described by the minimal PBPK model and the PBPK modeling was performed using WinNonlin software (version 8.3, Certara™, Princeton, NJ, USA). A total of 530 measurements (343 for pyronaridine; 60 for artesunate; 127 for dihydroartemisinin) from 108 hamsters were used for the minimal PBPK modeling. The model consisted of five compartments including the absorption compartment, blood, lung, trachea, and the rest of the body. Also, nontarget tissues were lumped together into the rest of the body following the EPA guidance [16]. The equations describing the PKs, lung, and trachea distribution of pyronaridine were as follows:Minimal PBPK model for pyronaridine dAadt=−ka×AadAblooddt=ka×Aa+Clung×QcoKlung+Ctrachea×QtracheaKtrachea+Crest×QrestKrest−Cblood×Qco−Cblood×Qtrachea−Cblood×Qrest−Cblood×CL/FdAlungdt=Cblood×Qco−Clung×QcoKlung+Atrachea×ktl−Alung×kltdAtracheadt=Cblood×Qtrachea−Ctrachea×QtracheaKtrachea+Alung×klt−Atrachea×ktldArestdt=Cblood×Qrest−Crest×QrestKrestCblood=AbloodVblood,Clung=AlungVlung,Ctrachea=AtracheaVtrachea where Aa, Ablood, Alung, Atrachea, and Arest are the amount of pyronaridine in the absorption compartment, blood, lung, trachea, and the rest of the body, respectively. Cblood, Clung, and Ctrachea are blood, lung, and trachea concentrations of pyronaridine, respectively. Vblood, Vlung, and Vtrachea are the physiological volumes for blood, lungs, and tracheas of hamsters, respectively. Qco is the cardiac output of hamsters. Qtrachea and Qrest are the blood flow rates for the trachea and the rest of the body, respectively. The first-order rate constants for absorption, trachea-to-lung transfer, and lung-to-trachea transfer are ka, ktl, and klt. Klung, Ktrachea, and Krest are lung-to-blood, trachea-to-blood, and the rest of the body-to-blood partition coefficient, respectively. CL/F is the apparent total clearance of pyronaridine. The minimal PBPK model was also developed for artesunate and its active metabolite (dihydroartemisinin). The model structure and parameters were similar to those of pyronaridine, and the parent PBPK model of artesunate was connected to the metabolite PBPK model of dihydroartemisinin as follows:Parent-metabolite PBPK model for artesunate dAadt=−ka×AadAblooddt=ka×Aa+Clung×QcoKlung+Ctrachea×QtracheaKtrachea+Crest×QrestKrest−Cblood×Qco−Cblood×Qtrachea−Cblood×Qrest−Cblood×CL/FdAlungdt=Cblood×Qco−Clung×QcoKlung+Atrachea×ktl−Alung×kltdAtracheadt=Cblood×Qtrachea−Ctrachea×QtracheaKtrachea+Alung×klt−Atrachea×ktldArestdt=Cblood×Qrest−Crest×QrestKrestCplasma=CbloodKb:p, Cblood=AbloodVblood, Clung=AlungVlung, Ctrachea=AtracheaVtrachea dAblood,mdt=Cblood×CL/F+Clung,m×QcoKlung,m+Ctrachea,m×QtracheaKtrachea,m+Crest,m×QrestKrest,m−Cblood,m×Qco−Cblood,m×Qtrachea−Cblood,m×Qrest−Cblood,m×CLm/FdAlung,mdt=Cblood,m×Qco−Clung,m×QcoKlung,m+Atrachea,m×ktl,m−Alung,m×klt,mdAtrachea,mdt=Cblood,m×Qtrachea−Clung,m×QtracheaKlung,m+Alung,m×klt,m−Atrachea,m×ktl,mdArest,mdt=Cblood,m×Qrest−Crest,m×QrestKrest,mCplasma,m=Cblood,mKb:p,m, Cblood,m=Ablood,mVblood, Clung,m=Alung,mVlung, Ctrachea,m=AtracheaVtrachea where Aa, Ablood, Alung, Atrachea, and Arest are the amount of artesunate in the absorption compartment, blood, lung, trachea, and the rest of the body, respectively. Ablood,m, Alung,m, Atrachea,m, and Arest,m are the amount of dihydroartemisinin in the blood, lung, trachea, and rest of the body, respectively. Cplasma, Cblood, Ctrachea, and Clung are plasma, blood, trachea, and lung concentrations of artesunate, respectively. Cplasma,m, Cblood,m, Ctrachea,m, and Clung,m are plasma, blood, trachea, and lung concentrations of dihydroartemisinin, respectively. Vblood, Vlung, and Vtrachea are the physiological volumes for blood, lung, and trachea of hamsters, respectively. Qco is the cardiac output of hamsters. Qtrachea and Qrest are the blood flow rates for the trachea and the rest of the body, respectively. The first-order absorption rate constant is ka, and ktl and klt are the first-order rate constants for trachea-to-lung and lung-to-trachea transfer of artesunate. The first-order rate constants for trachea-to-lung and lung-to-trachea transfer of dihydroartemisinin are ktl,m and klt,m. Kb:p, Klung, Ktrachea and Krest are blood-to-plasma, lung-to-blood, trachea-to-blood, and the rest of the body-to-blood partition coefficient for artesunate, respectively. Kb:p,m, Klung,m, Ktrachea,m and Krest,m are blood-to-plasma, lung-to-blood, trachea-to-blood, and the rest of the body-to-blood partition coefficient for dihydroartemisinin, respectively. CL/F and CLm/F are the apparent total clearance of artesunate and dihydroartemisinin, respectively. The structures of the minimal PBPK models for pyronaridine and artesunate are shown in Figure 1a and 1b. In the minimal PBPK models of both pyronaridine and artesunate, a perfusion rate-limited kinetics with tissue-to-blood partition coefficient [21] was used to describe the equilibrium between blood and tissue concentrations of each drug (Figure 1c). The physiological parameters of hamsters that were used to develop the minimal PBPK models of pyronaridine and artesunate are represented in Table 1. The blood volume (Vblood) and cardiac output (Qco) of hamsters that were reported in the literature were used for the PBPK model development [22,23]. The blood flow rate for the trachea (Qtrachea) was calculated by multiplying Qco by $2.1\%$ [24,25,26]. The blood flow rate for the rest of the body (Qrest) was calculated by subtracting Qtrachea from Qco. The average lung and trachea volumes (Vlung and Vtrachea) were calculated from the individual lung and trachea weights of hamsters assuming the unit density (1 mL = 1 g) [16]. The volume of the rest of the body (Vrest) was calculated by subtracting blood volume (Vblood), lung volume (Vlung), and trachea volume (Vtrachea) from the total body volume (102.01 mL) of the hamsters. Also, the reported values of blood-to-plasma partition coefficients for artesunate (Kb:p) and dihydroartemisinin (Kb:p,m) were used to calculate the blood concentrations from the plasma concentrations of both compounds. All physiological parameters were fixed, and biochemical parameters were fitted to develop the minimal PBPK model. A sensitivity analysis was performed for a quantitative evaluation of how model parameters (input parameters) influence the model predictions [16,17]. In this study, a normalized sensitivity analysis was conducted on the minimal PBPK models of pyronaridine and artesunate. The influence of model parameters on predicted blood concentrations was evaluated by using the Cmax and AUC resulting from increasing each parameter by $1\%$. The normalized sensitivity coefficients were calculated by original and changed parameters as the following equations [27,28]:Normalized sensitivity coefficient=A−BBC−DD where A is the AUC calculated from the $1\%$ increase in the biochemical parameter, B is the Cmax and AUC calculated from the original biochemical parameter, C is the increased biochemical parameter by $1\%$, and D is the original biochemical parameter. The normalized sensitivity coefficient of 1 means a 1:1 relationship between parameter changes and dose metric. If the normalized sensitivity coefficient was calculated to be 2, a $1\%$ change in the input parameter results in a $2\%$ change in Cmax or AUC. The normalized sensitivity coefficients were calculated from all biochemical parameters and those higher than 1 were considered to amplify the input error [16,29]. Also, the PK parameters (Cmax, AUCDay1, and AUCDay3) estimated from the observed and predicted concentrations of the three compounds were compared for evaluating overall model performance and calculating a fold error (FE) and average fold error (AFE) as follows [30,31,32,33]:Fold error FE=PpredPobs Average fold error AFE=10∑logFEn where Ppred is the estimated PK parameters from the model prediction and Pobs is the estimated PK parameters from the observed concentrations, and n is the number of samples. The validated minimal PBPK models were applied for the multiple-dosing simulation. PK profiles for the multiple oral dosing of pyronaridine–artesunate with either low or high doses ($\frac{180}{60}$ or $\frac{360}{120}$ mg/kg) once a day for 3 or 14 days were simulated in hamsters. An elimination half-life, accumulation ratio, time to reach a steady-state, and average lung, trachea, or blood concentration in the steady-state were evaluated using the simulated profiles of pyronaridine, artesunate, and dihydroartemisinin. The predictive performance of the minimal PBPK model was examined by comparing the observed and simulated concentrations in blood, lung, and trachea. The agreement of observed and simulated PK profiles was graphically evaluated. ## 2.4. Parameters Estimation A noncompartmental analysis (NCA) was used to estimate the model-independent PK parameters. The elimination rate constant (ke) was estimated by linear regression analysis and the elimination half-life (t$\frac{1}{2}$) was divided ln 2 by ke. The maximum plasma concentration (Cmax) and time to maximum concentration (Tmax) were obtained by a visual observation of the plasma concentration time profiles. The area under the plasma concentration time curve from zero to time t (AUCt) was calculated using a linear trapezoidal method. The average plasma concentration at a steady state (Cavg) in a repeated dosing simulation was calculated by dividing the AUCτ by the dosing interval (τ). The accumulation ratio was calculated using the ratio of the AUC0-24 hr at day 1 and AUCτ at a steady-state in multiple-dosing PK profiles. ## 3.1. Pharmacokinetics, Lung, and Tissue Distribution of Pyronaridine and Artesunate Since pyronaridine was uptaken by red blood cells and showed a high blood-to-plasma ratio (4.9–17.8), whole blood was selected as the biological matrix for the quantification of pyronaridine [34]. The blood-to-plasma ratios of artesunate and dihydroartemisinin were reported to be 0.75, suggesting that plasma rather than whole blood is the preferred matrix [21]. Thus, the plasma concentrations (Cplasma) of artesunate and dihydroartemisinin were first quantified, and the blood concentrations were calculated by multiplying Cplasma by Kb:p. A naïve pooled-data approach was used for both NCA and PBPK modeling since the sparse sampling was required to obtain blood, plasma, lung, and trachea samples in hamsters [35]. The blood, lung, and trachea PK profiles after daily multiple dosing of pyronaridine (180 or 360 mg/kg) are shown in Figure 2. After the single dosing, the Tmax was estimated to be 2–4 h, and Cmax was calculated to be 2701.6 and 4542.4 ng/mL for the low- and high-dose groups, respectively. The calculated AUCDay1 was estimated to be 24,134.4 and 51,016.0 h·ng/mL for the low- and high-dose groups, respectively. The calculated AUCDay3 was estimated to be 57,084.6 and 84,867.9 h·ng/mL for the low- and high-dose groups, respectively. The lung and trachea exposures of pyronaridine were higher than blood exposures from the graphical evaluation for both low- and high-dose groups. The majority of pyronaridine was distributed to the lung and trachea with high average exposure ratios of 25.5 and 7.17 for the lung-to-blood AUC ratio (=AUClung/AUCblood) and trachea-to-blood AUC ratio (=AUCtrachea/AUCblood) on day one. Also, lung-to-blood and trachea-to-blood AUC ratios of pyronaridine were calculated to be 51.00 and 16.60 on day three. The observed blood concentrations of artesunate and dihydroartemisinin in the low- and high-dose groups are shown in Figure 3. An absorption phase of artesunate could not be obtained from all dose groups since artesunate immediately entered the systemic circulation. Also, both artesunate and dihydroartemisinin were all eliminated within about 2 h, and the accumulation was not caused by the dosing interval of 24 h. This result agrees with the previous report that describes peak concentrations being achieved rapidly (less than five minutes) for both compounds, and artesunate concentrations were decreased below the quantification limit in 2 h with no accumulation [36]. ## 3.2. Development of Minimal Physiologically-Based Pharmacokinetic Models For accurate predictions of systemic, lung, and trachea exposure, the minimal PBPK models were developed using the observed PK profiles of pyronaridine, artesunate, and dihydroartemisinin. The minimal PBPK models in this study were modified from Jermain et al., which reported the minimal PBPK model of ivermectin for COVID-19 drug repurposing [11]. Since the target organ for the antiviral effects of pyronaridine and artesunate were the lung and trachea, the nontarget tissues were lumped together into the rest of the body. The physiological parameters (Qco, Qtrachea, Qrest, Vblood, Vlung, Vtrachea, and Vrest) were fixed from the literature or measured from animal experiments. Generally, each tissue compartment in the PBPK model is described by either perfusion rate-limited kinetics or permeability rate-limited kinetics. In the perfusion rate-limited kinetics, it is assumed that the drug immediately across the membranes and tissue-to-blood concentrations in equilibrium are determined by the Kp value (typically for small lipophilic molecules) [37]. Contrarily, if the permeability becomes the rate-limiting process (e.g., large polar molecules), the tissue compartment should be divided into extracellular and intracellular spaces, that are separated by a diffusional barrier [38]. In the European Medicines Agency (EMA) assessment report, artesunate and dihydroartemisinin were reported to follow perfusion rate-limited kinetics with a high extraction ratio [39]. Furthermore, since pyronaridine is a lipophilic compound that represents slow elimination and extensive distribution, the perfusion rate-limited kinetics were used for developing the minimal PBPK models [40]. According to the EMA report, artesunate is rapidly metabolized to dihydroartemisinin by blood esterases. Thus, artesunate is generally considered a prodrug of dihydroartemisinin [36,39]. Also, artesunate was reported to be almost completely metabolized to dihydroartemisinin in vivo [41]. Therefore, artesunate was modeled to be thoroughly converted to dihydroartemisinin in the blood compartment by the CL/F, and the rate of dihydroartemisinin produced was described by multiplying the artesunate concentration and CL/F. The biochemical parameters of pyronaridine, artesunate, and dihydroartemisinin were summarized in Table 2. The lung-to-blood partition coefficient (Klung) and trachea-to-blood partition coefficient (Ktrachea) were estimated to be 26.06 and 8.67 for pyronaridine, respectively. These values were similar to the tissue-to-blood AUC ratio (=AUCtissue/AUCblood) calculated from the observed PK profiles of pyronaridine on day one. The Klung and Klung,m for artesunate and dihydroartemisinin were estimated to be 10.33 and 0.34, respectively. Although not higher than pyronaridine, artesunate showed high lung distribution while dihydroartemisinin was less distributed in the lung than that in the blood (Klung,m < 1). The Ktrachea and Ktrachea,m for artesunate and dihydroartemisinin were estimated to be 1.48 and 1.08, respectively. Also, the results of the sensitivity analysis (Figure 4) showed that normalized sensitivity coefficients for all parameters were within one, and most parameters were close to zero. Thus, the input error was considered to be not significantly amplified in the model output. The fold errors (FEs) for Cmax, AUCDay1, and AUCDay3 for the three compounds were calculated to evaluate the accuracy of the model predictions (Figure 5). The percentage of PK parameters that were within a twofold error was $100\%$ for Cmax, $91\%$ for AUCDay1, and $75\%$ for AUCDay3, respectively. The average fold errors (AFEs) for Cmax, AUCDay1, and AUCDay3 were calculated to be 0.84, 0.94, and 0.86, respectively. Most of the FEs and all of the AFEs for PK parameters were under the twofold limit, suggesting the good predictive performances of the minimal PBPK models. ## 3.3. Application of Minimal Physiologically-Based Pharmacokinetic Models Using the developed minimal PBPK models of pyronaridine and artesunate, the multiple-dosing simulations for low and high doses were conducted. Table 3 summarizes the PK parameters of pyronaridine, artesunate, and dihydroartemisinin estimated from the simulated PK profiles. The simulated PK profiles for pyronaridine were represented together with observed concentrations in Figure 6. In the simulated profiles of pyronaridine, the t$\frac{1}{2}$ was estimated to be 19.7–19.9 h. The elimination half-life can be used for the prediction of the drug accumulation and time to reach steady-state equilibrium [42]. The time to reach the steady state is dependent only on the elimination half-life [43,44]. The pharmacological rule states the steady state is achieved after four to five times of the elimination half-life [42,45,46]. Thus, since the t$\frac{1}{2}$ of pyronaridine was calculated to be 19.7–19.9 h, the steady state can be reached in about three to four days (79–100 h) after the first dosing. The elimination half-life of pyronaridine has not been reported in hamsters, while it has been reported to be two to four days in rats and 2.5 days in dogs, respectively [39]. The blood AUCDay1 was calculated to be 32,508.2 and 50,672.1 hr·ng/mL for the low- and high-dose groups, and the blood AUCτ in the steady state was calculated to be 57,189.7 and 89,639.9 for the low- and high-dose groups, respectively. The accumulation ratio of pyronaridine was calculated to be 1.8 by dividing AUCτ by AUCDay1. The mean blood concentrations at the steady state (Cavg,blood) for the low- and high-dose groups were estimated to be 2382.9 and 3735.0 ng/mL. The Cavg in the lung for the low- and high-dose groups were estimated to be 61,547.4 and 96,472.7 ng/mL. The Cavg in the trachea for the low- and high-dose groups were estimated to be 29,579.9 and 46,366.1 ng/mL. At the steady state, the lung-to-blood concentration ratio (=Cavg,lung/Cavg,blood) and trachea-to-blood concentration ratio (=Cavg,trachea/Cavg,blood) were calculated to be 25.83 and 12.41 in all groups. The simulated PK profiles for artesunate and dihydroartemisinin are shown in Figure 7. Since the t$\frac{1}{2}$ of artesunate and dihydroartemisinin were all estimated to be 0.4 h, both compounds were eliminated within 2–3 h after dosing. This short elimination half-life suggests that the steady state is not achieved by daily multiple-dosing of artesunate. Therefore, the accumulation ratios of artesunate and dihydroartemisinin were all calculated to be one. The EMA report showed the elimination half-life for both artesunate and dihydroartemisinin was similar, ranging from 0.32 to 0.52 h [36]. In another report, only the PK parameters for dihydroartemisinin could be determined since artesunate is rapidly metabolized to dihydroartemisinin in vivo [39]. The reported elimination half-life of dihydroartemisinin was ranged from 0.25 to 1.03 h in rats and from 0.39 to 0.66 h in dogs [36,47]. The AUCt of artesunate was calculated to be 3.0 and 18.3 h·nmol/L for the low- and high-dose groups, and that of dihydroartemisinin was calculated to be 931.4 and 3849.7 h·nmol/L for each group. Since artesunate and dihydroartemisinin were not accumulated by dosing intervals of 24 h, the steady-state could not be reached. Thus, the tissue-to-blood AUC was used for evaluating the tissue exposures instead of the Cavg at the steady state. The lung-to-blood AUC ratios for artesunate and dihydroartemisinin were calculated to be 3.34 and 0.34. The trachea-to-blood AUC ratios for artesunate and dihydroartemisinin were calculated to be 1.51 and 0.15. A minimum toxic concentration (MTC) or minimum effective concentration (MEC) of pyronaridine and artesunate has not been reported in hamsters. Nevertheless, a maximal nonlethal dose of pyronaridine and artesunate was reported to be 1500 and 500 mg/kg in rodents [39]. In addition, artesunate appeared to be more toxic than pyronaridine whether it was administered alone or coadministered with pyronaridine [39]. Thus, since the doses of both drugs used in this study were about four to eight times lower than the lethal dose and unscheduled deaths of the animals were not observed, the doses were regarded as tolerated. Also, several studies reported the antiviral effects against SARS-CoV-2 for pyronaridine and artesunate in vitro. In the case of pyronaridine, Bae et al. showed pyronaridine could suppress the replication of SARS-CoV-2 in Vero cells, and the EC50 was calculated to be 569.9 and 1139.7 ng/mL after 24 and 48 h of culture, respectively [9]. Gendrot et al. reported that the EC50 for an effective anti-SARS-CoV-2 was 373.0 ng/mL in Vero E6 cells [48]. Aherfi et al. showed the anti-SARS-CoV-2 activity of pyronaridine at a concentration of 103.6 (Huh7.5 cells) and 8.6 ng/mL (Calu-3 cells) [49]. In the case of artesunate, Zhou et al. proved the range of the EC50 for artesunate was 18.2–31.2 μM in different cell types [50]. Cao et al. reported similar anti-SARS-CoV-2 effects of artesunate and dihydroartemisinin with EC50 values of 12.98 and 13.31 μM, respectively [8]. ## 4. Conclusions The pharmacokinetics, trachea, and lung exposures of pyronaridine, artesunate, and dihydroartemisinin were successfully evaluated in hamsters using NCA and minimal PBPK modeling. The majority of pyronaridine was distributed to the lung and trachea with high average exposure ratios of 25.5 and 7.17 for the lung-to-blood and trachea-to-blood AUC ratio on day one. Also, the lung-to-blood and trachea-to-blood AUC ratios of pyronaridine were calculated to be 51.00 and 16.60 on day three. Artesunate and dihydroartemisinin were all eliminated within about 2 h and not accumulated by the dosing interval of 24 h. Using the minimal PBPK model, the multiple-dosing simulations for daily oral dosing of pyronaridine and artesunate were conducted for 14 days and 3 days, respectively. The steady-state was reached about three to four days after the first dosing of pyronaridine, and pyronaridine was extensively distributed to the lung and trachea with the lung-to-blood and trachea-to-blood concentration ratios of 25.83 and 12.41, respectively. Artesunate and dihydroartemisinin were eliminated within 2–3 h after dosing, suggesting the steady-state is not achieved by a daily multiple-dosing of artesunate. 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--- title: '3D Nanocomposite with High Aspect Ratio Based on Polyaniline Decorated with Silver NPs: Synthesis and Application as Electrochemical Glucose Sensor' authors: - Anna A. Vasileva - Daria V. Mamonova - Vladimir Mikhailovskii - Yuri V. Petrov - Yana G. Toropova - Ilya E. Kolesnikov - Gerd Leuchs - Alina A. Manshina journal: Nanomaterials year: 2023 pmcid: PMC10058674 doi: 10.3390/nano13061002 license: CC BY 4.0 --- # 3D Nanocomposite with High Aspect Ratio Based on Polyaniline Decorated with Silver NPs: Synthesis and Application as Electrochemical Glucose Sensor ## Abstract In this paper, we present a new methodology for creating 3D ordered porous nanocomposites based on anodic aluminum oxide template with polyaniline (PANI) and silver NPs. The approach includes in situ synthesis of polyaniline on templates of anodic aluminum oxide nanomembranes and laser-induced deposition (LID) of Ag NPs directly on the pore walls. The proposed method allows for the formation of structures with a high aspect ratio of the pores, topological ordering and uniformity of properties throughout the sample, and a high specific surface area. For the developed structures, we demonstrated their effectiveness as non-enzymatic electrochemical sensors on glucose in a concentration range crucial for medical applications. The obtained systems possess high potential for miniaturization and were applied to glucose detection in real objects—laboratory rat blood plasma. ## 1. Introduction Accurate and fast glucose detection in small volumes of biological analytes has remained a vital challenge for many years. Diabetes is one of the life-threatening diseases of mankind. However, regular monitoring of blood glucose can prevent hypo- and hyperglycemia, thereby prolonging the life of diabetic patients. Small glucometer devices make life easier; however, they require the combination of several important characteristics. Simultaneous requirements are miniaturization, accuracy, operation speed in small volumes of the analyte (a drop of the patient’s blood). Ensuring the listed important characteristics stimulates scientists in the search for new solutions. Thus, the quest for easy-to-use patient-friendly detection of glucose has been most challenging for science in recent decades. Different routes are explored among which non-invasive glucose detection based, e.g., on sensing with acoustic and light waves, has particular appeal. While there have been promising advances [1,2], the breakthrough is still to come. That is why electrochemical sensors are still considered as most promising [3]. The latest, fourth generation of electrochemical glucose sensors is based on a non-enzymatic approach. Non-enzymatic sensors are characterized by direct electrocatalytic oxidation of glucose on the electrode surface that provides faster and more accurate glucose detection with higher reproducibility and stability during a prolonged operation. Non-enzymatic glucose detection was demonstrated for various electrode materials such as mono- and multimetallic nanostructures [4,5,6,7,8,9], carbon-based nanocomposites [10,11,12,13], and conductive polymers (CPs) [14,15,16,17,18]. Improving the analytical signal for non-enzymatic glucose detection was demonstrated for composite materials combining conductive polymers and metallic nanoparticles (MNPs) [15,19,20,21,22]. Furthermore, nanocomposites based on CP—polyaniline (PANI) present a special group promising for the creation of small glucometer devices. The main advantages of PANI as a material for glucometer devices are (i) high electron conductivity (thus providing total electrochemical potency), (ii) a large surface area of PANI due to its porous structure (it provides an increased surface for MNPs sites active in electrocatalysis), (iii) chemical stability (this allows various chemical approaches for the creation of PANI-based nanocomposites), (iv) biocompatibility (promising for sensors as implantable devices with tolerance to body fluids or tissues), (v) flexibility—potency for nanocomposites with 3D architecture (it provides the miniaturization option). All the listed features have attracted the attention of researchers to PANI as an important component of nanocomposites for glucose electrochemical sensors [23,24]. In spite of the advantages of PANI-based materials demonstrated for glucose sensing, there are still problems to be solved for their implementation in real applications. To make materials promising for electrochemical glucose detection, one should keep in mind the potential of the studied systems with respect to miniaturization and integration. Moreover, for adequate device operation, a controllable morphology with a highly electro-catalytically active area of the sample is essential. However, most of the reported systems are disordered matrices with catalytically active NPs on the surfaces of wires, disordered pores, etc. [ 25,26,27], leaving no possibility for morphology control and reproducibility. Here we present the synthesis of nanocomposites based on PANI with incorporated Ag nanoparticles. The suggested approach allows the creation of 3D-ordered porous nanocomposites with a high aspect ratio of the pores, topological ordering, uniformity of properties throughout the sample and a large specific surface area. Ordered 3D architecture of the PANI/Ag nanocomposite was ensured by a template of anodic aluminum oxide (AAO); the PANI layer on AAO pores was obtained by developed in situ oxidative polymerization of aniline; Ag NPs on the inner surface of the PANI-covered AAO pores were synthesized by laser-induced deposition (LID). The important LID peculiarity is NPs nucleation and growth directly on the substrate surface, thus providing good NPs adhesion. The presented 3D PANI/Ag nanocomposite was studied as an electrode in the electrochemical reaction of glucose oxidation. It was found that the 3D PANI/Ag nanocomposite acts as a potentiometric sensor on glucose in a range of glucose concentrations for real medical diagnostic applications (5–15 mM). We demonstrated the applicability of such structures for glucose detection in Ringer’s solutions and in the blood plasma of a laboratory rat. In such a way, the suggested 3D ordered porous PANI/Ag nanocomposites can be considered as new agents of non-enzymatic electrochemical glucose sensors. Another competitive advantage of the 3D PANI/Ag nanocomposite is the potency of a miniature device design for the study of microliter volumes of analytes. ## 2.1. Materials and Methods Aluminum plates ($99.99\%$), were used for AAO membranes synthesis. CuCl2 (>$98\%$ wt%), H3PO4 ($84\%$ wt%), HClO4 ($72\%$ wt%), HCl ($38\%$ wt%), CH4O, and C2H6O (spectroscopic grade) were purchased from Reachem (Moscow, Russia) and used without additional purification. For the PANI synthesis, C6H5NH2 was preliminarily purified using a standard procedure [28]; (NH4)2S2O8 (highly purified) was stored in darkness in the presence of desiccant and used as received. For solutions preparation, bidistilled water was used. As a precursor for laser-induced deposition, silver salt C6H5COOAg (containing Ag 47.1 wt%) from Alfa Aesar (Haverhill, MA, USA) was used. For the electrochemistry, Ringer’s solution was prepared (0.11 M NaCl, 0.06 M KCl, 0.02 M CaCl2) with different concentrations of glucose. Reagents (highly purified) were purchased from Reachem (Moscow, Russia) and used as received. Samples of terminal blood plasma from laboratory rats were used as a biological analyte for glucose detection. The samples were provided by the V.A. Almazov Scientific Research Center, Saint-Petersburg, Russia. After collection, the plasma was frozen and stored frozen at −80 °C. Defrosting was performed just before electrochemical measurements. ## 2.2. Synthesis of Composites First, highly ordered membranes of anodic aluminum oxide were prepared to be used as 3D templates. For the preparation, aluminum plates were electropolished in precooled ethanol solution of perchloric acid (volume ratio 3:1), applying 20 V during 15 min. Membranes were then synthesized in a two-step anodization procedure. The anodization was performed in $0.5\%$ H3PO4 solution, applying 180 V; the temperature in the chamber was maintained at 2 °C. The first step of anodization was carried out over 24 h. The obtained porous structure was then removed by exposition of samples in aqueous solution of 0.3 M potassium dichromate and $10\%$ of phosphoric acid for 24 h at 45 °C. As a result, an ordered aluminum surface was formed. The second step of anodization was subsequently carried out in the conditions of $1\%$ H3PO4, 180 V, +2 °C for 8 h. Finally, the back-side aluminum was removed from the sample by 0.7 M CuCl2 in $10\%$ HCl solution treatment and the barrier oxide layer was removed by sample exposition in $10\%$ H3PO4 at 45 °C for 40 min. Obtained ordered AAO membranes were used as templates for in situ polyaniline synthesis. For the polyaniline synthesis, aqueous solutions of aniline hydrochloride (0.04 M) and ammonium persulfate (0.05 M) were prepared and stored for 1 h at a temperature of +2 °C. The volume of each solution was 5 mL. The substrate was placed into a beaker and precooled. The synthesis itself was performed in a chamber at a temperature of +2 °C. Aniline hydrochloride and ammonium persulfate solutions were poured into the beaker, shaken for several seconds and left for diffusion into AAO pores and polymerization for 1 h. The sample was then removed from the reaction zone and dried in an airflow. Subsequently, a part of the samples was placed into a spin-coater and rotated for 10 min at 400 rpm. Obtained AAO/PANI structures were used for subsequent laser-induced deposition of silver NPs. For laser-induced deposition of silver NPs, the AAO/PANI sample was placed into a precursor solution of silver benzoate in methanol (0.4 mM) and stored in darkness for 3 h. Then the sample was removed from the solution and placed under continuous wave laser irradiation with a wavelength of 266 nm. The laser beam was unfocused, and the diameter of the laser spot was 1 cm2. The irradiation power density was 15 mW/cm2. The exposition was carried out during 40 min. After the LID procedure, AAO/PANI/Ag samples were ready for further operations. ## 2.3. Samples Characterization The polyaniline structure was studied by Raman spectroscopy using a Senterra (Bruker, Billerica, MA, USA) setup. The Raman spectra were excited by a 785-nm solid-state laser (1 mW power) using a 20× objective with a 200 s acquisition time, and the spectra were collected four times. The morphology of AAO/PANI structures was studied by scanning electron microscopy (SEM) using a Zeiss Merlin microscope (from Karl Zeiss, Oberkochen, Germany) equipped with a field emission cathode, a GEMINI-II electron-optics column, and an INCAx-act energy dispersive X-ray spectrometer (EDX), all in an oil-free vacuum system (Oxford Instruments, Abingdon, UK). The measurements were performed using a secondary electrons detector. The sample cross-section view was studied. Results of the laser-induced deposition were studied by Raman spectroscopy. The Raman spectra were excited by a 532-nm solid-state laser (10 mW power) using a 10× objective with an 80 s acquisition time, and the spectra were collected twice. For the study of the AAO/PANI/Ag structures morphology, SEM measurements were applied. The data were collected using a secondary electrons detector and back-scattered electron detectors from the top and cross-view of the sample. Additionally, EDX scanning across the sample was performed. ## 2.4. Electrochemical Measurements The electrochemical characterization was performed in a three-electrode cell with a sample as a working electrode, the Ag/AgCl(KCl3.5M) electrode as a reference and a platinum mesh as a counter electrode. The measurements were performed in Ringer’s solution (0.11 M NaCl, 0.06 M KCl, 0.02 M CaCl2) with different concentrations of glucose. The pH value was corrected to be 7 ± 0.1 by addition of the NaOH solution. Cyclic voltammetry (CV) and impedance spectroscopy (EIS) were used for the characterization. Measurements were carried out with a potentiostat/galvanostat Gamry Reference 600 (Gamry Instruments, Warminster, PA, USA). The cyclic voltammetry measurements were recorded at Vscan = 50 mV/s; the third cycles are presented. The impedance spectroscopy measurements were performed across a range from 100 kHz to 0.01 Hz in potentiostatic mode with the application of +0.5 V potential. The amplitude of the applied sinusoidal voltage was ±10 mV. In the next stage of the study, glucose detection by CV measurements in rat blood plasma as a real biological sample was carried out. For this, the electrochemical cell was adapted for small analyte volumes (see Supplementary Materials). The performed modernization made it possible to carry out measurements in the electrolyte volume of 100 µL. Samples of terminal blood plasma from the laboratory rats (mature male SPF Wistar rats weighing 283 ± 22 g) were used as a biological analyte for glucose detection. Animals were housed in a barrier-type facility in standard environmental conditions: 12 h light/dark cycle and standard temperature and humidity; and were administered food and water ad libitum. The animals study protocol was approved by an institutional animal care and use committee of the Centre for Experimental Biomodelling, Institute of Experimental Medicine, Almazov National Medical Research Centre, Ministry of Health of the Russian Federation (П3N°16-7, 19 August 2016). Blood samples were taken from the posterior vena cava. After collection, the plasma was frozen and stored frozen at −80 °C. Additionally, in blood plasma samples the glucose level was analyzed. The analysis was performed using ChemWell 2910 Combi automatic bio-chemical and enzyme-linked immunosorbent assay (ELISA) analyzer (Awareness Technology, SW Martin Hwy, Palm City, FL, USA) and a commercial kit, according to the manufacturer’s instructions. The results obtained were recorded using the Windows-based ChemWell Manager software (NEOGEN Corporation, 620 Lesher Place, Lansing, MI, USA). The provided samples of the blood plasma were placed in the cell without additional sample preparation. ## 3.1. Synthesis and Characterization of AAO/PANI/Ag Nanocomposite To prepare the PANI/Ag nanocomposite on AAO membranes, a two-step approach was chosen (Figure 1). In situ PANI synthesis on AAO (Figure 1a) was followed by laser-induced deposition of catalytically active Ag NPs (Figure 1b). The AAO templates with pores with a diameter of $d = 338$ ± 43 nm and a length of $L = 22$ ± 0.8 µm were used for the study. ## 3.1.1. PANI Synthesis on AAO Template According to modern understanding [29], the oxidative polymerization of aniline with PANI formation is realized in several stages: nucleation (formation of phenazine intermediates, their sorption on the substrate and agglomeration) and chains growth (by the reactions on side groups). After the start of the chains growth, the nucleation stage is inhibited. That is why if a substrate is placed in the reaction zone when the nucleation stage has been completed, no polymer formation on the substrate can be observed [30]. Taking this into account, polymer formation on the pore walls of AAO templates with a high L/D ratio is possible only if mass transport of precursors into the pores takes place during the nucleation period. However, in the presence of a template, the duration of the nucleation stage is decreased [31]. Additionally, it is necessary to note that the structure of the obtained polymer is greatly dependent on the synthesis parameters. For electrochemical applications, only polyaniline in the conductive form of emeraldine salt is useful. These circumstances make the formation of PANI coating on the pore walls of AAO templates a great challenge. Utilizing classical UIPAC methodology [32] for the synthesis of PANI in emeraldine form in the case of AAO templates leads to polymer formation on the membrane surface, while the pores remain empty. This is a result of the fact that the duration of the nucleation period is not sufficient to mas transport inside the pores. Thus, the goal of our studies was to increase the nucleation period. For this, the temperature of the synthesis and the precursors concentrations were decreased. The most successful experiments were performed at 2 °C, and with concentrations of monomer and oxidant of 0.04 M and 0.05 M correspondingly (that is, five times lower than the concentrations recommended by IUPAC). As far as the PANI synthesis conditions on AAO 3D templates significantly differ from IUPAC methodology, to confirm PANI formation in emeraldine form we additionally obtained emeraldine films on planar 2D substrates (cover glasses) for comparison. The polymer structure was studied by Raman spectroscopy; the results are presented in Figure 2. In accordance with Raman spectra, the structure of the PANI on the 3D substrate is close to the structure on the planar substrate. In both cases, PANI in the form of emeraldine salt was obtained. This is proved by the presence of a 1170 cm−1 peak (bending vibrations with hydrogen in ring structures) [33], peaks in a range of 1300–1400 cm−1 (stretching modes in C-N+•, associated with polarons) [34], 1505 cm−1 (stretching modes of C=N bands in quinoid fragments) [35], as well as a peak at 1590 cm−1 with a shoulder at 1618 cm−1 (stretching modes of C=C bands in quinoid and benzenoid fragments, respectively) [34,35]. However, the difference between 2D and 3D structures was observed in the spectral region of 1300–1400 cm−1. In the case of 2D architecture, two well-resolved peaks were observed. These peaks are related to the delocalized charge—polaron (1340 cm−1) and the localized charge—bipolaron (1380 cm−1). In the case of 3D architecture, only one peak that shifted to 1340 cm−1 was observed. This indicates a higher charge delocalization for the PANI with 3D architecture than for the PANI on planar substrates that should provide more effective charge transport in a 3D system [36]. The morphology of PANI structures determines the sample surface area that is of a great importance for further electrochemical applications. At first, the samples were characterized by SEM directly after removal from the polymerization zone (Figure 3a). SEM characterization of PANI synthesized on AAO template demonstrated the formation of polymer layer along the pores. However, PANI coating was found to be inhomogeneous with alternating empty areas and areas completely filled with polymer. To improve the morphology, the synthetic procedure was supplemented with a centrifugation step. During the stage of the polymer chains growth, the sample was removed from the reaction zone, placed into a spin-coating setup, and rotated for 10 min at 400 r/min. This approach allows us to obtain a PANI continuous coating with a lower thickness (Figure 3b). As can be seen from the insert pn Figure 3b, formation of an uniform PANI coating of the inner surface of the AAO pores was achieved. Demonstrated AAO/PANI samples were decorated with silver NPs by laser-induced deposition. ## 3.1.2. AAO/PANI Decoration with Ag NPs The important peculiarity of systems based on chosen AAO templates is the high aspect ratio L/d ~ 65. Due to this, it is possible to create the systems with a large electrocatalytically active surface area with a small visible area. A high electrocatalytical response (provided by a large specific surface area) in combination with a small visible area gives an opportunity for miniaturization of final devices. Furthermore, NPs are known to demonstrate high electrocatalytic activity [37]; this is why the loading of high-aspect ratio systems with NPs is very attractive. However, known methods of wet chemistry are useful for the decoration of high-aspect structures of various opal-type or nanowires morphologies [38,39,40,41]. While for inverted opal-type structures (such as AAO), there are no approaches that provide satisfactory coating parameters. Laser-induced deposition is one of the most promising among other methods for the decoration of structures of a complex topology [42]. Moreover, it allows precise control of deposited NPs composition, size, coating density, and localization area [43,44,45,46]. Other important advantages of LID are (i) that nucleation and growth of NPs takes place directly on the laser-affected area of the substrate thus providing good adhesion; (ii) that LID is realized at a low laser intensity, allowing the formation of NPs on polymer substrates [47]. The general scheme of LID of Ag NPs on the 3D AAO/PANI system is presented in Figure 1b and the experimental details are described in Section 2.2. As the PANI can be potentially destroyed by laser irradiation, optimization of the laser intensity was carried out. The optimal laser intensity was found to be 15 mW/cm2 as it provides both substrate preservation and efficient formation of Ag NPs. The results of the laser-induced deposition of Ag NPs on the 3D AAO/PANI system are shown in Figure 4. Figure 4a,b shows SEM images of AAO/PANI/Ag from the top of the sample. The images were obtained using different detectors, a—a secondary electrons detector, b—a backscattered electrons detector; images were taken from the same area. When using a secondary electrons detector, both the polyaniline component and silver nanoparticles can be observed. The use of a backscattered electrons detector makes it possible to observe only heavier silver nanoparticles and the AAO template, while the polymer phase is not detected. Thus, a comparison of the data obtained with different detectors proves the presence of both phases and demonstrates their distribution. Moreover, in the image Figure 4d obtained with the backscattered electrons detector, one can also observe additional diffuse signals from silver NPs located inside pores in deeper areas relative to the cut surface, which proves the formation of NPs over the entire volume of the sample. Figure 4f shows the EDX signal of silver detected in the scanning regime along the line (Figure 4e). One can see that the Ag signal is closer to the substrate surface; nevertheless, silver distribution along the whole pores length is clear. In addition, it is proved by the presence of a silver signal in the EDX spectra recorded from the backside of the sample (see Figure S3). ## 3.1.3. Mechanism of Ag NPs Formation during the LID Process To uncover the mechanism of Ag NPs formation during the LID process from the silver benzoate methanol solution, additional experiments were carried out. The silver benzoate methanol solution was placed into a spectrophotometric cuvette and closed with a quartz cover to avoid solvent evaporation during exposition under laser irradiation. Irradiation of the solution volume was then performed. Raman spectra were recorded for the methanol and silver benzoate solution before and after irradiation. The data are presented in Figure 5. Raman spectra of the methanol and the methanol solution of silver benzoate before laser irradiation are characterized by typical methanol peaks at 3360 cm−1 (stretching mode of OH group), 2943 cm−1 and 2834 cm−1 (stretching mode of C-H), 1454 cm−1 (bending mode of C-H) and 1034 cm−1 (stretching mode of C-O) [48]. The Raman spectrum of the silver benzoate methanol solution after laser irradiation demonstrates new peaks at 431 cm−1 and 836 cm−1, (νs C-C of benzene ring and δ(COO−) correspondingly); a shoulder at 1391 cm−1, (νs(COO−)), peak at 1601cm−1 (νs C-C in benzene ring) (Figure 5, range I) and shoulder at 3067 cm−1 (Figure 5, range II). The listed peaks (except for the shoulder at 3067 cm−1), are typical for benzoic acid [49,50]. The appearance of new peaks in the spectrum may be explained by the effect of the surface-enhanced Raman scattering on silver NPs formed during irradiation. The band at 3067 cm−1 can be associated with a symmetric stretching mode of C-H vibrations in benzene rings [51,52]. In the Raman spectra of benzoic acid, these vibrations appeared as the band with a maximum at 3085 cm−1 [53]. The difference between positions of the C-H peak in benzene (3067 cm−1) and benzoic acid (3085 cm−1) are explained by the effect of the substitute—carboxylic group. Because the other detected peaks are not shifted in comparison with the peaks of benzoic acid, we can assume that the 3067 cm−1 band is related with benzene which may appear as a photodegradation product during the LID process. This assumption is supported by electron paramagnetic resonance spectroscopy [54]. In this investigation, during UV irradiation of the silver benzoate isopropanol solution, the reaction of benzoate decarboxylation with the formation of phenyl radical takes place. his radical may then interact with a solvent or benzoic acid anion. In the last case, adduct and aqueous electron formation occurs. Taking this process into consideration, we can assume the same processes happens during the LID and the originated electrons taking part in silver ions reduction. ## 3.2. Electrochemical Glucose Detection on 3D AAO/PANI/Ag Nanocomposite The next stage of the study was devoted to a demonstration of the potency of AAO/PANI/Ag structures to glucose detection. The given current densities were calculated based on the visible area of the sample. Measurements were carried out in the absence and presence of glucose. Figure 6a shows CV data obtained for glucose concentrations close to physiological values (5–15 mM). The data presented vs. the Ag/AgCl electrode. There are several cathodic and anodic peaks on the presented CVA. A pair of peaks at +0.13 V (anodic curve) and −0.11 V (cathodic curve) indicate the presence of silver NPs in the system. To prove this judgement, additional experiments on laser-induced deposition of silver NPs on the graphite electrode with subsequent measurement of cyclic voltammetry were carried out. It was found that the peaks at +0.13 V and −0.11 V appear in the absence of PANI but in the presence of silver NPs (see Supporting Information, Figure S2). Glucose was then added to the electrolyte (5 mM concentration) and an anodic peak was found to appear at +0.515 V. With the increase in glucose concentration, the peak shifts to +0.690 V. One of the possible explanations of this observation is a local change in pH that affects the electrochemical response of polyaniline. This effect has been described in the literature [55], but is considered of little applicability for analytical purposes due to the rapid establishment of an equilibrium with the electrolyte. However, in the case of systems with 3D architecture based on AAO, which provide a high aspect ratio of pore length to pore diameter, this effect may be significant. On the other hand, a shift in potential with an increasing glucose concentration is observed on silver nanostructures [56]. That is why for the studied 3D nanocomposite, both effects can be considered as analytic signals for glucose detection. Thus, a 3D AAO/PANI/Ag nanocomposite can be used as a potentiometric sensor for glucose. The corresponding calibration curve is shown in Figure 6b. A linear dependence of the potential on the glucose concentration is observed in the selected concentration range. These concentrations correspond to the physiological range in the blood plasma. The sensor sensitivity is 17 ± 2 mV/mM and limit of detection = 0.35 mM. It is necessary to note that the structure under investigation acts as a potentiometric sensor while a wide range of PANI-based sensors are amperometric ones [3]. Obtained systems demonstrate a linear response in a range of glucose concentrations actual for real medical diagnostic applications while most of studies are devoted to achieving a low limit of detection [57,58,59,60,61]. To uncover the nature of the analytical signal observed by cyclic voltammetry, the impedance spectroscopy data were recorded in the absence and presence of glucose in the system. The results are presented in Figure 7. Figure 7a shows the hodograph obtained in the absence of glucose in the system and reflects the processes occurring in the 3D Ag-PANI nanocomposite itself. Based on the presented data, it can be concluded that two processes of charge transfer are realized. We can assume that one of the processes (which corresponds to the higher-frequency area of the hodograph) is associated with the charge transfer within the polymer component, and the second (the lower-frequency part of the hodograph) is associated with the charge transfer from silver NPs to the polymer. The data were fitted with an equivalent circuit in which two constant phase elements were included. The probable interpretation of them may be related to the high impact of heterogeneity on the phase boundary [1] between the electrolyte and NPs as well as the phase boundary [2] between the electrolyte and polymer, caused by high porosity of the system. The Rct[1] is 325 Ohm and Rct[2] is 791 Ohm while the R(solution) is 49 Ohm. It should be noted that there was no impact from the diffusion. This means that the electrode reaction is the limiting stage. When glucose is added to the system, the pattern in the low-frequency region is changed (see Figure 7b). This indicates that silver NPs are responsible for the analytic signal in the procedure of glucose detection. In the presence of glucose, the equivalent circuit had elements out of physical meaning; this is why it was not included in the discussion. It is necessary to note that the visible area of the working electrode of 3D AAO/PANI/Ag nanocomposite was just 0.07 cm2. Thus, such samples demonstrate their miniaturization potential which is critically recommended for the construction of real devices. In the next step of the investigation, the potency of 3D AAO/PANI/Ag nanocomposite as electrochemical glucose sensors for real samples was demonstrated. For this, glucose measurements were carried out using blood plasma from laboratory rats as electrolyte. To perform these measurements, the electrochemical cell with a small volume was constructed (see Figure S1 and description). The volume of the analyzed blood plasma sample was 100 µL. Figure 8 shows CV data recorded in the rat blood plasma electrolyte. According to the calibration curve (Figure 7b), the concentration of glucose in the studied blood plasma samples is 9.26 ± 0.31 mM. According to the data obtained by biochemical measurements (Section 2.4), the glucose level in the sample was 8.2 mM. The study of the plasma sample using a medical glucometer Accu-Check Active yielded a value of 12 mM. Thus, created 3D AAO/PANI/Ag nanocomposite structures demonstrated their effectiveness as sensors on glucose in real biological samples. ## 4. Conclusions In this research, we present a unique approach to the synthesis of electrocatalytically active nanostructures with a large specific surface area and the uniformity of properties throughout the sample thanks to the topological ordering. The systems are based on structured templates of anodic aluminum oxide with a high aspect ratio of pores and a high structural order. The templates were covered by uniform layers of polyaniline with embedded catalytically active silver NPs. The synthesis includes two main steps. The first is the developed in situ oxidative aniline polymerization directly on the inner pore walls of the AAO. The obtained coating was uniform, continuous and consisted of polyaniline in the form of emeraldine salt. The second step was the laser-induced deposition of silver NPs on the inner walls of the AAO/PANI system. This approach allowed the synthesis of NPs on the structures with a high aspect ratio and provided good NPs adhesion, as NPs nucleation and growth take place directly on the polyaniline layer. The proposed approach allowed the creation of AAO/PANI/Ag systems, which demonstrated applicability for electrochemical glucose detection. It was demonstrated that the systems act as a potentiometric sensor on glucose in a range of glucose concentrations actual for biomedical purposes (5–15 mM). In addition, it was found that a charge transfer with the participation of silver NPs is responsible for glucose detection. The investigated systems successfully demonstrated the operability for glucose detection in real biological objects—the blood plasma of laboratory rats. As a consequence of the high aspect ratio of the system, obtained structures exhibit a large electroactive surface area with a small visible surface area (0.07 cm2). Thus, the AAO/PANI/Ag systems demonstrated the potential for miniaturization and application in real biological objects: the volume of the analyzed sample was 100 µL. The current research achieved several goals: the development of synthetic procedures for obtaining ordered nanocomposite structures, glucose detection on the synthesized structures and demonstration of applicability for biological samples. Thus, the study may make a push for evolution in all the listed areas. ## References 1. Hertzberg O., Bauer A., Küderle A., Pleitez M.A., Mäntele W.. 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--- title: In Vitro Antitumor and Anti-Inflammatory Activities of Allium-Derived Compounds Propyl Propane Thiosulfonate (PTSO) and Propyl Propane Thiosulfinate (PTS) authors: - Enrique Guillamón - Nuria Mut-Salud - María Jesús Rodríguez-Sojo - Antonio Jesús Ruiz-Malagón - Antonio Cuberos-Escobar - Antonio Martínez-Férez - Alba Rodríguez-Nogales - Julio Gálvez - Alberto Baños journal: Nutrients year: 2023 pmcid: PMC10058678 doi: 10.3390/nu15061363 license: CC BY 4.0 --- # In Vitro Antitumor and Anti-Inflammatory Activities of Allium-Derived Compounds Propyl Propane Thiosulfonate (PTSO) and Propyl Propane Thiosulfinate (PTS) ## Abstract Increasing rates of cancer incidence and the side-effects of current chemotherapeutic treatments have led to the research on novel anticancer products based on dietary compounds. The use of Allium metabolites and extracts has been proposed to reduce the proliferation of tumor cells by several mechanisms. In this study, we have shown the in vitro anti-proliferative and anti-inflammatory effect of two onion-derived metabolites propyl propane thiosulfinate (PTS) and propyl propane thiosulfonate (PTSO) on several human tumor lines (MCF-7, T-84, A-549, HT-29, Panc-1, Jurkat, PC-3, SW-837, and T1-73). We observed that this effect was related to their ability to induce apoptosis regulated by oxidative stress. In addition, both compounds were also able to reduce the levels of some pro-inflammatory cytokines, such as IL-8, IL-6, and IL-17. Therefore, PTS and PTSO may have a promising role in cancer prevention and/or treatment. ## 1. Introduction Despite the fact that some recent research has shown that certain risk factors can ease the appearance of some types of cancer, the reasons why some people develop these processes while others do not remain unknown. Among these risk factors, the exposure to chemicals and radiation, age, genetics, lifestyle, or underlying chronic diseases, such as inflammatory disorders, seem to have a prominent role, representing major signaling cues driving the activation of cancer in humans [1]. After cardiovascular diseases, cancer remains the second leading cause of death around the world, with 19.3 million new cases and almost 10.0 million deaths in 2020 [2]. This scenario is projected to be amplified drastically soon; hence, continued searching for more effective chemoprevention and treatment therapies is clearly needed to increase surveillance and to lower the treatment cost for cancer care. Cancer is caused by the proliferation and progression of abnormal cells. Exposure to carcinogens causes DNA damage and mutations at the cellular level due to the failure in DNA repair mechanisms. The proliferation of the damaged cells causes inflammation of the cells and tissues, finally leading to a tumor formation [3]. One of the mutual traits of cancer is the quick formation of aberrant cells that expand beyond their normal borders, affecting neighboring sections of the body and migrating to other tissues. This process is known as metastasis and is the chief reason for death due to cancer [4]. The advent of modern drug therapies has undeniably improved cancer patients’ cares and lives. However, advanced metastasized cancers remain untreatable, and conventional treatment methods, such as chemotherapy, radiation therapy, or immunotherapy, have major side effects and toxicities [5]. Therefore, the identification and development of novel anticancer products based on natural substances with fewer adverse effects have gained attention in recent years [6]. For example, there is a growing interest in the use of natural immunostimulants in combination with the common therapeutic modalities in the treatment of cancer. The supplementation with these products pretends to improve the immune response against tumors and reduce the suppression effect produced by the chemotherapy [7]. The immune system exhibits the chief function in the defense against infected pathogens and harmful antigens, including tumor cells [8]. Although the induction of an acute immune response plays a cardinal aspect in the detection of and combating tumor cells, it is widely described that the shifting into chronic inflammation, as in case of chronic inflammatory bowel diseases, may also increase the incidence of cancer generation due to the excessive production of inflammatory mediators such as cytokines, reactive oxygen species (ROS), and growth factors. Supporting this, it is well known that chronic inflammation triggers different epigenetic mechanisms that shape the tumor microenvironment, affecting the cell plasticity, differentiation, and polarization of immune cells, promoting the release of ROS and cytokine production [9,10]. In fact, elevated levels of ROS in association with an impaired redox balance are common features of cancer progression and resistance to treatments [11]. In addition, ROS production causes DNA damage, which also contributes to cancer development. It has been estimated that $25\%$ of cancer-causing factors are related to chronic inflammation [3]. Accordingly, the current targets of the treatments include mediators-associated inflammatory pathways and/or oxidant-generating enzymes, as the evaluation of different anti-inflammatory drugs in several clinical trials has revealed that they can play dual roles in inflammation and tumorigenesis. However, some severe problems related to a long-term use of these drugs have been identified [3,9]. Consequently, the search for natural compounds with antiproliferative and/or anti-inflammatory properties, which provides a safe use profile, constitutes a line of work of great interest [12,13,14,15]. Furthermore, the potential synergism of conventional drugs with natural compounds introduces a new aspect to fight cancer, which involves a promising approach to improve the effectiveness of treatment while minimizing the adverse effects associated with chemotherapy [16]. A large number of studies point out that suitable dietary patterns may help to prevent cancer or inhibit tumor development in cancer patients [17]. For instance, some plants are rich in bioactive compounds that possess anticancer and immunomodulatory activities with a low risk of cytotoxicity and side effects. These biologically active plant metabolites are known as “phytochemicals” [18,19]. Although phytochemicals are not associated with nutritional functions, they play a key role as responsible compounds for multiple health benefits. Epidemiological studies, as well as in vivo, in vitro, and clinical trials, have shown the ability of a variety of dietary compounds to reduce the risk of different chronic diseases, including cancer. Many phytochemicals have been reported for their immunomodulatory activities and their uses in treatment of and combating several types of cancer through different mechanisms: the enhancement of the activity of the enzymes involved in the inactivation of carcinogens, the suppression of the growth of cancer cells, or affecting metabolic processes [20,21]. Some examples of phytochemicals with anticancer and immunostimulant properties include curcumin from turmeric, epigallocatechin-3-gallate from green tea, resveratrol from grapes, sulforaphane from broccoli, glucosinolates from cruciferous vegetables, or gingerol from ginger [22]. Among these dietary substances, those derived from alliaceous plants such as garlic, onion, or leek stand out. In general, vegetables from the Allium genus contain different reputed bioactive molecules including flavonoids, oligosaccharides, amino acids, selenium, and organosulfur compounds (OSCs) [18,19]. The beneficial properties of OSCs obtained from Allium spp., such as antimicrobial, anti-inflammatory, antidiabetic, antioxidant, and immunomodulatory, among others, have been broadly reported [22,23,24,25,26]. In addition, some of these compounds, mainly allylic derivatives from garlic, have been described to display a direct antitumoral effect [11,26] or used as adjuvants in chemotherapy treatment, enhancing the activity of drugs or reducing its side effects [27,28,29]. For instance, the anticancer potential of allicin (e.g., diallyl thiosulfinate), the most important OSC from garlic, has been recently reviewed [30], revealing that it suppresses the growth of different types of tumors. However, this compound is very unstable, and even at optimal processing and storage conditions, easily lead to the spontaneous decomposition of secondary OSCs such as diallyl disulfide (DADS). Several experimental studies have demonstrated that DADS also exhibits anti-tumor activity against many lines of tumor cells, including hematological cancers (leukemia, lymphoma), lung cancer, prostate cancer, or colorectal cancer (CRC) [31]. However, DADS has caused appreciable allergic reactions and toxicity, affecting normal cells too. Thus, the use of these compounds in the prevention and treatment of cancer is limited presently [32]. In contrast, despite the fact that epidemiological studies have confirmed that regular onion consumption reduces the incidence of various forms of cancer as well as other diseases associated with oxidative stress [33], much less is known about the biological activities of OSCs derived from onion. In particular, propyl propane thiosulfinate (PTS), the saturated analogue to allicin, and its oxidized derivative propyl propane thiosulfonate (PTSO) (Figure 1), also present antimicrobial and immunomodulatory activities [34,35], but they are highlighted for their higher stability compared to the OSCs derived from garlic. Therefore, as a first contribution to deep in the potential of PTS and PTSO in the chemotherapy treatment of cancer, the present study aims to characterize the in vitro antiproliferative and anti-inflammatory properties of both compounds and analyze some of their mechanisms of action. ## 2.1. Chemicals and Reagents PTSO and PTS ($93.5\%$ purity) were chemically isolated and provided by DOMCA S.A.U. (Granada, Spain). Both compounds were previously dissolved in dimethyl sulfoxide (DMSO). From these solutions, the different dilutions to be tested were prepared using Dulbecco’s Modified Eagle Medium (DMEM) without fetal bovine serum (FBS) or antibiotics. All reagents were purchased from Sigma-Aldrich Química S.L (Madrid, Spain), unless otherwise stated. ## 2.2. Cell Lines and Culture MCF-7 (a human breast adenocarcinoma line; ECACC 86012803), T-84 (a human colon carcinoma line; ECACC 88021101), A-549 (a human lung carcinoma line; ECACC 86012804), HT-29 (a human colon adenocarcinoma line; ECACC 91072201), Panc-1 (a human pancreatic cancer line; ECACC 87092802), Jurkat E6.1 (a human leukemia line; ECACC 88042803), PC-3 (a human prostate adenocarcinoma line; ECACC 90112714), and SW-837 (a human rectum adenocarcinoma line; ECACC 91031104) were obtained from the Cell Cultures Unit of the University of Granada (Spain). T1-73 (a human osteosarcoma line; CRL-7943) and hMSCs (human adipose-derived multipotent mesenchymal cells; PCS-500-01) were supplied by the American Type Culture Collection (ATCC). PBMCs (peripheral blood mononuclear cells) were obtained from blood samples of healthy volunteers and provided by the biobank of “Sistema Sanitario Público de Andalucía (SPPA)”. All cell lines were cultured in darkness at 37 °C, with a humidified atmosphere of $5\%$ CO2, using DMEM supplemented with $10\%$ FBS, 10 mL/L of penicillin–streptomycin 100×, and 2 mM of L-glutamine, except hMSCs that were supplemented with $20\%$ FBS and without antibiotics, and PBMCs that were cultured with RPMI-1460 medium supplemented with $10\%$ FBS. ## 2.3. In Vitro Antiproliferative Assays In order to calculate the half-maximal inhibitory concentration (IC50) values of PTS and PTSO, adherent cells (MCF-7, T-84, A-549, HT-29, Panc-1, SW-837, PC-3, and T1-73) were seeded in sterile 96-well plates (Thermo Fisher Scientific, Denmark) at a high density (1.4 × 104 cells/well) and incubated at 37 °C with $5\%$ CO2 for 24 h to allow for cell adhesion. In non-adherent cells (Jurkat and PBMCs), the induction was conducted directly. Increasing concentrations of PTS and PTSO (1–250 μM) were added in the corresponding wells and incubated for 72 h at 37 °C with $5\%$ CO2. The effect of both compounds on adherent cell lines was evaluated using a colorimetric technique with Sulforhodamine-B (SRB) [36]. Non-adherent cell lines were quantified by the MTT assay [37]. The optical density values of adherent and non-adherent cells were determined by colorimetry at 490 nm using a microplate reader (Multiskan EX, Thermo Electron Corporation). The assessment of absorbance was obtained using the SkanIt RE 5.0 for Windows v.2.6 (Thermo Labsystems, USA) and a regression analysis for each cell line using Statgraphics 18 software (Statistical Graphics Corp, 2000, Warrenton, VA, USA) was conducted. The IC50 values were calculated from the semi-logarithmic dose–response curve by linear interpolation. Finally, the therapeutic index (TI) of each compound was determined to determine the margin of safety of PTS and PTSO when used as an antiproliferative. TI was calculated by establishing the ratio between the IC50 values obtained in non-tumoral cells and in a tumor cell line. For each cell line, the assays were performed in duplicate. ## 2.4. Oxidative Stress Assays MCF-7 and T-84 cells were seeded in 96 well-plates at a high density in sextuplicate. At 24 h, the cells were induced with increasing concentrations of PTS and PTSO, with or without 5mM of NAC (N-Acetyl-Cystein) for 1 h pre-induction. After 72 h, the cell viability was evaluated using the SRB method. The IC50 values were calculated from the semilogarithmic dose–response curve by linear interpolation. Assays were performed in duplicate. The production of intracellular ROS was detected by fluorescence microscopy. MCF-7 cells were seeded at 5 × 103 cells/well for 24 h on a µ-Slide 8 well high glass bottom (Ref.80807, Ibidi, Gräfelfing, Germany). Then, the cells were preincubated in the presence or absence of 5mM of NAC for 1 h and treated with PTS or PTSO for 24 h at doses of IC50. Subsequently, the cells were incubated with 2,7-dichlorofluorescein diacetate (DCFH-DA) (10 μM) in darkness at 37 °C for 30 min. Fluorescent images were taken with a confocal laser scanning microscope Confocal Leica TCS-SP5 (Leica, Munich, Germany) at 25× of magnification and 1.5× of zoom. ## 2.5. Apoptosis Assays The cell viability was determined by flow cytometry using the Annexin V-FITC kit (Trevigen, Gaithersburg, MD, USA). MCF-7 and T-84 cells were seeded at a high density (2 × 105 cells/cm2) in 6-well plates. After 24 h, the cells were induced with PTS and PTSO for 48 h at the IC50 concentration for each cell line. The cells were detached with the TrypLE Express Enzyme (ThermoFisher Scientific, Waltham, MA, USA), washed with PBS, and collected by centrifugation at 300× g for 10 min. Then, the cells were washed again and incubated with annexin-V FITC and propidium iodide (PI) in an annexin-V binding buffer for 15 min. After incubation, the cells were diluted with the binding buffer and examined immediately in a FACScan flow cytometer, using FlowJo (v.7.6.5, Tree Star, Inc., Ashland, OR, USA). This assay was performed in duplicate. ## 2.6. In Vitro Anti-Inflammatory Assays The HT-29 and T-84 cells were seeded at a high density (1.4 × 104 cells/well) in 96-well plates for 24 h. Then, the supernatants were discarded and the compound dissolved in the supplemented medium was added. After 1 h of incubation with PTS or PTSO, 1 µg/mL of lipopolysaccharide from Salmonella enterica serotype typhimurium (LPS) was added, and the plates were incubated for 24 h at 37 °C and $5\%$ CO2. All the concentrations tested were performed in sextuplicate. After induction, the supernatants were collected, centrifuged at 1000× g for 10 min, and stored at −80 °C. Finally, the IL-8, IL-6, and IL-17 determination was carried out by an ELISA using cytokines commercial kits (Invitrogen-ThermoFisher Scientific, Bethlehem, PA, USA). The assays were performed in duplicate. ## 2.7. Statistical Analysis The results of absorbance in cytotoxicity assays and IC50 were evaluated using an analysis of variance (ANOVA), using the statistical software SPSS 11.5 (IBM, New York, NY, USA). All the results were expressed as mean ± standard deviations (SD). Figures and statistical analysis for apoptosis assays and anti-inflammatory assays were generated with GraphPad prism 8.0 software (GraphPad Software Inc., La Jolla, CA, USA) using a one-way ANOVA test supplemented with Tukey’s post hoc. Differences were considered statistically significant when $p \leq 0.05.$ The relative fluorescence intensity was quantified using the software Image J (v. 1.53t). ## 3.1. In Vitro Antiproliferative Effects of PTS and PTSO The antiproliferative activity of PTS and PTSO was evaluated in all the cell lines described above. Both compounds inhibited cellular proliferation in a dose–response manner with a different efficacy against the cell lines used (Table 1). The results revealed that the IC50 values from PTSO were higher than for PTS, except in MCF-7, Jurkat, SW-837, and Panc-1 (Table 1). Therefore, these findings indicated a different but remarkable antitumor effectiveness of PTS and PTSO (Table 1). In order to determine the in vitro TI of PTS and PTSO, their effect by performing cultures with PBMCs was studied under the conditions described in Section 2.2. In this cell line, the results obtained show an IC50 value of 229.2 µM for PTS and 248.5 µM for PTSO. Therefore, the TIs for PTSO and PTS were 12.9 and 36, respectively, taking as reference the MCF-7 line, and 14.6 and 23.4 considering the Jurkat line. To confirm the harmlessness of PTS and PTSO in healthy cells, their effect was also tested on hMSCs. It was found that both compounds hardly produced toxicity on these cells as very high concentrations are required to affect cell viability (Figure 2). Moreover, certain concentrations of these compounds even were able to induce the proliferation of hMSCs. Specifically, induction with 10 µM of PTS or PTSO increased the population by $17\%$ and almost $11\%$, respectively, compared to the control. At concentrations greater than 20 µM, it was noted that PTSO was generally less harmful on hMSCs than PTS. ## 3.2. Oxidative Stress Assays In order to determine if the mechanism of action of PTS and PTSO was related to ROS production, their cytotoxicity was tested in MCF-7 and T-84 cells in the presence or absence of NAC 5 mM. In MCF-7 cells, the IC50 of PTS and PTSO in the presence of NAC barely affected the cell viability, reducing the population by $10\%$ compared to controls without NAC (Figure 3A). Thus, the presence of NAC decreased the anti-proliferative effect of both compounds, increasing by $40\%$ the cell population. In T-84 cells, the IC50 of PTS and PTSO in the presence of NAC were able to reduce the population by $20\%$ and $15\%$, respectively, increasing the cell viability by 33–$34\%$ compared to the controls without NAC. From these results, it may be concluded that NAC protects tumor cells from the activity of PTS and PTSO. These results were also confirmed by the determination of intracellular ROS by a confocal microscope using DCFH-DA in the MCF-7 line. Thus, the cells were treated with PTS and PTSO at IC50 concentrations, in the absence or presence of NAC 5 mM. As it can be observed in Figure 3B. NAC incubation reduced the high fluorescence of tumor control cells. Remarkably, the incubation for 24 h only with PTS or PTSO in MCF-7 cells diminished considerably the cell population in the absence of the antioxidant, and so did the fluorescence (Figure 3B). On the contrary, when MCF-7 cells were incubated with PTS or PTSO and previously supplemented with NAC, the findings revealed a higher fluorescence because the population had barely been affected (Figure 3B). ## 3.3. Study of Apoptosis Cultures of MCF-7 and T-84 cells were incubated with the IC50 concentrations of PTS and PTSO for 48 h. The apoptosis induction was assessed by an annexin V FITC assay using flow cytometry. Figure 4A shows the different apoptotic stages in both cell lines when they were incubated with both compounds. Specifically, the percentage of the different apoptotic stages was quantified, and the results showed that in MCF-7 cells, the fraction of early apoptosis increased from $12.7\%$ to $20.2\%$ in cultures treated with PTS, and to $17.3\%$ with those treated with PTSO. The number of late apoptotic cells also increased in treated cells, from $1.6\%$ to $10.7\%$ with PTS and to $5.9\%$ with PTSO (Figure 4B). In T-84 cells, the percentages of early and late apoptotic cells were also higher in treated cells compared to the control for both compounds, although the induction of apoptosis was more evident with PTS, increasing from $0.9\%$ to $7.4\%$ of early apoptotic and $0.3\%$ to $2.8\%$ of late apoptotic cells (Figure 4B). ## 3.4. Evaluation of Anti-Inflammatory Properties To evaluate the anti-inflammatory properties of PTS and PTSO, the production of IL-8, IL-6, and IL-17 was determined in HT-29 and T-84 cells after their incubation with LPS, which has already been long demonstrated to be capable of eliciting responses associated with inflammation in vitro, including the production of pro-inflammatory cytokines [38]. The concentrations of PTS and PTSO tested were selected considering the levels of cytotoxicity already determined in these lines considering their IC50. Both PTS and PTSO were able to significantly inhibit the LPS-activated production of these cytokines (Figure 5). However, no concentration–response relationship was observed since most of the concentrations assayed showed a similar efficacy for both compounds with some exceptions: when the production of IL-8 in HT-29 cells was considered, the most effective concentrations were 1 μM of PTS and 10 μM of PTSO. ( Figure 5A); or when the production of IL-17 was considered in HT-29 and T-84 cells, both compounds showed more efficacy at the highest doses assayed (10 µM and 25 µM) (Figure 5C). ## 4. Discussion Treatment with the extracts or compounds derived from Allium has been the subject of numerous studies and trials to establish a link with a reduced risk of cancer. In this sense, our findings are in concordance with other assays previously published [39,40,41]. In fact, several in vitro and in vivo studies have shown the potential antiproliferative activity of the extracts or compounds derived from Allium in the same cell lines we have tested. For instance, in one study conducted with quercetin from Allium cepa, this compound showed cytotoxicity against MCF-7, HT-29, PC-3, and Jurkat cells [42]. The antitumor capacity of crude thiosulfinates from Allium tuberosum affected the viability of MCF-7 breast tumor cells, with an IC50 of 155.1 μM in the case of S-methyl methanethiosulfonate and 51.1 μM for S-methyl 2-propene-1-thiosulfinate [43]. In another study conducted with 22 stabilized thiosulfinates derived from Allium vegetables, the IC50 of the compound with the greatest anticancer activity in MCF-7 cells (S-4-methoxyphenyl 4-methoxybenzenesulfinothioate) was 46.5 µM [20]. Despite the fact that in this article, PTS was synthesized to carry out studies on the mechanism of action, the IC50 in the MCF-7 line was not reported [20]. In our assays, both PTS and PTSO achieved lower IC50 values in MCF-7 (17.7 and 6.9 μM, respectively) than the mentioned compounds. Other Allium OSCs, whose IC50 values at 72 h in MCF-7 have been reported, are allicin (10 μM) [44] and DADS (4.1 μM) [45], showing an antiproliferative effect in this line similar or a little higher than the one obtained in our assays with PTS and PTSO. Some of the OSCs more commonly studied, as allicin, DADS, or diallyl trisulfide (DATS), have also showed antitumor activity in colon cancer cell lines, including HT-29 [11,45,46,47]. A similar effect has been described for water-soluble garlic-derivatives, such as S-allylmercaptocysteine. The effect of this compound on cell cycle progression and proliferation was evaluated in colon cancer cell lines SW-480 and HT-29, achieving the growth inhibition of both lines inducing apoptosis [48]. Our results showed that PTS and PTSO exerted cytotoxicity in all of the colon tumor cells challenged, being especially remarkable for PTS in T-84 and HT-29, with IC50 values below 20 μM (18.2 μM and 15.6 μM, respectively). Conversely, in SW-837 cells, the IC50 of PTS was higher than for PTSO (150.8 μM and 132.8 μM, respectively). Regarding lung tumor cell lines, DADS and DATS have also shown antitumor activity against A-549 by inducing apoptosis [49], though in this study, the IC50 was not indicated. In another in vitro assay, DADS (15–120 μM) was tested in AML HL-60 leukemic cells, succeeding in suppressing cell growth [50]. These results are in accordance with those obtained in our experiments since the IC50 of PTS and PTSO against Jurkat cells were in the same concentration range (10.6 and 15.7 μM, respectively). In recent years, the use of blood cells from healthy volunteers has become a model increasingly popular as a method to determine the toxicity of a compound, instead of using established human cell lines [51]. In the assay to test the antiproliferative effect of PTS and PTSO in PBMCs, high concentrations of both compounds were necessary to affect the viability of these healthy cells (IC50 > 200 µM). These concentrations lead to high TIs. Another proof of the harmlessness of PTS and PTSO is the fact that certain concentrations of these compounds could increase the population of hMSCs, as seen in Figure 2. Consequently, our results are indicative of the large margin of safety of PTS and PTSO and, therefore, of their potential to be tested in in vivo treatments against neoplastic pathologies. These results in PBMCs are consistent with those obtained in previously conducted in vivo assays, in which it was demonstrated that PTSO did not cause toxicity in Sprague Dawley rats administered 55 mg PTSO/kg body weight/day for 90 days, without showing liver damage, neither clinical signs nor mortality [27,52,53]. Oxidative stress can damage membrane lipids, proteins, and nuclear and mitochondrial DNA in cells. The assays related to oxidative stress revealed that populations of MCF-7 and T-84 decreased significantly after treatment only with PTS or PTSO at IC50 concentrations, compared to cells treated with the same concentrations but also pre-incubated with NAC. This effect was more evident in MCF-7 cells, whose population increased around $40\%$ compared to cells induced in the absence of NAC but only with both onion-derivative compounds (Figure 3). These findings may be justified by the fact that NAC exerts an antioxidant and protective effect against PTS and PTSO, which involved lower cell death. In the assay performed with DCFH-DA, a ROS indicator, it was observed that MCF-7 cells incubated only with PTS or PTSO showed a lower fluorescence, which corresponds to a lower cell density (Figure 4). As it is widely known, tumor cells have a high level of oxidative stress compared to healthy cells, and this is related to an increase in ROS production due to changes in their metabolism [54,55,56]. When MCF-7 cells were induced with any of the compounds for 24 h but also preincubated with NAC, their viability was hardly affected as their fluorescence increased. Therefore, this assay confirms the results obtained in the proliferation assays conducted in the absence or presence of NAC (Figure 3). It could be concluded, hence, that oxidative stress seems to be involved in the mechanism of action of PTS and PTSO, as occurs with other known antitumor agents such as elesclomol or paclitaxel, among others [57,58]. Nevertheless, it must be considered that the cytotoxic activity of both compounds could also be due to their pro-apoptotic action. Similar findings have been reported with DADS in experiments conducted with A-549 and PC-3 cells [59], where the treatment with NAC was able to block both the production of ROS (e.g., H2O2) and apoptosis. Other authors have reported that DATS-induced apoptosis was associated with ROS production in several of the lines tested in our trials, such as MCF-7 [60,61]. However, there are other articles reporting that ROS generation appears to play only a secondary role in the cytotoxicity of OSCs in tumor cells. For example, in an assay conducted with esophageal cancer cells WHCO1 [62], it was observed that ROS was not the main cause of cytotoxicity of garlic-related disulfides, although NAC was still able to interfere with the assay. As oxidative stress and ROS levels seem to affect cancer development, personalized treatments for patients should be addressed, considering the basal antioxidant status, type of cancer, and mechanisms of action of drugs [63,64,65]. Moreover, various studies suggest that the intake of supplements or foods with an antioxidant capacity may not be generally recommended during chemotherapy treatments [66,67]. As previously stated, tumor cells used to be more sensitive to drugs that generate large amounts of ROS, or that affect the ability of cells to eliminate them, which has been associated with their death by apoptosis [68,69]. Apoptosis is the programmed cell death characterized by a series of morphological events, including DNA fragmentation, cell shrinkage, and the formation of membrane-bound apoptotic bodies that are rapidly phagocytized by neighboring cells [70,71]. Our results revealed that there were significant differences in the fraction of early and late apoptosis in MCF-7 and T-84 cells induced with PTS and PTSO, indicating that both compounds would be able to induce apoptosis in tumor cells. According to the literature, there are studies that state that the regular intake of garlic reduces neoplastic growth and tumor cells proliferation by inducing apoptosis [72,73]. Regarding, specifically, OSCs, it has been reported that DADS showed a significant induction of apoptosis in a human gastric adenocarcinoma cell line [74], and allicin supplementation induced death by apoptosis in several colon tumor cell lines, including HT-29 [75]. Therefore, the way that PTS and PTSO exhibit their antitumor activity seems to be similar to other OSCs. However, since the autophagy and apoptosis regulated by ROS are cellular processes that can interact with each other [76], further studies would be necessary to determine if autophagy is also involved in the mechanism of action of PTS and PTSO. In summary, the reported IC50 of PTS and PTSO in the tumor lines tested are in the same range than those of the common OSCs whose antitumor effect has been proven. Nevertheless, given their higher stability compared to substances such as allicin or DADS, PTS and PTSO could be considered promising candidates to use in anticancer treatments, alone or as adjuvants of chemotherapy drugs. This approach was described by Perez-Ortiz et al., who co-administered a thiosulfinate-enriched garlic extract with 5-fluorouracil (5-FU), achieving a greater effectiveness than standard chemotherapy with 5-FU and oxaliplatin [29]. Similarly, other dietary compounds have also been used as adjuvants, such as curcumin [77], epigallocatechin gallate (EGCG) [78], and lycopene [79]. In the anti-inflammatory assays, both PTS and PTSO were able to reduce the levels of three pro-inflammatory cytokines usually involved in the development of cancer: IL-8, IL-6, and IL-17. Some authors correlate IL-6 levels with tumor stage, the metastasis survival rate, or apoptosis in various types of cancer, such as breast [80] or colon [81], while the production of IL-8 has been linked to pro-tumorigenic roles which influence the tumor microenvironment [82]. The IL-17 cytokine is widely recognized for its ability to modulate the inflammatory response, contributing to the development of chronic inflammation [83], and its level could increase in the serum and tissues of patients with CRC [84]. In fact, in vivo studies related to this type of cancer have shown that IL-17 plays an important role in its prognosis and metastasis [85]. As previously stated, the production of this cytokine and IL-8 was significantly reduced by PTS and PTSO in both cell lines, HT-29 and T-84. However, compared to the control, the reduction of IL-6 was only achieved in HT-29 cells. Interestingly, most of the highest reductions in the production of pro-inflammatory cytokines were obtained with the lowest concentrations of PTS and PTSO. Thus, these OSCs would not act in a dose-dependent manner to exert their anti-inflammatory activity, making their action dependent on the cancer cell line characteristics. In agreement with our findings, PTS and PTSO have previously demonstrated their immunomodulatory effect in several animal models. Concretely, PTSO was tested in two experimental models of colitis, which were associated with the regulation of cytokines in inflamed colonic tissue, leading to a reduction of pro-inflammatory cytokines IL-1β, TNF-α, and IL-6 [86]. In a more recent work, PTSO showed its capacity of attenuating the obesity-associated systemic inflammation, reducing the expression of the mentioned cytokines in adipose and hepatic tissues in mice [87]. Moreover, in a murine model, PTS was able to normalize the levels of IL-22 of animals fed an obesogenic diet [88]. ## 5. Conclusions PTS and PTSO were able to inhibit the growth of human tumor lines MCF-7, T-84, A-549, HT-29, Panc-1, Jurkat, PC-3, SW-837, and T1-73. In addition, both compounds showed high TIs and were able to induce hMSCs proliferation at low concentrations. Furthermore, PTS and PTSO reduced the values of pro-inflammatory cytokines IL-6, IL-8, and IL-17 in HT-29 and T-84 lines. The generation of ROS and apoptosis seems to be related to the antiproliferative and anti-inflammatory activity of PTS and PTSO in tumor cells. 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--- title: How Does Dietary Intake Relate to Dispositional Optimism and Health-Related Quality of Life in Germline BRCA1/2 Mutation Carriers? authors: - Anne Esser - Leonie Neirich - Sabine Grill - Stephan C. Bischoff - Martin Halle - Michael Siniatchkin - Maryam Yahiaoui-Doktor - Marion Kiechle - Jacqueline Lammert journal: Nutrients year: 2023 pmcid: PMC10058690 doi: 10.3390/nu15061396 license: CC BY 4.0 --- # How Does Dietary Intake Relate to Dispositional Optimism and Health-Related Quality of Life in Germline BRCA1/2 Mutation Carriers? ## Abstract Background: The Mediterranean diet (MD) is an anti-inflammatory diet linked to improved health-related quality of life (HRQoL). Germline (g)BRCA$\frac{1}{2}$ mutation carriers have an increased risk of developing breast cancer and are often exposed to severe cancer treatments, thus the improvement of HRQoL is important. Little is known about the associations between dietary intake and HRQoL in this population. Methods: We included 312 gBRCA$\frac{1}{2}$ mutation carriers from an ongoing prospective randomized controlled lifestyle intervention trial. Baseline data from the EPIC food frequency questionnaire was used to calculate the dietary inflammatory index (DII), and adherence to MD was captured by the 14-item PREDIMED questionnaire. HRQoL was measured by the EORTC QLQ-C30 and LOT-R questionnaires. The presence of metabolic syndrome (MetS) was determined using anthropometric measurements, blood samples and vital parameters. Linear and logistic regression models were performed to assess the possible impact of diet and metabolic syndrome on HRQoL. Results: Women with a prior history of cancer ($59.6\%$) reported lower DIIs than women without it ($$p \leq 0.011$$). A greater adherence to MD was associated with lower DII scores ($p \leq 0.001$) and reduced odds for metabolic syndrome (MetS) ($$p \leq 0.024$$). Women with a more optimistic outlook on life reported greater adherence to MD ($p \leq 0.001$), whereas a more pessimistic outlook on life increased the odds for MetS (OR = 1.15; $$p \leq 0.023$$). Conclusions: This is the first study in gBRCA$\frac{1}{2}$ mutation carriers that has linked MD, DII, and MetS to HRQoL. The long-term clinical implications of these findings are yet to be determined. ## 1. Introduction With continual improvements in cancer outcomes, both patients and clinicians are shifting their focus from survival alone towards improving health-related quality of life (HRQoL) and patient-centred functional outcomes [1]. HRQoL is defined as the impact a disease and its treatment have on a patient’s physical, functional, psychological, social, and financial well-being [2,3,4]. In cancer care, there is a growing recognition of the significance of HRQoL, as reduced HRQoL may result in lower treatment adherence [5] and an increased risk of mortality [6]. A more comprehensive definition of HRQoL could encompass dispositional optimism, which is a psychological attribute associated with health advantages [7]. Different aspects of HRQoL have been associated with chronic inflammation, i.e., decreased physical [8] and cognitive functioning [9], increased fatigue [10] and higher pain levels [11]. Pre-treatment inflammatory status may predict the development of common cancer treatment side effects [12], e.g., aromatase inhibitor-induced musculoskeletal syndrome in women with pre-existing musculoskeletal pain. Most importantly, elevated inflammatory markers have been associated with adverse cancer outcomes [13,14], potentially by promoting a microenvironment for tumour growth and metastasis [15]. The quantity, quality, and composition of foods have been shown to regulate inflammation [16,17,18]. This has prompted research into developing a literature-derived index to reflect the inflammatory potential of diets; the Dietary Inflammatory Index (DII) [19] scores an individual’s diet on a continuum from anti- to pro-inflammatory. A pro-inflammatory diet has been linked to an increased cardiovascular risk and mortality [20], and it increases the likelihood of both metabolic syndrome (MetS) [21] and various types of cancer [22,23,24,25]. Recent studies indicate a negative association between a pro-inflammatory diet and HRQoL [26,27,28]. A diet associated with low DII scores is the Mediterranean diet (MD) [29]. MD is characterized by high consumption of fruits, vegetables, legumes, grains, and polyunsaturated fats from olive oil and nuts, moderate consumption of fish and dairy products, and low intake of red meat and processed foods [30]. MD has been shown to be associated with reduced cardiovascular risk [31], prevent MetS and lower cancer risk [32]. Furthermore, adherence to MD has been linked to improved HRQoL in healthy individuals [33,34], as well as cancer survivors [35]. Breast cancer (BC) is the most common type of cancer in women [36]. Particularly vulnerable are women with a germline (g)BRCA$\frac{1}{2}$ mutation have a risk of 69–$72\%$ of developing breast cancer and a risk of 17–$44\%$ of developing ovarian cancer by the age of 80 years [37]. These women are exposed to cancer treatments and/or prophylactic surgeries with detrimental short- and long-term effects on their health [38,39,40,41,42] and HRQoL [6,43,44,45]. Recent studies suggest that beneficial dietary changes after completing primary cancer treatment, as opposed to during treatment, might be most effective in improving HRQoL [46]. Dietary factors to reduce chronic inflammation and improve metabolic profile may be an approach to improving HRQoL, functional capacity, and cancer outcomes in women with a gBRCA$\frac{1}{2}$ mutation. A first step in addressing this issue is to determine the relationship of DII, MD, MetS, and different aspects of HRQoL in gBRCA$\frac{1}{2}$ mutation carriers with and without a previous history of cancer. ## 2.1. Study Design and Participants The present study is a cross-sectional secondary analysis of the baseline data from the randomized controlled LIBRE-2 trial (a lifestyle intervention study in women with hereditary breast and ovarian cancer) and the associated feasibility study LIBRE-1 [47,48]. The trials are registered at ClinicalTrial.gov (NCT numbers: NCT02087592–registered on 14 March 2014, NCT02516540–registered on 6 August 2015). The LIBRE-2 trial is an ongoing, two-armed randomized (1:1) controlled multicentre trial conducted in Germany aimed at determining the impact of a structured one-year lifestyle intervention program on adherence to MD, cardiorespiratory fitness, and body mass index (BMI) among gBRCA$\frac{1}{2}$ mutation carriers. The study cohort includes both women with a previous diagnosis of early stage cancer in remission (diseased) and without a prior cancer diagnosis (non-diseased). Details on the study design have been published elsewhere [47,48]. A total of 312 participants were available for the current analysis. ## 2.2. Instruments Blood samples, anthropometric measurements, and medical history. At baseline, participants completed a standardized questionnaire to collect information on their medical history, socio-demographic factors, as well as lifestyle factors. Furthermore, all participants underwent a physical examination to determine systolic and diastolic blood pressure, heart rate, and anthropometric measurements such as height (in m), body weight (in kg), and waist and hip circumferences (in cm). These were used to calculate BMI (kg/m2) and the waist-to-hip ratio (waist circumference in cm/hip circumference in cm). Blood samples were taken after a 12-h fasting period, and analysed by the affiliated laboratories of the local institutions. MetS was defined according to the International Diabetes Federation criteria by the presence of a waist circumference ≥ 80 cm and at least two metabolic abnormalities, i.e., fasting glucose ≥ 100 mg/dL, systolic blood pressure ≥ 130 mmHg and/or diastolic blood pressure ≥ 85 mmHg, triglycerides ≥ 150 mg/dL, HDL-cholesterol < 50 mg/dL and/or treatment with lipid-lowering, glucose-lowering or antihypertensive drugs. Cardiopulmonary exercise testing was conducted to assess cardiorespiratory fitness via peak oxygen uptake (VO2peak). FFQ, MEDAS and Dietary Inflammatory Index. Dietary intake was determined by two validated questionnaires. The participants completed the German version of the PREDIMED questionnaire, the Mediterranean diet adherence screener (MEDAS), a 14-item questionnaire that captures adherence to MD [49,50,51]. We calculated the MEDAS score as the percentage of positively answered questions [52]. Additionally, the German version of the EPIC food frequency questionnaire (FFQ) was applied to collect information on the quantity and frequency of 148 food items consumed over the previous year [53,54]. Data from the FFQ were then used to calculate DII using the method reported by Shivappa et al. [ 19]. Briefly, the DII is based on 1943 scientific papers scoring 45 food parameters according to whether they increased (+1), decreased (−1), or had no effect [0] on six inflammatory biomarkers (IL-1β, IL-4, IL-6, IL-10, TNF-α, and CRPs). As reported in previous studies [22,55,56,57], not all required food items were assessed by the German FFQ. Hence, the DII was calculated using the corresponding 30 food parameters available from the FFQ used in our study. Those were carbohydrates, protein, saturated fat, polyunsaturated fatty acids (PUFA), monounsaturated fatty acids (MUFA), n-3-fatty-acids, n-6-fatty-acids, cholesterol, total fat, energy, fibre, alcohol, iron, magnesium, zinc, vitamin A, thiamin, vitamin B12, riboflavin, niacin, vitamin B6, folic acid, vitamin C, vitamin D, vitamin E, flavonones, anthocyanidins, flavan-3-ol, flavonols, and flavones. Psychological questionnaires. All LIBRE trial participants completed several psychological questionnaires. To assess optimism and pessimism as a personality trait, the revised 10-item life orientation test (LOT-R) was applied [58]. The “optimism score” (LOTR-O) ranging from 0 (minimally optimistic) to 12 (maximally optimistic) was calculated as the sum of the three positively formulated items. The “pessimism score” (LOTR-P) was calculated accordingly. The EORTC QLQ-C30 (questionnaire for quality of life assessment in patients with cancer, Version 3.0) [3] was used to evaluate HRQoL. This questionnaire consists of 30 items and is designed for patients receiving cancer treatment regardless of cancer type and location. It measures five functional dimensions (physical, role, emotional, cognitive, and social), three symptom items (fatigue, nausea or vomiting, and pain), six single items (dyspnea, insomnia, appetite loss, constipation, diarrhea, and financial impact), and a global health status, which is the mean of two questions regarding overall health and overall quality of life. The BKAE (“Bewertung körperlicher Aktivität und Ernährung”, in English “evaluation of physical activity and nutrition”) is a questionnaire designed specifically for the LIBRE trials [47,48] to analyse attitudes and views on physical activity and dietary intake. It is based on the concept of “planned behaviour” by Fishbein & Ajzen [1975] [59] promoting that attitude, subjective norms and perceived behaviour control contribute to behavioural intention, which leads to actual behaviour. We only used the dietary information of the questionnaire for our analysis. The scores BKAE-AT (attitude towards healthy eating), BKAE-SN (subjective norms about healthy eating), BKAE-PBC (perceived behaviour control over healthy eating), BKAE-IT (intention to eat healthy in the future) and BKAE-PB (past behaviour with regard to healthy eating) range from 0 (minimum) to 100 (maximum). The physical activity part of the questionnaire has been evaluated previously; the strongest predictor for cardiopulmonary fitness was attitudes towards physical activity [60]. ## 2.3. Statistical Analysis SPSS Version 29.0.0 (IBM Corp., Armonk, NY, USA) was used to analyse data. Descriptive statistics are presented as mean ± standard deviation (SD) for continuous variables or as proportions for categorical variables. The distributions of continuous variables between diseased and non-diseased women were compared using Student’s t-test. The distributions of categorical variables were compared using the Chi-square test. Linear regression models were created to detect associations between dietary intake and HRQoL. EORTC-QC30 scores were evaluated in diseased women only since the questionnaire was validated for cancer patients. Logistic regression models were performed to estimate odds ratios (ORs) and their associated $95\%$ confidence intervals ($95\%$ CI) between MetS, dietary intake and different aspects of HRQoL. Multivariate analyses were carried out to control for potential confounding variables. These analyses were adjusted for body composition (BMI), physical fitness (VO2peak), adherence to MD, and/or dietary inflammatory potential (DII). All p values were based on two-sided tests and were considered significant if p ≤ 0.05. ## 2.4. Ethics The study was approved by the ethics committees of both the host institutions Technical University of Munich (Reference No. $\frac{5685}{13}$), the University Hospital Cologne (Reference No. 13-053), the University Hospital Schleswig-Holstein in Kiel (Reference No. B-$\frac{235}{13}$), and the participating study centres. Written consent from all study participants was obtained. All methods were carried out in accordance with relevant guidelines and regulations. ## 3. Results A total of 312 women with a gBRCA1 and/or gBRCA2 mutation were included in the study. Table 1 summarizes the selected participants’ characteristics by health status (diseased vs. non-diseased). The mean age of the entire study cohort was 43.5 years (SD ± 10.3 years). Of all the women, $59.6\%$ had a previous diagnosis of cancer. Among these, breast cancer accounted for $88.7\%$ and ovarian cancer for $7.0\%$ of all cancer cases. Women with a history of breast cancer were older (46.5 years vs. 39.1 years, $p \leq 0.001$), more likely married ($67\%$ vs. $55\%$, $$p \leq 0.026$$), and less educated (high school diploma: $58\%$ vs. $75\%$, $$p \leq 0.002$$). Diseased women had significantly lower hsCRP levels (1.7 vs. 3.3 mg/L, $$p \leq 0.045$$) and lower DII scores (−1.1 vs. −0.5, $$p \leq 0.011$$) compared to non-diseased women. Non-diseased mutation carriers had better physical fitness (17.3 vs. 16 mL/min/kg, $$p \leq 0.029$$), reported significantly higher quality of life (QL2 72.2 vs. 57.7, $$p \leq 0.041$$), role (RF 90.3 vs. 79.8, $p \leq 0.001$), cognitive (CF 82.5 vs. 72.9, $p \leq 0.001$) and social functioning (SF 85.2 vs. 72.0, $p \leq 0.001$), and experienced less pain (PA 15.7 vs. 25.6, $$p \leq 0.001$$), dyspnea (DY 9.6 vs. 16.1, $$p \leq 0.015$$), insomnia (SL 28.0 vs. 39.4, $$p \leq 0.003$$), and fewer financial difficulties (FI 4.3 vs. 18.5, $p \leq 0.001$). On the other hand, diseased mutation carriers reported stronger social norms about healthy eating (BKAE-SN 79.6 vs. 73.7, $$p \leq 0.008$$) and greater behavioural control over healthy eating (BKAE-PBC 86.9 vs. 84.2, $$p \leq 0.010$$). They also reported a more frequent consumption of healthy foods compared to women without a prior history of cancer (BKAE-PB 58.5 vs. 51.6; $$p \leq 0.008$$). We then analysed associations between DII and various metabolic and lifestyle factors using linear regressions. The results are presented in Table 2. A lower DII score was significantly associated with higher adherence to MD ($p \leq 0.001$). Among diseased women, higher DII scores were associated with better role functioning (RF) ($$p \leq 0.032$$), cognitive functioning (CF) ($$p \leq 0.003$$), and social functioning (SF) ($$p \leq 0.012$$) as well as decreased fatigue (FA) ($$p \leq 0.046$$), dyspnea (DY) ($$p \leq 0.029$$) and appetite loss (AP) ($$p \leq 0.007$$). Associations between adherence to MD (MEDAS) and various factors were carried out using linear regressions (see Table 3). Adherence to MD was associated with higher VO2peak ($$p \leq 0.024$$), as well as lower DII scores (p = <0.001). Furthermore, adherence to MD was associated with dispositional optimism ($$p \leq 0.001$$). We then carried out logistic regression models to estimate odds ratios (OR) and their associated $95\%$ confidence intervals ($95\%$ CI) of having metabolic syndrome (MetS) by different dietary variables and different aspects of HRQoL (see Table 4). Higher adherence to MD (MEDAS ≥ 0.50) reduced odds for MetS (OR = 0.538, $$p \leq 0.024$$). Women with dispositional pessimism had increased odds for MetS (OR = 1.147, $$p \leq 0.023$$). Among diseased women, those who had poorer physical functioning (OR = 0.955, $p \leq 0.001$) or experienced more dyspnea (OR = 1.017, $$p \leq 0.012$$) had increased odds for MetS. ## 4. Discussion The aim of this analysis was to evaluate the relationship between anti-inflammatory diet, metabolic syndrome (MetS), and different aspects of health-related quality of life (HRQoL) in gBRCA$\frac{1}{2}$ mutation carriers. gBRCA$\frac{1}{2}$ mutation carriers have a very high lifetime risk of developing breast and/or ovarian cancers. The average age of cancer diagnosis is substantially younger than in the general population [37]. BRCA-associated cancers exhibit pathological features suggestive of an aggressive phenotype [61,62,63], and therefore, most patients undergo chemotherapy with detrimental side effects. When diagnosed with ER-positive breast cancer, patients might benefit from an extended adjuvant endocrine therapy [64,65], especially premenopausal women [66]. However, adjuvant endocrine therapy impacts HRQoL negatively [67]. Thus, identifying modifiable lifestyle factors to improve HRQoL is of particular relevance to gBRCA$\frac{1}{2}$ mutation carriers, possibly resulting in better treatment adherence and (cancer-free) survival. We observed that diseased women consumed a more anti-inflammatory diet compared to non-diseased women (DII −1.1 vs. −0.5, $$p \leq 0.011$$). Moreover, diseased participants perceived greater behavioural control over selecting healthier food options and were more likely to make healthier food choices than women without a history of cancer. This conforms to previous research that a breast cancer diagnosis can lead to beneficial dietary changes [68]. The German breast cancer guideline issued by the German Association of the Scientific Medical Societies (AWMF) and the German Agency for Quality in Medicine (AeZQ) acknowledges the importance of lifestyle factors, such as diet and physical activity, in the aftercare of breast cancer patients. However, it was not until 2017 that the guideline included this recommendation [69]. The guideline suggests adhering to the dietary guidelines set by the German Society for Nutrition (DGE), which emphasize the consumption of plant-based foods such as cereal, grains, fruits, and vegetables as the foundation of a healthy diet, with small portions of animal products such as dairy, eggs, meat, and fish [70]. Compared to the MD, the consumption of olive oil, fish, seafood, and red wine is less emphasized in the DGE guidelines. As four items of the MEDAS focus on these food groups, it is possible that the lack of emphasis on them in the DGE guidelines may explain why diseased women in our study did not report a higher adherence to the MD compared to non-diseased women. Of interest is the significant inverse association between adherence to MD and DII, indicating that MD is an anti-inflammatory diet (p = <0.001). In a prospective study, Hodge et al. [ 2016] identified MD as an anti-inflammatory diet that significantly reduced the risk of lung cancer [29]. The PREDIMED trial was the first randomized controlled trial to support these findings in a group of postmenopausal females; adherence to MD reduced the risk of breast cancer by $68\%$ ($95\%$ CI 0.13–0.79) [69]. Porciello et al. [ 35] reported that adherence to MD in breast cancer survivors was associated with better HRQoL, i.e., improved physical functioning, better sleep quality and lower pain. We were not able to show an association between adherence to MD and HRQoL among diseased gBRCA$\frac{1}{2}$ mutation carriers in our univariate and multivariate analyses. In our analysis, the median time from cancer diagnosis to study enrolment was four years (range: 1–48 years). To be eligible for participation in the LIBRE study, women had to be physically fit and functional, and several criteria that could hinder participation in the intervention program had to be excluded at study entry. These criteria included ongoing chemotherapy and/or radiation therapy, metastatic tumor disease, Karnofsky index below $60\%$, and exercise capacity below 50 watts. Consequently, our study participants were likely much fitter and more functional than those in Porciello et al. ’s study, where women had to be diagnosed with breast cancer within the previous twelve months and had a mean age that was ten years older than our study participants. In our study, adherence to MD was positively associated with dispositional optimism (p ≤ 0.001). This finding is consistent with the results of a study by Ait-Hadad et al. [ 70], which investigated the relationship between dietary intake and dispositional optimism in a sample of over 32,000 participants. The authors reported a positive association between optimism and overall diet quality; high intake of fruits, vegetables, legumes, whole grains, seafood, and fats was positively associated with optimism, while high intake of meat and dairy products was negatively associated with optimism. Dispositional optimism is characterized as a general expectation or belief in positive outcomes in the future [71]. It has been associated with improved cardiovascular health and reduced all-cause as well as cause-specific mortality in large epidemiological studies [72,73]. Among breast cancer patients, optimism has been linked to psychological well-being and improved quality of life [74,75]. Boehm et al. found that dispositional optimism was associated with higher serum levels of antioxidants [76]. This association was partially influenced by dietary intake. Scheier and Carver [77] suggest that there are two underlying mechanisms linking optimism to health. Firstly, dispositional optimism facilitates the engagement in health promoting behaviours, i.e., diet and physical activity. Secondly, optimistic individuals better cope with adverse life events better than pessimistic individuals, which results in reduced stress levels and increased physiological wellbeing. Although dispositional optimism is considered to be relatively stable across one’s lifespan, some studies found that cognitive therapy can increase optimism levels [78,79]. Since dispositional optimism and MD are linked in gBRCA$\frac{1}{2}$ mutation carriers, identifying further strategies to increase dispositional optimism might help to implement a healthy diet. Moreover, adherence to MD was associated with reduced odds for MetS (OR = 0.54, $$p \leq 0.024$$). An Italian randomized controlled trial found that an MD-based dietary intervention in gBRCA$\frac{1}{2}$ mutation carriers improved adherence to MD and reduced components of MetS [80]. Recent studies suggest that MetS is associated with impaired HRQoL [81,82,83]. Cohen et al. [ 84] reported a positive association between pessimism and the prevalence of MetS in patients with coronary heart disease. In our analysis, we found a positive association between MetS and dispositional pessimism (OR = 1.15, $$p \leq 0.023$$). In univariate analyses, MetS was associated with poorer physical functioning (OR = 0.96, p = <0.001) and higher levels of dyspnea (OR = 1.02; $$p \leq 0.012$$) among diseased women. However, these associations diminished following adjustment for physical fitness (VO2max). In women with a history of cancer, higher DII scores were associated with better role functioning (RF), cognitive functioning (CF), and social functioning (SF), as well as reduced fatigue (FA), reduced dyspnea (DY), and reduced appetite loss (AP). These findings were robust after adjustment for body composition (BMI), physical fitness (VO2peak), and adherence to MD. To rule out that different types of cancer treatment or time since diagnosis influenced these associations, we calculated further multivariate regression models (see Appendix A). Our results were similar (see Table A1, Table A2 and Table A3). This is surprising since it is contradictory to prior findings indicating that a more pro-inflammatory diet is associated with reduced HRQoL [28]. A possible explanation could be that diseased women with better HRQoL were not concerned about healthy eating. According to the theory of planned behaviour by Fishbein and Ajzen, behaviours are influenced by intentions, which are determined by three factors: attitudes, subjective norms, and perceived behavioural control [59]. To test our hypothesis, we adjusted our multivariate regression models for associations between DII and different dimensions of EORTC QLQ-C30 for the three core components of the Fishbein and Ajzen model, i.e., attitudes, subjective norms and perceived behavioural control. None of the three factors were associated with a pro-inflammatory diet nor did they influence the link between greater DII scores and reduced role, cognitive and social functioning (see Appendix A—Table A4). After inserting the variables attitudes, social norms and perceived behavioural control into the linear regression models for DII and fatigue, dyspnea and appetite loss, the models no longer reached significant levels ($$p \leq 0.059$$–0.143). Thus, in our analysis, the positive associations between pro-inflammatory diet patterns and HRQoL were likely not influenced by attitudes and beliefs towards healthy eating. ## Strengths and Limitations The strengths of the current study include the comprehensive evaluation of predictors that could be linked to HRQoL in gBRCA$\frac{1}{2}$ mutation carriers. After adjusting for body composition, physical fitness and eating patterns, the adjusted and unadjusted results did not differ significantly. Therefore, any additional confounding was likely to be small. This supports our hypothesis that dietary intake is linked to different aspects of HRQoL. Although our results provide an interesting direction for HRQoL research, this study had several limitations. Firstly, the nature of a cross-sectional secondary analysis cannot establish a cause-and-effect relationship. The prospective nature of the LIBRE trials will allow for evaluating the impact of dietary changes on HRQoL. Secondly, as the number and type of food components to compute DII vary between studies, our results can hardly be compared to other populations of gBRCA$\frac{1}{2}$ mutation carriers. Our study cohort was not representative for the average German population regarding education, net income, marital status, and parity [85,86,87,88]. 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--- title: 'Factors Deciding Conservative or Intervention Treatment for Prostate Abscess: A Retrospective Case-Control Study' authors: - Yi-Huei Chang - Szu-Ying Pan - Chia-Yu Lin - Chi-Ping Huang - Chi-Jung Chung - Yung-Hsiang Chen - Wen-Chi Chen journal: Journal of Personalized Medicine year: 2023 pmcid: PMC10058703 doi: 10.3390/jpm13030484 license: CC BY 4.0 --- # Factors Deciding Conservative or Intervention Treatment for Prostate Abscess: A Retrospective Case-Control Study ## Abstract Prostate abscess (PA) can lead to severe urosepsis and septic shock if not treated promptly. However, early diagnosis can be hindered by the declining incidence of PA, especially in developing countries and high-risk patients. Despite the prevalence of PA, there is currently a lack of well-established contemporary guidelines or treatment algorithms. This study aimed to review the etiology, pathophysiology, diagnosis, and treatment options for PA, as well as analyze the characteristics, background profiles of patients, and clinical course. Ultimately, the goal was to develop a personalized treatment strategy for patients with PA. This retrospective study examined 44 patients diagnosed with PA at a tertiary medical center between 2010 and 2020. The patients were divided into two groups based on their treatment: conservative treatment or intervention (transurethral resection of the prostate [TURP] or transurethral prostate drainage [TPD]). The study evaluated various factors, including patients’ background profiles, comorbidities, laboratory data, and PA size and volume. Complications of the interventions were also analyzed. No significant differences were found in basic data between the conservative treatment group (19 patients) and intervention group (25 patients; 20 for TURP, 5 for TPD). However, it was observed that single abscesses, size <2.2 cm, and prostate volume <48 cm3, may be suitable for conservative treatment. Patients with diabetes mellitus and human immunodeficiency virus should be monitored for thrombotic events. In addition, there was a significant difference in white blood count between the two groups (12.1 ± 7.0 vs. 17.6 ± 9.7 × 109/L, $p \leq 0.05$). A subgroup analysis of the intervention group showed no significant difference in the risk of complications between TPD and TURP. Patients with poorly controlled diabetes mellitus and immunodeficiency are at a high risk of PA but are not indicated for surgical treatment. The PA profile, including number, size, volume, and percentage to prostate volume, should be considered when deciding on surgical intervention for patients with PA. Patients with higher leukocytosis may require surgical treatment. Overall, these findings can help guide the development of a personalized treatment strategy for patients with PA. ## 1. Introduction Prostate abscess (PA) is a type of acute infection that affects the lower urinary tract [1,2]. Fortunately, the incidence of PA has decreased in recent years due to the widespread use of antibiotics. Nevertheless, patients with PA can still experience a range of distressing symptoms, including dysuria, frequency, urgency, and urinary retention [3]. Additionally, individuals with PA often present with fever and perineal pain. While broad-spectrum antibiotics are commonly used to combat infections, conservative treatment may fail to effectively resolve the abscess in some instances. In light of the emergence of antibiotic-resistant bacteria, atypical infections, and immunocompromised patients, managing PA has become increasingly challenging. In fact, a recent study by Ackerman and colleagues suggested that surgical drainage should be initiated promptly in such cases to prevent complications such as sepsis and septic shock [4]. Therefore, it is critical to further investigate the timing and indications for surgical treatment in patients with PA. Doing so may help healthcare professionals to optimize patient outcomes [5,6,7] and reduce the risk of severe complications associated with this condition. The current state of PA treatment guidelines is lacking, and further research is needed in this area [8]. In a retrospective review of 18 patients with PA, Oshinomi et al. divided the treatment into two groups: conservative and drainage [9]. The use of imaging modalities is crucial for the accurate diagnosis and effective management of PA. Ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI) are just a few of the imaging techniques available for this purpose. These imaging modalities can provide valuable information on the size, location, and number of abscesses in the prostate gland. In a study by Ackerman et al., it was found that abscesses larger than 30 mm are an indication for transurethral drainage, regardless of whether they are focal or multiple. However, the optimal approach to treating patients with urinary retention remains unclear, as this aspect was not investigated in the aforementioned research. Furthermore, CT imaging is particularly useful for accurately diagnosing PA, especially when differentiating it from other urinary tract infections. Given the rise in antibiotic-resistant strains of bacteria, prompt diagnosis and appropriate treatment initiation based on imaging findings are crucial for managing PA and reducing the risk of severe complications such as sepsis and shock [10]. Additional research in this area may provide valuable insights into optimizing PA treatment protocols and improving patient outcomes. This retrospective study aimed to comprehensively evaluate the most effective treatment modalities for patients diagnosed with PA. In order to achieve this goal, the investigation conducted an extensive analysis of the patients’ medical history, comorbidities, therapeutic interventions, and clinical outcomes. The findings of this study carry substantial implications for clinical practice, furnishing crucial insights that can guide medical professionals in developing personalized treatment plans for patients afflicted with PA [11,12,13,14]. The results of this research have the potential to significantly enhance patient outcomes and, as a result, elevate the quality of care provided to individuals grappling with this condition. ## 2.1. Patients and Study Design Prior to commencement, the study underwent a rigorous review process and received ethical approval from the Institutional Review Board of China Medical University Hospital (IRB: CMUH 112-REC1-014), Taichung, Taiwan. This board is responsible for ensuring that all research involving human subjects adheres to the highest ethical standards and that the rights and welfare of study participants are protected. The approval of the IRB indicates that the study was designed and conducted in a manner that prioritized the safety and wellbeing of the participants while producing scientifically sound results. It is important to note that obtaining ethical approval from an IRB is a critical step in any research involving human subjects, as it indicates that the study meets the ethical guidelines and standards set forth by regulatory bodies. This commitment to ethical conduct not only protects the rights of participants, but also helps to establish trust and confidence in the research findings among the broader scientific community and the general public [15,16,17]. From January 2010 to Mach 2020, a total of 44 male patients diagnosed with a PA were recruited from China Medical University Hospital. The recruitment process involved a thorough evaluation of patients presenting with suspected PA for clinical symptoms and laboratory data. The presenting symptoms of patients included typical lower urinary tract symptoms such as dysuria, urgency, frequency, and urinary retention, as well as fever or perineal pain. Laboratory data revealed the presence of an infection, including leukocytosis and pyuria. The diagnosis of PA was made based on a combination of clinical presentation, laboratory findings, and imaging studies, such as suprapubic ultrasound and CT scans. Patients with small and single abscesses who were in a stable clinical condition and did not have sepsis were treated conservatively with an intravenous administration of broad-spectrum antibiotics, according to the results of cultures. On the other hand, patients with larger and multiple abscesses or those with sepsis required surgical intervention, typically after a 2-week course of intravenous antibiotics had failed. It is worth noting that the decision to opt for conservative or surgical treatment was made after careful consideration of the patient’s clinical condition and imaging findings. Of the 44 patients recruited, 19 were successfully treated with conservative management, indicating the effectiveness of this approach for certain cases of PA. The results of this study contribute to the growing body of knowledge on the optimal management of PA, especially in the context of emerging antibiotic-resistant strains of bacteria and the need for individualized treatment approaches. The interventional treatment group for patients with PA consisted of 5 patients who received transurethral prostate drainage (TPD) and 20 patients who underwent transurethral resection of the prostate (TURP) [18,19]. The size of the abscess and the size of the prostate were important factors in determining the appropriate treatment approach. TPD was used for small abscesses (less than 1 cm3), while TURP was reserved for larger abscesses and prostate size. Comorbidities such as DM, hypertension, CAD, HIV infection, and cirrhosis of the liver were analyzed to determine their impact on treatment outcomes. Laboratory data, such as complete blood count, urine and blood culture; C-reactive protein; and HbA1c, were also analyzed to assess the severity of the infection and the overall health of the patients. The flow chart depicted in Figure 1 provides a visual representation of the study design and patient inclusion criteria. The retrospective analysis of patients with PA involved a thorough review of their medical records, including clinical presentation, laboratory data, imaging studies, and treatment outcomes. The study was approved by the IRB of China Medical University Hospital, ensuring that all ethical considerations were taken into account. Overall, this study provides valuable insights into the optimal management of PA and the factors that influence treatment outcomes. ## 2.2. Statistical Assay SPSS version 25 was used for all statistical analyses (IBM Inc., Armonk, NY, USA). The Student’s t test was used for comparisons of independent numeric parameters between the two study groups. The Mann–Whitney U test was used for non-parametric analysis between the two groups. A p value < 0.05 was considered statistically significant. ## 3. Results Of the 44 patients, 26 ($59.1\%$) initially presented with fever (Figure 2). The second most common presentation was acute urinary retention (nine patients, $18.2\%$), and six patients ($13.6\%$) had symptoms of dysuria. There was no significant difference in average age between the two groups (Table 1). All patients in the study achieved successful treatment outcomes with symptomatic relief and were subsequently discharged. Notably, the intervention group exhibited a considerably prolonged average hospital stay in comparison to the conservative group (18.5 vs. 11.6 days, $$p \leq 0.02$$). The prevalence of diabetes mellitus was higher in the conservative group, with 15 patients ($78\%$) being affected, as opposed to 11 patients ($44\%$) in the intervention group ($$p \leq 0.02$$). Conversely, no significant differences were observed in the incidence of other comorbidities, including cirrhosis, hypertension, coronary artery disease, and human immunodeficiency virus, between the two study groups, as presented in Table 2. The white blood cell (WBC) count in the intervention group was significantly higher than that in the conservative group ($$p \leq 0.04$$). There were no significant differences in laboratory data between the two groups, including urine WBC count, C-reactive protein, HbA1c, and serum creatinine (Table 3). Regarding the PAs, the size, number, and volume of the PAs were significantly larger in the intervention group (Table 1). The prostate volume in the conservative group was 48 ± 14 cm3, compared to 71 ± 27 cm3 in the intervention group ($$p \leq 0.003$$). ## 4. Discussion This study aimed to establish a personalized treatment algorithm for patients with PA by analyzing the records of 44 patients admitted to China Medical University Hospital from 2010 to 2020. The analysis included patients’ background profiles, clinical courses, laboratory studies, PA size and volume, outcomes, and intervention complications. The patients were categorized into conservative ($$n = 19$$) and intervention ($$n = 25$$) groups based on the treatment they received. Among the patients, $59.1\%$ had diabetes mellitus (DM), while other comorbidities included hypertension, coronary artery disease (CAD), liver cirrhosis, and thrombotic events. A small proportion of patients ($6.8\%$) had HIV infection. Our analysis suggests that a personalized treatment approach should be adopted for patients diagnosed with PA. Specifically, patients presenting with smaller PA sizes (less than 2.2 cm in diameter) or low prostate volume (<48 cm3) may be suitable candidates for conservative management. Conversely, patients presenting with larger abscesses or elevated white blood cell counts may benefit from intervention to prevent the progression of the disease and the consequent accumulation of pus in the prostate. As such, we recommend that healthcare professionals carefully evaluate each patient’s unique clinical characteristics before deciding on the most appropriate treatment strategy. In this study, both the conservative and intervention groups had similar basic characteristics, with median ages of 57.1 and 59.6 years, respectively, consistent with the typical age range for PA occurrence. The average hospital stay for the intervention group was significantly longer than that of the conservative group (18.5 vs. 11.6 days), which is in line with previous research by Alnadhari et al. [ 20]. The longer stay in the intervention group may be attributed to more advanced disease and severe symptoms requiring a longer recovery time, as all patients received medical treatment followed by intervention treatment with TURP or TPD. Even though the incidence of PA has decreased with the use of broad-spectrum antibiotics, PA remains a challenge and has a high mortality rate in high-risk groups, including those who are immunocompromised and those with DM. The initial presentation of PA is usually unspecific, and includes fever; acute urinary retention; dysuria; urgency; frequency; the sensation of incomplete voiding and tenesmus, which can therefore be misdiagnosed as urethritis; urinary tract infection; and acute or chronic bacterial prostatitis. If the diagnosis is delayed or neglected, PA can progress to a lethal condition with a mortality rate ranging from $1\%$ to $16\%$ [21]. The treatment of PA can generally be divided into conservative and interventional. Conservative treatment entails the use of broad-spectrum parenteral antibiotics, which are usually given during the hospital course, followed by specific antibiotics based on culture and sensitivity results. The most commonly used intervention treatments are TURP and TPD, both of which have the advantages of a fast recovery, lower recurrence rate, and reduced hospitalization time. The early diagnosis and prompt treatment of PA is crucial [22,23], since most PAs develop from acute or chronic bacterial prostatitis. The initial presentation of a PA is usually non-specific, including systemic symptoms such as fever ($59\%$), acute urinary retention ($18\%$), and dysuria ($14\%$); thus, it can be misdiagnosed as urethritis, urinary tract infection, acute or chronic bacterial prostatitis, benign prostatic hyperplasia, or urinary obstruction. Therefore, further physical examinations, laboratory studies, or imaging studies may be needed for the differential diagnosis [5,24]. According to the literature, over $95\%$ of patients with PA have a painful digital rectal examination [4], with the presence of a palpable fluctuant prostate in $16\%$ to $88\%$ of patients [25,26]. Laboratory results of PA usually mimic a urinary tract infection, with the presence of leukocytosis, pyuria, and bacteria. Since such positive physical examination findings and laboratory results cannot distinguish a PA from prostatitis, Ha et al. suggested that patients with acute prostatitis who do not respond to treatment after 48 h should be evaluated for a possible PA [21]. There can be a correlation between the organisms obtained from abscesses, urine cultures, and blood cultures, but it ultimately depends on the specific case. In general, if there is an infection in the urinary tract, it is possible for bacteria to travel up the urinary tract and cause a kidney or prostate abscess [27]. In such cases, the organisms obtained from the abscess may be similar or identical to those found in the urine culture. If blood cultures were obtained, they can provide valuable information about the presence of bacteremia (bacteria in the bloodstream) and the potential spread of infection to other parts of the body. Positive blood cultures can indicate the presence of the same bacteria that caused the abscess or urinary tract infection, but it is not always the case. Sometimes, different bacteria can cause infections in different parts of the body. Ultimately, the correlation between the organisms obtained from the abscess, urine cultures, and blood cultures will depend on the specific case and the individual’s unique medical history and circumstances. It is important to work closely with a healthcare provider to determine the most appropriate diagnostic and treatment plan for any suspected infection. Concerning prostatic abscesses (PAs), our study observed significant differences in terms of number, size, volume, percentage, and volume between two patient groups. Patients with a larger PA volume (mean ± SD: 25.4 ± 21.7 cm3) necessitated intervention treatment. Our findings suggest that patients diagnosed with a PA exceeding 2 cm in diameter should consider intervention treatment, while those with a smaller PA diameter may be eligible for conservative treatment, although clinical symptoms must be taken into account. Medical interventions may include antibiotic therapy, transrectal ultrasound-guided aspiration or drainage, and surgical excision. Conservative management may consist of antimicrobial agents, analgesics, and close monitoring of the patient’s condition. Further research is needed to explore optimal treatment strategies for PAs of various sizes and clinical presentations. A normal prostate gland is approximately 3 × 3 × 5 cm in size or has a volume of 25 mL [28]. The larger the prostate volume, the higher the likelihood it could develop into BPH and cause symptoms similar to lower urinary tract symptoms, such as increased frequency, urgency, nocturia, dysuria, starting urination, weak urine stream, or dribbling at the end of urination. The symptoms of BPH can be difficult to distinguish from other urinary obstruction diseases, and BPH itself is a risk factor for PA. In the current study, the median prostate volume in the conservative group was 48 ± 18 cm3, compared to 71 ± 27 cm3 in the intervention group. The WBC count results also showed different profiles between the two groups, with 12,100/μL in the conservative group and 17,600/μL in the intervention group, and the difference was statistically significant. These findings are consistent with the clinical features of PA and show that purulent formation within the prostate may exceed the penetration of antibiotics, and that a surgical approach is essential in such cases. Fever of unknown origin is a common presentation in men, and imaging studies such as computed tomography (CT), magnetic resonance imaging (MRI), and transrectal ultrasound are often used to identify potential sources. In some medical centers, transrectal ultrasound is utilized to evaluate the presence of prostatic abscesses. Additionally, in certain institutions, ultrasound-guided transperineal or transrectal needle aspiration is conducted with favorable outcomes, which may be followed by an intracavitary injection of antibiotics. However, our study did not involve transperineal or transrectal aspiration or injection of the abscess. Future research may investigate the effectiveness and safety of such interventions in managing prostatic abscesses, including potential complications such as bleeding, infection, or urinary dysfunction. Further, the development of standardized protocols for the diagnosis and management of prostatic abscesses would aid in providing optimal patient care and outcomes. In the realm of diagnostic imaging, micro-ultrasound (MUS) is an innovative technique that displays potential in enhancing the quality of ultrasonic imaging. MUS is a real-time imaging modality characterized by high spatial resolution, which has recently been introduced in the field of urology. MUS offers a multitude of benefits over traditional ultrasound imaging, including the ability to discern subtle changes in prostatic tissue, augment the visualization of the prostate capsule and surrounding tissue, and heighten the detection of small lesions. Additionally, MUS has the potential to guide biopsy procedures with greater accuracy, reducing the need for repetitive biopsies and mitigating patient discomfort. Future studies may explore the utility of MUS in the diagnosis and management of prostatic abscesses, potentially improving outcomes for patients. This novel tool aims to describe the current evidence regarding the application of MUS for the diagnosis and detection of benign and even malignant lesions. Research has demonstrated high sensitivity and specificity for the diagnosis of prostate cancer with MUS. Given its ability to provide high-resolution images, MUS may also prove useful for the diagnosis of prostatic abscess in the future. The high spatial resolution of MUS allows for precise identification of the location and size of abscesses, which can facilitate the selection of an appropriate management strategy. Furthermore, MUS-guided drainage procedures can potentially reduce the risk of complications and improve patient outcomes. To establish the diagnostic and therapeutic utility of MUS in the management of prostatic abscesses, further studies are necessary. Additionally, studies comparing the accuracy of MUS with other imaging modalities in detecting and characterizing prostatic abscesses would be valuable in determining the most effective diagnostic and management strategies for patients [29]. PA is an uncommon cause of urinary tract infections (UTIs), especially in individuals who have compromised immune systems or abnormalities in their urinary tract. While conservative treatment approaches may be effective in managing mild cases, surgical intervention may be necessary in more severe cases. Determining the optimal timing for surgical intervention is a major clinical challenge. Various drainage procedures have been suggested as potential interventions to reduce the duration of antibiotic therapy, shorten hospital stays, and improve voiding function. The effectiveness of these procedures, however, may be influenced by factors such as the patient’s age, comorbidities, and severity of infection. Therefore, a comprehensive evaluation of each patient’s condition is necessary to determine the appropriate treatment strategy for managing UTIs caused by PA [30]. This study has some limitations, including its retrospective design, nonrandomized participant assignment, and small sample size. These limitations suggest that more rigorous research with larger sample sizes is needed to confirm these findings and broaden our understanding of the topic. Furthermore, this study was conducted in a single center, which may limit the generalizability of the results to other populations. In addition, the use of different antibiotics and surgical techniques among patients may have influenced the outcomes, leading to potential bias. The lack of long-term follow-up data also limits our ability to draw conclusions about the long-term outcomes of different treatment modalities. Future studies with longer follow-up periods are needed to investigate the long-term efficacy and safety of different treatment approaches for PA. Despite these limitations, this study provides valuable insights into the management of PA and may serve as a starting point for future research in this field. ## 5. Conclusions PA is a serious condition that requires careful consideration of various factors for treatment. Patients with poorly controlled diabetes or immunodeficiency are at a higher risk of developing PA. Treatment for PA should be based on the severity of the abscess, associated comorbidities, and response to antibiotics. Interventional treatments, such as TPD or TURP, may be necessary for larger abscesses or those that do not respond to antibiotics. Early recognition and appropriate management are crucial for preventing complications and improving outcomes. Additionally, imaging plays a vital role in the diagnosis and management of PA, and various imaging modalities such as ultrasound, CT, and MRI can assist in determining the size, location, and number of abscesses in the prostate gland. The development of antibiotic-resistant strains of bacteria highlights the importance of prompt and accurate diagnosis and the initiation of appropriate treatment. While the findings of this study suggest that conservative treatment with antibiotics can be effective for small and single abscesses in stable patients, further research is needed to determine the optimal treatment approach for patients with urinary retention. Despite the limitations of this study, the results provide valuable insights into the management of PA and can inform medical professionals in developing personalized treatment plans for patients with this condition. 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--- title: Comparative Analysis of Traditional Oriental Herbal Fruits as Potential Sources of Polyphenols and Minerals for Nutritional Supplements authors: - José Javier Quesada-Granados - José Ángel Rufián-Henares - Suryakant Chakradhari - Pravin Kumar Sahu - Yaman Kumar Sahu - Khageshwar Singh Patel journal: Molecules year: 2023 pmcid: PMC10058731 doi: 10.3390/molecules28062682 license: CC BY 4.0 --- # Comparative Analysis of Traditional Oriental Herbal Fruits as Potential Sources of Polyphenols and Minerals for Nutritional Supplements ## Abstract There are a plethora of plant species in India, which have been widely used in vegetable dishes, soups, desserts and herbal medicine. In addition to these traditional uses, today there is the extra possibility of also being able to use these plants in the nutritional supplements industry due to their favorable antioxidant and mineral composition. In this sense, thirteen vegetable species—Chanania lanzan, Ziziphus mauritiana, Nilumbo nucifera, Terminalia catappa, Terminalia arjuna, Terminalia bellirica, Terminalia chebula, Lagenaria siceraria, Luffa aegyptiaca, Praecitrullus fistulosus, Benincasa hispida, Citrullus lanatus var. lanatus and Cucurbita maxima—have been analyzed. In this paper we discuss the distribution of polyphenols and minerals (Na, K, Mg, Ca, Al, P, S, Cr, Mn, Fe, Cu, Zn, Mo, As and Pb) in different seed parts (the rhizome, pericarp, carpel, seed coat and kernel) of the above species and their possible use in the nutritional supplements industry. The concentrations of total polyphenols, flavonoids and minerals ranged from 407 to 3144 mg rutin hydrate/100 g, 24 to 3070 mg quercetin/100 g and 1433 to 7928 mg/100 g, respectively. K, Ca, P and S were abundant in these herbal fruits. In two species of herbal fruits, Terminalia arjuna and Terminalia chebula, only part of the seed structure was suitable for use in nutritional supplements. ## 1. Introduction Seeds contain vital nutrients and ultra-trace elements, which reduce the risk of cardiovascular disease and diabetes [1] and promote different healthy functions in human beings [2,3]. Many plants also contain polyphenols and flavonoids with strong antioxidant and disease-preventing properties, and could be valuable sources of these compounds in the preparation of nutritional supplements [4,5,6,7]. Ziziphus mauritiana (as Ziziphus jujuba (L.) Gaertn., and Ziziphus jujuba (L.) Lam.) is widely cultivated, especially in southeastern Asia, as a commercial crop [8]. The fruit is eaten raw or preserved and its seeds contain a number of medically active compounds, including saponins, triterpenes, flavonoids and alkaloids. It is hypnotic, narcotic, sedative, stomachic and tonic, and is used internally in the treatment of palpitations, insomnia, nervous exhaustion, night sweats and excessive perspiration [9]. Buchanania lanzan is a medium-sized deciduous tree with edible fruits and seed kernels. Its seed kernel and extracted kernel oil are used in the preparation of several Indian dishes and are a potential source of phytochemicals, tocopherols and essential fatty acids including oleic, linoleic and linolenic acid [10]. Nilumbo nucifera (Lotus) is an aquatic plant grown in tropical climates. Its rhizome and seeds are edible and have various therapeutic benefits including allelopathic, antiobesity, anti-HIV, antioxidant, diuretic, astringent, anti-inflammatory, hepatoprotective, antipyretic, antibacterial and immunomodulatory effects [11]. The Terminalia family (Terminalia arjuna, Terminalia bellerica and Terminalia chebula) includes several medicinal plants which have astringent and purgative properties and are used to treat cough, diarrhea, dropsy and leprosy, among other diseases [12]. Cucurbitaceae, of considerable economic importance, is a major source of food and medicine [13,14]. Studies have detected valuable polyphenols and minerals in some of these fruits [15,16,17,18,19,20,21,22], but no information is available as to their quantity and distribution within the pericarp, seed and seed coat. Our study, therefore, was conducted to determine the quantity and distribution of total polyphenols, total flavonoids and minerals in the following widely-consumed seeds: Buchanania lanzan, Ziziphus mauritiana, Nilumbo nucifera, Terminalia catappa, Terminalia arjuna, Terminalia bellirica, Terminalia chebula, Lagenaria siceraria, Luffa aegyptiaca, Praecitrullus fistulosus, Benincasa hispida, Citrullus lanatus var. lanatus and Cucurbita maxima. Specifically, we determine the relative proportions of polyphenols and minerals in the pericarp, seed, seed coat and carpel of these representative species: Buchanania lanzan, Ziziphus mauritiana, Nilumbo nucifera, Terminalia catappa, Terminalia arjuna, Terminalia bellirica, Terminalia chebula and Lagenaria siceraria. Finally, we discuss the possibility of using these seeds as sources of polyphenols and minerals for nutritional supplements. ## 2. Results and Discussion The mean values of each set of three analyses were calculated. The RSD for each group of data and species ranged from $0.68\%$ to $24.0\%$ and were considered homogeneous. ## 2.1. Physical Characteristics Table 1 summarizes the physical characteristics of the seeds analyzed. The seed mass of the species Buchanania lanzan, Cucurbitaceae, Nilumbo nucifera, Terminalia (Combretaceae) and Ziziphus mauritiana ranged from 38 to 5770 mg per seed ($p \leq 0.05$). That of Terminalia was by far the highest. These seed masses were ordered as follows: Terminalia (4738 mg) > Nilumbo nucifera (1197 mg) > Ziziphus mauritiana (978 mg) > Buchanania lanzan (310 mg) > Cucurbitaceae seeds (126 mg). The seeds were of diverse colors and shapes (Figure 1). The Buchanania lanzan, Terminalia and Ziziphus mauritiana seeds were composed of the pericarp, the hard seed coat and the kernel. The seeds of the other species were covered with a soft seed coat. The Cucurbitaceae seeds were covered with a large edible carpel. The major fractions of the seeds were composed of the pericarp and the hard seed coat. The kernel masses accounted for $5.4\%$ to $43\%$ of the total ($p \leq 0.05$), in the following order: Cucurbitaceae seeds ($43\%$) > Buchanania lanzan ($24\%$) > Terminalia seeds ($6.4\%$) > Ziziphus mauritiana ($6.1\%$) > Nilumbo nucifera ($5.4\%$). The moisture content of the cultivars ranged from $1.2\%$ for the Ziziphus mauritiana kernel to $13.5\%$ for the Lagenaria siceraria carpel, with a mean value of $6.0\%$ ($p \leq 0.05$). ## 2.2. Total Polyphenol (TPh) and Mineral Contents Polyphenols are secondary metabolites that are synthesized by plants to protect against UV light, pathogens and herbivores [23]. Among several hundred polyphenols that have been detected in edible plants are flavonoids (Fla), one of the strongest and most abundant sources of antioxidants. The concentration of total polyphenols (TPh) in the twelve seed kernels (KE) and six pericarps with seed coat (PC + SC) included in our analysis ranged from 407 to 2554 mg rutin hydrate/100 g ($p \leq 0.05$) and 1094 to 3144 mg rutin hydrate/100 g ($p \leq 0.05$), respectively (Table 2). As expected, the highest average content was found in the PC + SC samples (2242 mg rutin hydrate/100 g). Although the seed coat (SC) of Lagenaria siceraria also presented interesting values (1460 mg rutin hydrate/100 g), the fact that only two samples were available for analysis limited the value of the conclusions drawn. However, this was not the case of the KE samples, which also presented an interesting average total polyphenol content (1257 mg rutin hydrate/100 g). Nevertheless, no significant statistical differences ($p \leq 0.05$) were observed in the TPh contents of the different fruits according to the part of the plant analyzed (PC + SC, KE, SC, CA, SE, Rh). The concentration of Fla in the KE and PC + SC samples ranged from 228 to 1970 mg quercetin/100 g ($p \leq 0.05$) and 525 to 3070 mg quercetin/100 g ($p \leq 0.05$), respectively (Table 2). The Fla presented a distribution similar to that found for total polyphenols, i.e., a higher content in the PC + SC samples (average 1526 mg quercetin/100 g), a high content in Lagenaria siceraria (SC) with 915 mg quercetin/100 g and high values of Fla in the KE samples (738 mg quercetin/100 g). This similarity in the distributions of the TPh and Fla contents seems to indicate a relationship between them, which would mean that Fla are the predominant polyphenolic species. This hypothesis was confirmed by a Pearson’s correlation study (Figure 2). The R-squared statistic indicates that the adjusted model explains $57.9966\%$ of the variability in TPh. As expected, and so appears in many other studies, the correlation coefficient is equal to 0.761555, indicating a strong relationship between the variables. The maximum TPh and Fla values were observed for the Terminalia chebula and Terminalia arjuna samples, with 2819 and 2543 mg rutin hydrate/100 g, respectively for TPh, and 2456 and 1950 mg quercetin/100 g, respectively for Fla. However, the ANOVA test did not reveal significant statistical differences between the different fruit species ($p \leq 0.05$). The highest TPh and Fla contents were recorded for the Combretaceae and Anacardiaceae and for the Combretaceae and Rhamnaceae families, respectively ($p \leq 0.05$). Comparable TPh contents in the Rhamnaceae, Cucurbitaceae and Combretaceae species have been detected in previous research [15,16,17,18,19]. Table 3 shows the concentrations of the minerals analyzed in the samples, which ranged from 1432.59 to 7927.99 mg/100 g ($p \leq 0.05$), with a mean value of 3730.24 mg/100 g. The highest values were observed for Buchanania lanzan (PC + SC), Terminalia arjuna (KE) and Terminalia catappa (KE). Comparable mineral contents were observed in the Terminalia species, analyzed by X-ray fluorescence [19]. However, markedly different mineral contents were observed in the African Cucurbitaceae species, possibly due to climatic variations [20,21,22]. The polyphenol and mineral contents of the samples were determined separately, in the pericarp (PC + SC) and in the seed kernel (KE), for Buchanania lanzan, Ziziphus mauritiana, Nilumbo nucifera, Terminalia catappa, Terminalia arjuna, Terminalia bellirica, Terminalia chebula and Lagenaria siceraria. Remarkably high levels of TPh were detected in the pericarp of four Terminalia species, ranging from 2055 to 3144 mg rutin hydrate/100 g. In contrast, the mineral contents were high in the seed kernels (4145 to 7928 mg/100 g) in all samples except Terminalia bellirica, in which the contents were similar in both phases. Higher TPh contents were also observed in the seed kernel phase of the following species: Buchanania lanzan, Ziziphus mauritiana, Nilumbo nucifera and Lagenaria siceraria. The mineral contents were much higher (4038 to 5271 mg/100 g) in the pericarp of Buchanania lanzan and Nilumbo nucifera. Finally, in Terminalia bellirica and Lagenaria siceraria the mineral content was similar in both phases. ## 2.3. Detailed Description of the Minerals Potassium, an element promoting muscle strength, metabolism, water balance, electrolytic functions and the nervous system [24] was found in all of the species considered and in all parts of their fruits, ranging from 701.81 to 3427.72 mg/100 g, with a mean value of 1690.32 mg/100 g. The highest value was found for Terminalia arjuna, but there were no significant statistical differences between species or between different parts of the fruit ($p \leq 0.05$). On the other hand, the K content was significantly correlated with Ca in the kernel samples (KE) ($r = 0.90$). Magnesium and calcium each play a major role in strengthening and maintaining the bones, muscles and nerves, and also contribute to protein synthesis and cellular metabolism [25]. In our samples, Mg was present in all species and in all parts of the fruits [26], ranging from 52.89 to 1455.81 mg/100 g, with a mean value of 496.50 mg/100 g. The highest value was found in Praecitrullus fistulosus (853 mg/100 g). In general, levels of Mg were higher in the kernel (KE) (mean value 769 mg/100 g) than elsewhere (mean value 169 mg/100 g). The large difference between KE and all other areas of the plant (PC + SC, CA, SC, SE, Rh) explains the significant statistical differences found according to the part of the plant ($p \leq 0.05$). The content of Mg was strongly correlated with that of P ($r = 0.71$–0.80). The Ca contents in the pericarp (PC + SC), carpel (CA), rhizome (Rh) and kernel (KE) ranged from 32.34 to 3662.57 mg/100 g, with a mean value of 515.05 mg/100 g. Although the highest values were found in fruits with pericarp (PC + SC), 952.12 mg/100 g, there were no statistically significant differences between these concentrations and those in other types of fruits ($p \leq 0.05$). The highest values for Mg and Ca were recorded for the Buchanania lanzan pericarp and the Terminalia arjuna kernel, respectively. The Ca/K ratio ranged from 0.03 to 5.22, with a mean value of 0.61. This ratio was especially high in the Buchanania lanzan pericarp. The Mg/Ca mass ratio ranged from 0.16 to 0.91 and 0.45 to 26.01, with mean values of 0.47 and 10.04 in the pericarp/carpel/seed cat/rhizome and seed kernel samples, respectively. These values are within the margins established as optimal for this relationship [27]. The phosphorus content in the pericarp/carpel/rhizome and kernel (PC + SC, CA, Rh, KE) ranged from 25.95 to 1617.28 mg/100 g, with a mean value of 680.67 mg/100 g. In this case, the differences between the fruits were statistically significant ($p \leq 0.05$). These data are similar to those found for other plant species [28] The concentration of sulphur in the samples ranged from 32.28 to 367.84 mg/100 g in the pericarp/carpel/rhizome and in the kernel, respectively ($p \leq 0.05$), with an average value of 209.64 mg/100 g. The highest P and S contents in the pericarp were recorded in the Terminalia chebula carpel. In the kernel, the highest P and S values were obtained for Terminalia arjuna and Citrullus lanatus var. lanatus. P and S were strongly correlated ($r = 0.85$–0.99) in all the samples. The S/P mass ratio ranged from 0.21 to 1.35, with a mean value of 0.54. The highest S/P mass ratios were observed in the Terminalia pericarp (PC + SC), ranging from 0.98 to 1.35. In the analyzed samples, the content of sodium, which plays a key role in osmoregulation and fluid maintenance in the human body, ranged from 2.31 to 1549.87 mg/100 g, with a mean value of 83.76 mg/100 g for the pericarp/carpel/rhizome and kernel (PC + SC, CA, Rh, KE), with no significant statistical differences between these areas ($p \leq 0.05$). A very high value (1549.87 mg/100 g) was detected for the Terminalia catappa kernel. There was a strong correlation ($r = 0.78$–1.0) between Na and Al, Pb and Zn in the fruits with kernel. Iron, which is essential to metabolize proteins and in the production of hemoglobin and red blood cells [25], was present in low concentrations in the pericarp/carpel/rhizome and seed kernels (PC + SC, CA, Rh, KE), ranging from 4.77 to 64.64 mg/100 g ($p \leq 0.05$) with a mean value of 13.16 mg/100 g. However, there was a high Fe content in the Nilumbo nucifera rhizome (64.64 mg/100 g), followed by the Terminalia arjuna (35.84 mg/100 g) and the Buchanania lanzan (22.57 mg/100 g) pericarp. The Fe content correlated strongly ($r = 0.81$–0.98) with that of Al and Mn. The content of manganese, another essential element, which promotes the growth of bone structures [24], ranged from 0.49 to 8.69 mg/100 g ($p \leq 0.05$), with a mean value of 3.40 mg/100 g. The highest values were recorded in the Nilumbo nucifera rhizome and seed. The Mn/Fe mass ratio ranged from 0.05 to 0.75, with a mean value of 0.33. Copper, vital for a range of body functions including the production of red blood cells and energy and the maintenance of nerve cells and the immune system [25] was detected in 17 of the samples, at concentrations ranging from 0.27 to 181.64 mg/100 g ($p \leq 0.05$), with a mean value of 13.48 mg/100 g. The highest contents were detected in the Terminalia arjuna pericarp (181.64 mg/100 g) and in the Terminalia catappa pericarp (18.96 mg/100 g). The Cu concentration observed in the Terminalia arjuna pericarp was similar to that reported elsewhere [19]. Zinc, essential to maintain the immune and digestive systems [24] was present in most of the seed kernel samples (KE). The lowest levels were recorded in Luffa aegyptiaca (0.57 mg/100 g) and the highest in Terminalia catappa (10.76 mg/100 g). These high levels of Zn are appropriate due to the usual deficiency of this mineral in India [29]. Statistically significant differences ($p \leq 0.05$) were observed among the Zn concentrations in the kernel samples. There were strong correlations (0.75–0.89) between Zn and Al, Cr, Na and Pb. Chromium is another essential trace mineral, which heightens insulin sensitivity and promotes the metabolism of proteins, carbohydrates and lipids [24]. Our analysis detected Cr in fourteen samples, corresponding to Buchanania lanzan, Cucurbita maxima, Ziziphus mauritiana, Nilumbo nucifera, Lagenaria siceraria, Luffa aegyptiaca and Terminalia seeds, at concentrations ranging from 0.02 to 1.41 mg/100 g, with no significant statistical differences ($p \leq 0.05$). The content was appreciable in the Buchanania lanzan pericarp (PC + SC), at 1.41 mg/100 g. In fifteen samples, nickel was detected at trace levels, ranging from 0.01 to 0.95 mg/100 g ($p \leq 0.05$). The highest value was recorded for the Citrullus lanatus (KE), followed by Terminalia arjuna (KE) and Terminalia catappa (KE) (0.86 and 0.82 mg/100 g, respectively). Molybdenum participates in enzymatic systems and is related to the metabolism of uric acid, alcohol, drugs, sulphites and toxins, among others [24]. A small amount (0.05 mg/100 g) was detected in one sample, Terminalia bellirica (PC + SC). Aluminum is a non-essential element. Nevertheless, it was detected in all samples, at concentrations ranging from 0.45 to 388.17 mg/100 g ($p \leq 0.05$). Particularly high contents were observed in the Terminalia catappa kernel sample (388.17 mg/100 g), the Nilumbo nucifera rhizome (57.81 mg/100 g) and the Terminalia arjuna pericarp (30.42 mg/100 g). Although these concentrations seem high, Al is unlikely to be a human carcinogen at normal dietary doses [30]. The content of Al was strongly correlated ($r = 0.70$–1.0) with Na, Pb and Zn (KE), and with Fe and Mn (Rh/PC + SC). Lead, a toxic element, was found in nine samples belonging to the Combretaceae, Cucurbitaceae, Nelumbonaceae and Rhamnaceae families, with a content ranging from 0.22 to 2.94 mg/100 g ($p \leq 0.05$). In Cucurbitaceae and Combretaceae, this range was 0.29 to 2.94 mg/100 g. In five samples, Terminalia catappa (average concentration 2.72 mg/100 g), Terminalia arjuna (1.76 mg/100 g), Terminalia bellirica (1.30 mg/100 g) and Ziziphus mauritiana (0.53 mg/100 g), the content exceeded the permissible limit of 0.5 mg/100 g [31]. Another toxic element, arsenic, was detected in three Cucurbitaceae species: Lagenaria siceraria (CA), Benincasa hispida (KE), Luffa aegyptiaca (KE), with a content ranging from 1.27 to 4.75 mg/100 g ($p \leq 0.05$). These two minerals are highly undesirable in human nutrition and so the following species should be excluded from consideration: Ziziphus mauritiana (KE), Nilumbo nucifera (Rh), Terminalia catappa (PC + SC, KE), Terminalia arjuna (KE), Terminalia bellirica (PC + SC), Lagenaria siceraria (CA, KE), Luffa aegyptiaca (KE), Benincasa hispida (KE) and Citrullus lanatus var. lanatus (KE). Table 4 lists the species in which lead and/or arsenic were detected. ## 2.4. Viability of Herbal Fruits as a Source of Polyphenols and Minerals for Nutritional Supplements Having discarded the samples containing lead and/or arsenic, we then analyzed the remainder to determine which would be most suitable as a source of polyphenols and minerals. The TPh value was taken as a reference for this purpose, since the Fla content was closely related to that of total polyphenols. The content of total minerals was also considered, as most of these minerals were present in the viable samples (Figure 3 and Figure S1a,b). This analysis showed that two samples in particular, Terminalia arjuna (PC + SC) and Terminalia chebula (KE) were highly suitable as sources of TPh and minerals in the preparation of nutritional supplements. ## 3.1. Sampling of Herbal Fruits The above-mentioned herbal fruits were collected from Raipur (India) during May-June 2017 (summer), in accordance with ISO recommendations [32]. The fruits were sun dried for one week indoors, under glass and on a glass plate. The Lagenaria siceraria pericarp and seeds were separated manually before drying. The seeds were also oven-dried overnight at 50 °C. ## 3.2. Sample Preparation In every case, the pericarp, seed, seed coat and kernel were separated from the fruit. They were then crushed to a powder, sieved to obtain particles of ≤0.1 mm and stored in glass containers. The mass of each cultivar was measured using a Mettler electronic balance. Composite samples were prepared by mixing three samples in identical mass ratios. The moisture content of the sample was determined by heating at 105 °C for 6 h. ## 3.3. Analysis of Polyphenols For each analysis, 100 mg of sample was extracted with 5 mL of an acetone:water (70:30, v/v) solution maintained in an ultra-sonic bath for 20 min at 20 °C. Then, 5 mL of fresh acetone: water (70:30, v/v) solution was added to the mixture and the extraction was repeated for 20 min at 20 °C. After centrifugation, the supernatant was collected [33]. The total phenolic content (TPh) of each extract was determined as rutin hydrate, using the Folin-Ciocalteu reagent and according to the method of Singleton, Orthofer, and Lamuela-Raventós [34,35]. The flavonoid (Fla) content was determined by the aluminum chloride method as quercetin [36]. Each analysis was conducted in triplicate. ## 3.4. Analysis of Minerals A precisely-weighed amount (0.10 g) of sample was mixed with 5.0 mL of the acid solution in a Teflon tube for microwave digestion. The solution was diluted to 100 mL with deionized water for the ICP-OES and ICP-MS analysis of the mineral, using appropriate standard reference materials [37]. ## 3.5. Statistics The Statgraphics® Centurion XVI (v16. StatPoint Technologies, Inc., Warrenton, VA, USA) statistical package was used to interpret the data obtained. The coefficients of variation (CV) or relative standard deviations (RSD) for each group of data and species were calculated, to determine their distributive characteristics and to enable appropriate statistical tests (parametric or non-parametric)—ANOVA, Bartlett, Kruskal-Wallis, Student’s t-test or Pearson’s correlation—to be applied. Statistical significance was assumed at p ≤ 0.05. ## 4. Conclusions The species Terminalia arjuna, Buchanania lanzan and Nilumbo nucifera pericarp/rhizome contain high levels of minerals and polyphenols. The ripe fruit of Buchanania lanzan is a good source of polyphenols and Mg, Ca and Cr. Nilumbo nucifera rhizome is a good source of the polyphenols and of P, K. Fe and Mn. Terminalia arjuna contained useful levels of polyphenols and of P, K, S, Mg and Cu. Terminalia catappa was a significant source of polyphenols and of Al, Na and Zn. 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--- title: 'Alcohol Consumption and a Decline in Glomerular Filtration Rate: The Japan Specific Health Checkups Study' authors: - Yoshiki Kimura - Ryohei Yamamoto - Maki Shinzawa - Katsunori Aoki - Ryohei Tomi - Shingo Ozaki - Ryuichi Yoshimura - Akihiro Shimomura - Hirotsugu Iwatani - Yoshitaka Isaka - Kunitoshi Iseki - Kazuhiko Tsuruya - Shouichi Fujimoto - Ichiei Narita - Tsuneo Konta - Masahide Kondo - Masato Kasahara - Yugo Shibagaki - Koichi Asahi - Tsuyoshi Watanabe - Kunihiro Yamagata - Toshiki Moriyama journal: Nutrients year: 2023 pmcid: PMC10058733 doi: 10.3390/nu15061540 license: CC BY 4.0 --- # Alcohol Consumption and a Decline in Glomerular Filtration Rate: The Japan Specific Health Checkups Study ## Abstract Previous studies have reported conflicting results on the clinical impact of alcohol consumption on the glomerular filtration rate (GFR). This retrospective cohort study aimed to assess the dose-dependent association between alcohol consumption and the slope of the estimated GFR (eGFR) in 304,929 participants aged 40–74 years who underwent annual health checkups in Japan between April 2008 and March 2011. The association between the baseline alcohol consumption and eGFR slope during the median observational period of 1.9 years was assessed using linear mixed-effects models with the random intercept and random slope of time adjusting for clinically relevant factors. In men, rare drinkers and daily drinkers with alcohol consumptions of ≥60 g/day had a significantly larger decline in eGFR than occasional drinkers (difference in multivariable-adjusted eGFR slope with $95\%$ confidence interval (mL/min/1.73 m2/year) of rare, occasional, and daily drinkers with ≤19, 20–39, 40–59, and ≥60 g/day: −0.33 [−0.57, −0.09], 0.00 [reference], −0.06 [−0.39, 0.26], −0.16 [−0.43, 0.12], −0.08 [−0.47, 0.30], and −0.79 [−1.40, −0.17], respectively). In women, only rare drinkers were associated with lower eGFR slopes than occasional drinkers. In conclusion, alcohol consumption was associated with the eGFR slope in an inverse U-shaped fashion in men but not in women. ## 1. Introduction Alcohol consumption is a major modifiable risk factor for the global health burden [1]. Systematic reviews reported a J-shaped association between alcohol consumption and all-cause mortality [2,3,4,5]. Alcohol consumption causes various health problems [6]: a J-shaped association has been reported with stroke [7,8], especially ischemic stroke [9,10]; a U-shaped association with type 2 diabetes [11,12,13,14]; a positive dose-dependent association with atrial fibrillation [15,16], heart failure [7], hemorrhagic stroke [9,10], breast cancer [17,18], and colorectal cancer [18,19]; and a negative dose-dependent association with ischemic heart disease [7,8,20]. The clinical impact of alcohol consumption on kidney function in the general population is controversial. Alcohol consumption has been associated with the incidence of end-stage kidney disease (ESKD) in a positive [21] or negative [22] dose-dependent manner. Another cohort study reported no significant association between alcohol consumption and the incidence of ESKD [23]. The incidence of chronic kidney disease (CKD), which is defined as a glomerular filtration rate (GFR) of <60 mL/min/1.73 m2, was associated with alcohol consumption in a negative dose-dependent [24,25,26,27] and U-shaped manner [28,29]. One of the main reasons for the different associations in previous studies might be the varied range of the highest alcohol consumption: >10–30 [24,25,26,27], ≥46 [30], ≥48 [31], and >69 g/day [28]. In order to assess the dose-dependent association between alcohol consumption and the GFR accurately, the trajectory of the GFR should be analyzed in heavy drinkers with an alcohol consumption rate of ≥60 g/day. Because previous studies have reported that women are more vulnerable to the deleterious effect of high alcohol consumption than men [30,31], the dose-dependent association between alcohol consumption and the GFR should be assessed in men and women separately. This retrospective cohort study aimed to investigate the dose-dependent association between alcohol consumption and the GFR trajectory in a large cohort of the general population, including 304,929 participants (125,698 men and 179,231 women) who underwent annual health checkups in Japan. The findings of the present study suggest a potential threshold to prevent the deleterious effects of alcohol consumption when considering the GFR. ## 2.1. Participants This study included 1,071,566 participants who were eligible for the study, aged 40–74 years and underwent their annual health checkups in 26 prefectures in Japan between April 2008 and March 2011. The details of the design of this retrospective cohort study are described elsewhere [32,33]. The initial visit between April 2008 and March 2011 was set as the baseline date. After excluding (i) 176,364 ($16.5\%$) participants with a missing baseline estimated GFR (eGFR), (ii) 110,647 ($10.3\%$) participants with a missing baseline alcohol consumption, (iii) 242,966 ($22.7\%$) participants with missing data on other baseline variables, and (iv) 236,660 ($22.1\%$) participants who had no eGFR measurement during the observational period between their baseline visit and the end of the study in March 2012, we finally included 304,929 ($28.5\%$) participants from 18 prefectures (Hokkaido, Ibaraki, Tochigi, Saitama, Chiba, Niigata, Ishikawa, Fukui, Nagano, Gifu, Osaka, Tokushima, Fukuoka, Saga, Nagasaki, Kumamoto, Miyazaki, and Okinawa) (Figure 1). The study protocol was approved by the Ethics Committees of Fukushima Medical University (No. 2771) and Osaka University Hospital (No. 24086-9). ## 2.2. Measurements Baseline demographics, physical examinations, and laboratory data at their first visit included age, sex, body mass index (BMI = weight (kg)/height2 (m2)), mean arterial pressure (diastolic blood pressure + [systolic blood pressure—diastolic blood pressure]/3), hemoglobin A1c, uric acid, high-density lipoprotein (HDL) cholesterol, serum creatinine, eGFR, and dipstick urinary protein. To calculate eGFR, a Japanese equation [34] was used:194 × age (year)−0.287 × serum creatinine (mg/dL)−1.094 (× 0.739 if female) The participants’ baseline drinking and smoking status; current treatments for hypertension, dyslipidemia, and diabetes; and history of cardiovascular disease (CVD) were obtained from standard questionnaires at the baseline visit. The main exposure of interest in this study was alcohol consumption, which was ascertained by asking the following questions: “How often do you drink alcoholic beverages: (i) every day, (ii) occasionally, or (iii) rarely?” and “How many alcoholic beverages do you drink: (i) <1 drink per day, (ii) 1–2 drinks per day, (iii) 2–3 drinks per day, or (iv) ≥3 drinks per day?”, respectively. One standard drink was defined as 500 mL beer, 180 mL Japanese sake (a traditional Japanese alcoholic beverage), 80 mL shochu (a Japanese liquor), 60 mL whiskey, or 240 mL wine. The ethanol content per one standard drink was calculated to be equivalent to 20 g [35]. Based on these two questions, we classified alcohol consumption into six categories: rare drinkers, occasional drinkers, and daily drinkers with an ethanol intake of ≤19, 20–39, 40–59, and ≥60 g/day. Participants who answered “Yes” to the “Do you smoke?” question were classified as current smokers. Diagnoses of hypertension, dyslipidemia, and diabetes were made if the participants answered “Yes” to the question, “Are you being treated for hypertension, dyslipidemia, or diabetes?” CVD history was determined according to positive answers to the question, “Have you ever been diagnosed with heart disease and/or stroke?”. ## 2.3. Outcomes The main outcome of this study was the difference in eGFR slope over time (mL/min/1.73 m2/year) between the exposure and reference groups, based on all eGFR measurements at the annual health checkups during the study period between April 2008 and March 2012. The difference in eGFR slope was estimated using linear mixed-effects models, described in Section 2.4 Statistics in detail. We also examined the risk for incidence of a ≥$30\%$ decline in the eGFR during the observational period. Participants were followed up until March 2012 and censored on the last day of the eGFR measurement at the annual health checkup before the end of March 2012. ## 2.4. Statistics The baseline clinical characteristics between the included and excluded participants were compared using the χ2 test, t-test, and Wilcoxon rank sum test, as appropriate. The differences in baseline variables among the alcohol consumption categories were compared using the χ2 test, one-way ANOVA, or Kruskal–Wallis test, as appropriate. The association between alcohol consumption and the eGFR trajectory was assessed using linear mixed-effects models, including all available eGFR values [36,37]. A random intercept was used to account for the variation in baseline eGFR values among participants, and a random slope for time was used to account for the variation in the participants’ eGFR trajectory. The jth eGFR of the ith participants was estimated using the following equation:eGFRij = ß0 + ß1Exposrei + ß2Timeij + ß3Timeij × Expoxurei + u0i + u2iTimeij + εij where ß1 represents the estimated difference between the exposure and reference groups, ß2 represents the estimated rate of eGFR decline in the reference group, and ß3 represents the difference in the eGFR slope between the exposure group and reference groups. The terms u0i and u2i represent a random intercept and random slope for time. The estimated differences in eGFR slopes (ß3) and their $95\%$ confidence intervals ($95\%$ CIs) for each exposure group were reported. To control the potential confounding effects of clinically relevant factors, we used nested linear mixed-effects models, whereby the baseline covariates from each prior model were retained as follows. Model 1 was unadjusted. Model 2 included age (year) as a covariate. Model 3 added urinary protein dipstick values (−, ±, 1+, 2+, and ≥3+). Model 4 added body mass index (kg/m2), mean arterial pressure (mmHg), hemoglobin A1c (%), HDL cholesterol (mg/dL), uric acid (mg/dL), and current smoking status. Model 5 added CVD history and current treatments for hypertension, dyslipidemia, and diabetes. For sensitivity analyses, first, an association between alcohol consumption and the eGFR slope was assessed in 168,347 participants with ≥3 measurements of the eGFR during the observational period; this was after excluding 136,582 participants with 2 measurements of eGFR during the observational period. Second, after excluding 121,431 participants with a CVD history and/or current treatment for hypertension, dyslipidemia, and/or diabetes, we assessed the association between alcohol consumption and the eGFR slope in 183,498 participants without a CVD history or current treatment for hypertension, dyslipidemia, or diabetes, to alleviate the potential impact of sick quitters. Sick quitters who had such comorbidities and, therefore, quit drinking or reduced alcohol consumption [38] might be at a high risk of eGFR decline. The inclusion of sick quitters might lead to a biased estimate of the association between alcohol consumption and the eGFR slope. Third, to clarify the effect of alcohol consumption categorization on the dose-dependent association between alcohol consumption and the eGFR slope, we categorized alcohol consumption into five groups: rare drinkers, occasional drinkers, and daily drinkers with an ethanol intake of ≤19, 20–39, and ≥40 g/day, and calculated the estimated difference in eGFR slopes for each group. Fourth, an association between alcohol consumption and the incidence of a ≥$30\%$ decline in the eGFR was assessed by using nested Cox proportional hazards models that were adjusted for clinically relevant factors. Fifth, a propensity score-matched approach was used to compare the eGFR slope and incidence of a ≥$30\%$ decline in the eGFRs of rare drinkers and daily drinkers with ≥60 g/day of alcohol consumption with occasional drinkers. Propensity scores, estimated probabilities of being rare drinkers and daily drinkers with ≥60 g/day of alcohol consumption (vs. occasional drinkers), were calculated in separate multivariable-adjusted logistic regression models, including age (year); urinary dipstick protein (−, ±, 1+, 2+, and ≥3+); eGFR (mL/min/1.73 m2); body mass index (kg/m2); mean arterial pressure (mmHg); hemoglobin A1c (%); HDL cholesterol (mg/dL); uric acid (mg/dL); current smoking; current treatments for hypertension, dyslipidemia, and diabetes; and CVD history as independent variables. After calculating the propensity scores for each patient, each rare drinker and daily drinker with ≥60 g/day of alcohol consumption was matched to occasional drinkers, with the closest propensity score at a ratio of 1:1 and 4:1, respectively, without replacement, using a nearest neighbor matching algorithm with a caliper width of 0.1 standard deviations of the logit of the propensity score [39]. Continuous variables were expressed as the mean ± standard deviation or median ($25\%$–$75\%$), as appropriate, and the categorical variables were expressed as numbers (proportions). The statistical significance was set at $p \leq 0.05.$ In order to perform statistical analyses, we used R software, version 4.1.1 (R Foundation for Statistical Computing, www.r-project.org, accessed on 1 February 2023). ## 3. Results The baseline clinical characteristics of 125,698 and 325,377 men, who were included in and excluded from the present study, are listed in Table S1. All baseline variables were significantly different between the included and excluded men, except for HDL cholesterol (Table S1). The excluded men were more likely to be current smokers and those with diabetes and CVD history than the included men. Table S2 shows the baseline clinical characteristics of the 179,231 included women and 440,740 excluded women. All variables were statistically different between the included and excluded women, except for BMI. Table 1 shows the baseline characteristics of 125,698 men, including 38,726 ($30.8\%$) rare drinkers, 32,774 ($26.1\%$) occasional drinkers, and 15,236 ($12.1\%$), 25,819 ($20.5\%$), 10,220 ($8.1\%$), and 2923 ($2.3\%$) daily drinkers with alcohol consumption of ≤19, 20–39, 40–59, and ≥60 g/day, respectively. Daily drinkers with higher alcohol consumption were more likely to be young, current smokers, and hypertensive and had higher levels of uric acid and eGFR, whereas rare drinkers were more prone to dyslipidemia, diabetes, and CVD. The prevalence of proteinuria was comparable among alcohol consumption categories. Contrary to men, most women were rare drinkers, and the prevalence of daily drinkers was very low among women, including 131,484 ($73.4\%$) rare drinkers, 34,874 ($19.5\%$) occasional drinkers, and 7372 ($4.1\%$), 3821 ($2.1\%$), 1152 ($0.6\%$), and 528 ($0.4\%$) daily drinkers with alcohol consumption of ≤19, 20–39, 40–59, and ≥60 g/day, respectively (Table 2). Similar trends in age, smoking status, eGFR, urinary dipstick protein, dyslipidemia, diabetes, and CVD across the alcohol consumption categories were observed among women. Among 125,698 men, the number of eGFR measurements during the median observational period of 1.9 years (interquartile range 1.1–2.4) was 2, 3, and 4 in 57,589 ($45.8\%$), 47,283 ($37.6\%$), and 20,826 ($16.6\%$) men, respectively (Table S3). An unadjusted model (Model 1) showed that rare drinkers and daily drinkers with alcohol consumption of ≥60 g/day were likely to have a significantly lower eGFR slope than daily drinkers with alcohol consumption of ≤19 g/day (difference in eGFR slope (mL/min/1.73 m2/year) of rare drinkers, occasional drinkers, and daily drinkers with alcohol consumptions of ≤19, 20–39, 40–59, and ≥60 g/day: −0.30 [$95\%$ CI −0.57, −0.03], 0.00 [reference], 0.24 [−0.12, 0.61], 0.11 [−0.20, 0.41], −0.16 [−0.59, 0.27], and −1.33 [−2.02, −0.64], respectively) (Figure 2a and Table S4). Even after adjusting for clinically relevant factors, daily drinkers with alcohol consumption of ≥60 g/day were associated with significantly lower eGFR slopes than those with alcohol consumption of ≤19 g/day. However, the association between rare drinkers and the eGFR slope was remarkably attenuated (Model 5: −0.33 [−0.57, −0.09], 0.00 [reference], −0.06 [−0.39, 0.26], −0.16 [−0.43, 0.12], −0.08 [−0.47, 0.30], and −0.79 [−1.40, −0.17], respectively) (Figure 2a and Table S4). The sensitivity analyses verified a U-shape association between alcohol consumption and the eGFR trajectories in men. First, among 68,109 participants with ≥3 measurements of the eGFR during the observational period, a similar dose-dependent association between alcohol consumption and the eGFR slope was observed (Model 5: −0.45 [−0.93, 0.02], 0.00 [reference], −0.16 [−0.80, 0.48], −0.37 [−0.91, 0.17], 0.02 [−0.74, 0.77], and −1.43 [−2.69, −0.17], respectively) (Table S4). Second, after excluding 51,422 men with a CVD history and/or current treatment for hypertension, dyslipidemia, and/or diabetes, an association between alcohol consumption and the eGFR slope was assessed among 74,276 men without a CVD history or current treatment for hypertension, dyslipidemia, or diabetes. Rare drinkers and daily drinkers with ≥60 g/day of alcohol consumption had a significantly higher risk of eGFR decline than occasional drinkers (Model 5: −0.37 [−0.67, −0.07], 0.00 [reference], −0.16 [−0.57, 0.24], −0.44 [−0.78, −0.10], −0.40 [−0.87, 0.07], and −0.98 [−1.73, −0.23], respectively) (Figure 2c and Table S4). Additionally, the association between the alcohol consumption of 20–39 and 40–59 g/day and eGFR decline was more enhanced in the 74,276 men without the mentioned comorbidities than in 125,698 men (daily drinkers with an alcohol consumption of 20–39 and 40–59 g/day in Model 4: −0.44 [−0.78, −0.10] and −0.40 [−0.87, 0.07] in 74,276 men without comorbidities; −0.16 [−0.43, 0.12] and −0.08 [−0.47, 0.30] in 125,698 men, respectively) (Figure 2a,c and Table S4), suggesting that sick quitters might blunt a deleterious effect of alcohol consumption on the eGFR slopes in 125,698 men. Third, if 10,220 and 2923 daily male drinkers with alcohol consumptions of 40–59 and ≥60 g/day were categorized into a single group, this group was no longer associated with the eGFR slope (eGFR slope [mL/min/1.73 m2/year] of rare drinkers, occasional drinkers, and daily drinkers with alcohol consumptions of ≤19, 20–39, and ≥40 g/day in Model 5: −0.33 [−0.57, −0.09], 0.00 [reference], −0.06 [−0.39, 0.26], −0.16 [−0.43, 0.12], and −0.23 [−0.57, 0.12], respectively) (Table S5). Fourth, the incidence of a ≥$30\%$ decline in the eGFR was observed in 544 ($1.4\%$), 439 ($1.3\%$), 178 ($1.2\%$), 370 ($1.4\%$), 168 ($1.6\%$), and 60 (2.1) men, respectively (Table S6). The multivariable-adjusted Cox proportional hazards model showed a similar association between alcohol consumption and the incidence of a ≥$30\%$ decline in the eGFR (1.17 [1.02, 1.34], 1.00 [reference], 0.95 [0.78, 1.14], 1.03 [0.88, 1.20], 1.11 [0.91, 1.35], and 1.21 [0.90, 1.61], respectively), although the association between alcohol consumption of ≥60 g/day and the incidence of a ≥$30\%$ decline in the eGFR was not at statistically significant levels, probably because of their small number. Fifth, after calculating the propensity scores of being rare drinkers and daily drinkers with ≥60 g/day of alcohol consumption (vs. occasional drinkers), each rare drinker and daily drinker with ≥60 g/day was matched to occasional drinkers at a ratio of 1:1 and 1:4, respectively. The clinical characteristics of 28,846 rare drinkers and 2901 daily drinkers with ≥60 g/day were clinically comparable with 28,846 and 9825 occasional drinkers, respectively (Table S7). Rare drinkers and daily drinkers with ≥60 g/day had a significantly lower eGFR slope than the occasional drinkers (rare drinkers vs. occasional drinkers, −0.43 [−0.73, −0.13]; daily drinkers with ≥60 g/day vs. occasional drinkers, −0.81 [−1.62, −0.01]) (Table S7). Rare drinkers had a significantly higher risk of a ≥$30\%$ decline in the eGFR (hazard ratio, 1.18 [1.01, 1.37]). The hazard ratio of daily drinkers with ≥60 g/day (vs. occasional drinkers) was at the same level as that of rare drinkers but was not at a statistically significant level (1.18 [0.86, 1.62]) because of their small number (Table S7). Among the 179,231 women, the number of eGFR measurements during the median observational period of 2.0 years (1.1–2.3) were 2, 3, and 4 times in 78,993 ($44.1\%$), 71,063 ($39.6\%$), and 29,175 ($16.3\%$) women, respectively (Table S3). Rare drinkers had significantly lower eGFR slopes than occasional drinkers, whereas daily drinkers did not (Model 5: −0.25 [−0.47, −0.04], 0.00 [reference], −0.17 [−0.64, 0.31], 0.47 [−0.15, 1.08], 0.20 [−0.86, 1.26], and 0.74 [−0.73, 2.20], respectively) (Figure 2b and Table S4). Rare drinkers had significantly lower eGFR slopes than the occasional drinkers among 100,238 women with ≥3 measurements of the eGFR during the observational period and 109,222 women without current treatment for hypertension, dyslipidemia, diabetes, or who had a CVD history (Table S4). The incidence of a ≥$30\%$ decline in the eGFR was observed in 2757 ($2.1\%$), 667 ($1.9\%$), 109 ($1.5\%$), 75 ($2.0\%$), 27 ($2.3\%$), and 13 ($2.5\%$) women, respectively (Table S6). The multivariable-adjusted Cox proportional hazard model showed no significant association between alcohol consumption and a ≥$30\%$ decline in the eGFR. ## 4. Discussion This retrospective cohort study clarified a U-shaped association between alcohol consumption and eGFR decline in men. However, in women, daily drinking was not significantly associated with the eGFR trajectory, while rare drinkers were significantly more vulnerable to eGFR decline than occasional drinkers in women, like men. A large sample size enabled us to perform a statistically meaningful analysis of the critical impact of heavy drinking (≥60 g/day) on eGFR decline in men. However, the low prevalence of daily drinking in women hinders the assessment of their clinical impact on the eGFR trajectory. Although multiple cohort studies have assessed the clinical impact of alcohol consumption on eGFR trajectory, most studies have defined the largest alcohol consumption as >10–30 g/day [24,25,26,27], partly because of their limited sample sizes. The results of this study strongly suggest that these previous studies might have underestimated the deleterious effects of heavy drinking (Table S5). Few studies have assessed the clinical impact of alcohol consumption of >40 g/day on eGFR trajectory. The Kansai Healthcare Study, including 9112 male workers in a single company in Japan, reported an inverse J-shaped association between alcohol consumption and the incidence of a low eGFR of <60 mL/min/1.73 m2 during a median observational period of 10.5 years (multivariable-adjusted hazard ratio [$95\%$ confidence interval] of non-drinkers and current drinkers with an alcohol consumption of ≤23.0, 23.1–46.0, 46.1–69.0, and ≥69.1 g/day: 1.00 [reference], 0.89 [0.76, 1.04], 0.65 [0.55, 0.77], 0.77 [0.61, 0.77], and 0.76 [0.43, 1.37], respectively) [28]. However, among 102 drinkers with an alcohol consumption ≥69.1 g/day, only 12 drinkers developed a low eGFR, suggesting that the incidence of having a low eGFR was too small to estimate the risk of low eGFR precisely. Another small cohort study, the Italian Longitudinal Study on Aging (ILSA), assessed a dose-dependent association between alcohol consumption (abstainers, former drinkers, and current drinkers with alcohol consumptions of ≤12, 13–24, 25–47, and ≥48 g/day) and the incidence of a low eGFR of <60 mL/min/1.73 m2 among 886 older men and 653 older women, in whom the incidence of low eGFRs was observed in 91 participants during the mean observational period of 3.5 years [31]. This study, with low statistical power, showed that only former male drinkers were significantly associated with an incidence of a low eGFR (multivariable-adjusted odds ratio [$95\%$ confidence interval] of former drinkers vs. abstainers: 0.20 [0.05, 0.87]), and current drinkers were not associated with the incidence of low eGFRs in either men or women. The remarkably large sample size of this study enabled us to statistically analyze the clinical impact of heavy drinking on eGFRs in men. However, this study lacked the power to assess the clinical impact of heavy drinking on the eGFR trajectory in women with a very low prevalence of alcohol consumption of ≥60 g/day. A larger number of female heavy drinkers was essential to clarify the association between heavy alcohol consumption and the eGFR trajectory in women. The exclusion of men with a CVD history and/or current treatment for hypertension, dyslipidemia, and/or diabetes clarified a negative linear association between alcohol consumption and the eGFR trajectory in male daily drinkers (Figure 2c). Current drinkers are likely to decrease alcohol consumption and quit drinking after the incidence of cardiometabolic diseases, including diabetes and heart diseases [38,40]. Patients with these cardiometabolic diseases are at high risk for CKD [26,41]. Herein, sick quitters who reduced alcohol consumption after the incidence of cardiometabolic diseases might be classified into lower alcohol consumption categories than those before the incidence of the cardiometabolic disease, possibly leading to an attenuation of the beneficial effect of mild alcohol consumption on eGFR (Figure 2a). The exclusion of participants with these cardiometabolic diseases might alleviate the sick-quitter effect, clarifying the dose-dependent association between alcohol consumption and the eGFR slope (Figure 2c). Aside from the sick-quitter effect, an anti-inflammatory effect of mild alcohol consumption might contribute to a significantly lower risk for eGFR decline in occasional drinkers than that of rare drinkers. Mild drinkers have lower levels of inflammatory markers than non-drinkers, including C-reactive protein [42]. These inflammatory markers are risk factors for GFR decline [43,44]. Thus, occasional drinkers with lower inflammatory levels might be less vulnerable to eGFR decline than rare drinkers in this study. This study had several limitations. First, alcohol consumption was self-reported in this study, possibly leading to a misclassification bias. Measurement of the biomarkers of alcohol consumption, including urinary ethyl glucuronide [45], is desirable to confirm the validity of this study. Second, the median observational period of 1.9 [1.1–2.3] years was short, and information on ESKD was unavailable in this study. Cohort studies with longer observational periods are necessary to estimate the clinical impact of alcohol consumption on long-term kidney function and the incidence of ESKD. Third, information regarding the type of alcoholic beverages was not available in this study. A Chinese cohort study reported that liquor consumption was associated with a significantly lower risk of ESKD incidence, whereas non-liquor consumption was not [22], suggesting that the beneficial effect of alcohol consumption might be dependent on specific types of alcoholic beverages. Fourth, unmeasured confounding factors may have affected the association between alcohol consumption and the eGFR slope. One potential confounding factor may be salt intake. A recent large cross-sectional study, including 10,762 Japanese participants, reported that higher alcohol consumption is associated with higher salt intake [46]. Because high salt intake is a risk factor for a decline in GFR [47], the association between alcohol consumption and the eGFR slope should be strengthened after an adjustment for the confounding factors associated with salt intake. ## 5. Conclusions In conclusion, this retrospective cohort study showed that the men who were rare drinkers and current drinkers with a heavy alcohol consumption of ≥60 g/day were at a higher risk of a decline in eGFR than those of men who were occasional drinkers, suggesting that alcohol consumption was associated with the eGFR trajectory in a U-shaped fashion in men. 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--- title: 'Association between Late-Eating Pattern and Higher Consumption of Ultra-Processed Food among Italian Adults: Findings from the INHES Study' authors: - Marialaura Bonaccio - Emilia Ruggiero - Augusto Di Castelnuovo - Claudia Francisca Martínez - Simona Esposito - Simona Costanzo - Chiara Cerletti - Maria Benedetta Donati - Giovanni de Gaetano - Licia Iacoviello journal: Nutrients year: 2023 pmcid: PMC10058735 doi: 10.3390/nu15061497 license: CC BY 4.0 --- # Association between Late-Eating Pattern and Higher Consumption of Ultra-Processed Food among Italian Adults: Findings from the INHES Study ## Abstract Late eating is reportedly associated with adverse metabolic health, possibly through poor diet quality. We tested the hypothesis that meal timing could also be linked to food processing, an independent predictor of health outcomes. We analysed data on 8688 Italians (aged > 19years) from the Italian Nutrition & HEalth Survey (INHES) established in 2010–2013 throughout Italy. Dietary data were collected through a single 24 h dietary recall, and the NOVA classification was used to categorize foods according to increasing levels of processing: [1] minimally processed foods (e.g., fruits); [2] culinary ingredients (e.g., butter); [3] processed foods (e.g., canned fish); [4] ultra-processed foods (UPFs; e.g., carbonated drinks, processed meat). We then calculated the proportion (%) of each NOVA group on the total weight of food eaten (g/d) by creating a weight ratio. Subjects were classified as early or late eaters based on the population’s median timing for breakfast, lunch and dinner. In multivariable-adjusted regression models, late eaters reported a lower intake of minimally processed food (β = −1.23; $95\%$ CI −1.75 to −0.71), a higher intake of UPF (β = 0.93; 0.60 to 1.25) and reduced adherence to a Mediterranean Diet (β = −0.07; −0.12 to −0.03) as compared to early eaters. Future studies are warranted to examine whether increased UPF consumption may underpin the associations of late eating with adverse metabolic health reported in prior cohorts. ## 1. Introduction Obesity and associated cardiometabolic diseases continue to rise worldwide despite extensive public health efforts to reverse this trend [1]. Unhealthy diets, i.e., diets not meeting nutritional requirements, are major risk factors for obesity and associated diseases [2,3], and therefore, common strategies to tackle obesity and diet-related diseases have been almost exclusively focused on food composition, leading to recommendations to reduce sugar, salt and fat while emphasizing high intakes of foods that are natural sources of fibre, vitamins and minerals [4]. Among the factors that possibly contribute to the rise in obesity and cardiometabolic diseases, growing attention has been paid to the timing of food intake (i.e., the time when meals are usually consumed), which has been associated with various indicators of adiposity, possibly, but not entirely, through higher energy intake [5,6,7,8,9,10,11,12]. Population studies suggest that late eating, which refers to a delay in the timing of meals (usually the main meal of the day or the last meal, i.e., dinner) [12] may be a factor implicated in obesity and other non-communicable diseases related to nutrition [13,14,15]. Potential mechanistic links through which meal timing may promote obesity and associated diseases include, among others, the lower diet quality and higher calorie intake observed in late eaters [16,17,18]. However, no prior studies to date have evaluated the possible association of meal timing with the intake of foods with different degrees of processing. Actually, it has been suggested that obesity prevalence continues to increase concomitantly with the increased consumption of ultra-processed foods (UPFs) [19]. According to the NOVA classification, UPFs are industrial formulations of ingredients, containing little or no whole food and typically including flavouring and colouring agents, emulsifiers and other cosmetic additives [20]. Consistently, population-based cohorts support a direct association of a large dietary share of UPFs with obesity [21,22] and cardiometabolic diseases [23], as well as with the incidence of major chronic diseases, regardless of the overall diet quality [24]. To fill this knowledge gap, we tested the hypothesis that the meal timing pattern is differentially associated with the intake of foods that have different food processing levels according to the NOVA classification. This study was conducted using a large dataset of adults recruited throughout Italy in 2010–2013. ## 2.1. Study Population The data are from the Italian Nutrition & HEalth Survey (INHES), which was a 3-year telephone-based survey on nutrition and health designed to collect information on dietary habits (i.e., quality, quantity, food and meal patterns), food choice determinants, and food health awareness of the Italian population according to geographical distribution, age, gender and socioeconomic status. A total of 9422 men and women aged ≥4 years throughout Italy were enrolled between November 2010 and November 2013. Details about this cohort have been previously described [25]. To capture an adequate proportion of weekdays and weekends, a survey calendar was organized at a group level accordingly in order to distribute the sample subjects across four seasons (excluding Christmas, Easter and mid-August periods). During the recruitment phase, the computer-assisted telephone interview method was used to collect dietary data (dietary habits and behaviour), the health status of the subjects, risk factors, anthropometric measurements (for example, height and weight) and health perception. Given the study objective, participants were excluded for the following reasons: subjects below 20 years of age ($$n = 571$$), missing data on diet ($$n = 2$$), extreme energy intakes reported (<800 kcal/d in men and <500 kcal/d in women or >4000 kcal/d in men and >3500 kcal/d in women; $$n = 159$$) and missing data on meal timing ($$n = 2$$). Therefore, a total of 8688 subjects were analysed. ## 2.2. Assessment of Dietary Data A self-recorded diary, using computer-based 1-day 24-h dietary recall interview (24-HDR) software, and an Italian version of the European Food Propensity Questionnaire were used to record dietary data [26,27]. Subjects were instructed to recall and record the following data for each meal consumed: (a) time and place of food intake; (b) detailed description of foods (or beverages) and (c) the quantity of intake and the food brand chosen (for manufactured foods). Further, a picture booklet was used as a reference by the subjects to report portion sizes. Lastly, participants answered whether they were currently on any diet and whether their consumption differed from their habitual diet. Individual food items and recipes reported by the participants were later matched with those available in the food list of the data management system INRAN-DIARIO 3.1 [26,28] by a nutritionist during the interviews. Finally, a total of 2000 single food items extracted from the final output database were included in the software food list. The NOVA classification [29] was used to categorize each food item into one of the following categories according to the extent and purpose of food processing: [1] fresh or minimally processed foods (e.g., fruit, meat, milk); [2] processed culinary ingredients (e.g., oils, butter, sugar); [3] processed food items (e.g., canned fish, unpackaged freshly made breads); or [4] UPFs containing predominantly industrial substances and little or no whole foods (e.g., carbonated drinks, processed meat, sweet or savoury packaged snacks). Consumption (in g/d) in each of the four NOVA groups and the percentage they represented with respect to the total amount of food eaten were determined in order to obtain a weight ratio. We used this approach instead of the energy ratio because total food amounts better account for non-nutritional factors related to food processing (e.g., neo-formed contaminants, additives and alterations to the structure of raw foods) [30]. The full list of individual foods and food groups categorized according to the NOVA classification is available in Table 1. For analyses on individual meal types, we calculated the consumption in each NOVA group separately for breakfast, lunch and dinner. Adherence to the Mediterranean Diet was evaluated by the Mediterranean Diet Score (MDS) as proposed by Trichopoulou et al. [ 31]. Briefly, we assigned 1 point to healthy foods (i.e., fruits and nuts, vegetables, legumes, fish, cereals, monounsaturated-to-saturated fat ratio) whose consumption was above the sex-specific medians of intake in the adult population of the whole INHES cohort; foods presumed to be detrimental (i.e., meat and dairy products) were given a positive score if their consumption was below the median. All other intakes received 0 points. For alcohol intake (ethanol), participants who consumed alcohol (men: 10–50 g/d; women: 5–25 g/d) scored 1 point; otherwise, the score was 0. The Mediterranean Diet Score potentially ranges from 0 to 9 (the latter reflecting maximum adherence). To evaluate overall diet quality, we also calculated the Food Standards Agency Nutrient Profiling System (FSAm-NPS) dietary index, which is used to compute the Nutri-Score front-of-pack labelling system that ranks food items according to their nutritional value [32]. The FSAm-NPS score was calculated as previously implemented in other population cohorts [24,33] as follows: for all foods and beverages consumed, based on composition for each 100 g of content, 0 to 40 points were allocated for nutrients that should be consumed in limited amounts (A points), i.e., total sugars (g), saturated fats (g), sodium (mg) and energy (kJ), and 0 to 15 points were given for nutrients or components that should be promoted, i.e., dietary fibre (g) and protein (g), and for fruit, vegetables, legumes and nuts (%) (C points). The total score of the product was calculated by subtracting the sum of C points from the sum of A points. Thus, the final FSAm-NPS score for each food/beverage was based on a scale that could theoretically range from −15 (healthiest food) to +40 (least healthy food). Based on this overall FSAm-NPS score, the Nutri-Score labelling system categorizes food products into five colours, associated with letters A (dark green) to E (dark orange), reflecting their nutritional quality [32]. The FSAm-NPS dietary index (DI) was computed at the individual level as an energy-weighted mean of the FSAm-NPS scores of all foods and beverages consumed by each participant using the following equation:FSA−NPS DI =∑$i = 1$nFSiEi∑$i = 1$nEi FSi represents the score of food/beverage ‘i’, Ei is the energy intake from food/beverage ‘i’ specific to each participant, and ‘n’ is the total number of foods/beverages consumed. An increase in the FSAm-NPS dietary index values therefore reflects a decrease in the overall diet quality value. ## 2.3. Assessment of Meal Timing The timing of main meals (i.e., breakfast, lunch and dinner) was obtained by using information provided by participants during the 24 h dietary recall, where they were asked to indicate the time of each eating occasion. For each main meal, we calculated the study population sample’s median time and assigned 1 point to those participants reporting having (a) breakfast after 7 am (study sample median time); (b) lunch after 1 p.m. (study sample median time); and (c) dinner after 8 p.m. (study sample median time). Individuals consuming meals before the median time were given 0 points. Participants scoring ≥2 points were considered to have a late meal timing pattern; otherwise, people were classified as having an early meal timing pattern. For simplification, we called them late eaters and early eaters, respectively. ## 2.4. Ascertainment of Covariates Education was based on the highest qualification attained and was categorized as up to elementary school (corresponding to ≤5 years of study), lower secondary (>5–≤8 years), upper secondary (>8–≤13 years) and postsecondary (>13 years). Present occupations were categorized into six groups: manual, non-manual, housewife, retired, student and unemployed. Marital status was defined as married/living in a couple, single, separated/divorced and widowed. The definition of urban or rural environments was based on the urbanization level described by the European Institute of Statistics (EUROSTAT definition)—obtained by the tool ‘Atlante Statistico dei Comuni’ provided by the Italian National Institute of Statistics [34]. Subjects were classified as never (one who has never smoked, or who has smoked less than 100 cigarettes in the lifetime), current (smoking one or more cigarettes per day at the time of the interview), former (one who had quit smoking at the time of interview) or occasional smokers (smoking less than 1 cigarette per day at the time of interview). History of cardiovascular disease and cancer and a previous diagnosis of diabetes, hyperlipidaemia or hypertension were self-reported and categorized as yes/no. Body mass index (BMI) was calculated by using self-reported measurements of height and weight, calculated as kg/m2 and grouped into three categories: normal (≤25 kg/m2), overweight (>25–<30 kg/m2) or obese (≥30 kg/m2). Self-reported sport activity was used as a categorical variable (yes/no). ## 2.5. Statistical Analysis The general characteristics of the analytic sample according to early and late-eating patterns are presented as numbers and percentages for categorical variables and means with standard deviations (SDs) for continuous traits. Differences in the distribution of baseline covariates were calculated using generalized linear models adjusted for age, sex and energy intake (GENMOD procedure for categorical variables and GLM procedure for continuous variables in SAS software). Beta coefficients with $95\%$ confidence intervals ($95\%$ CI) from multivariable-adjusted linear regression analyses were used to evaluate the association between the meal timing pattern (independent variable) and each category of NOVA (continuous dependent variable) or dietary index (i.e., the Mediterranean Diet Score and the FSAm-NPS dietary index; continuous dependent variables). Each dietary variable was standardized to one standard deviation to allow comparison. An a priori approach was used to select potential covariates instead of statistical criteria [35]. Two models were ultimately fitted: model 1 was adjusted for age, sex and energy intake, and multivariable model 2 was model 1 but further adjusted for education, geographical area, place of residence, sport activity, occupation, marital status, smoking, BMI, cardiovascular disease, cancer, hypertension, diabetes and hyperlipidaemia. To maximize data availability, missing data on covariates were handled using multiple imputation (SAS PROC MI, followed by PROC MIANALYZE; $$n = 10$$ imputed datasets). We conducted subgroup analyses to test the robustness of the findings by analysing the potential effect modification of the association of the meal timing pattern with each dietary score by various risk factors, such as age (19–50 years; 51–65 years and 66–97 years) and sex. We used SAS/STAT software, version 9.4 (SAS Institute Inc., Cary, NC, USA), for the analysis. ## 3. Results The analytic sample consists of 4053 men ($46.7\%$) and 4635 women ($53.3\%$) with a mean age of 56.9 years (±14.6). The average (SD) weight contributions of unprocessed/minimally processed foods, culinary ingredients, processed foods and UPFs to the diet were $73.7\%$ (±12.0), $2.6\%$ (±1.2), $15.9\%$ (±10.7) and $7.8\%$ (±7.0), respectively. More than half ($58.1\%$) of the total calories came from unprocessed/minimally processed foods and culinary ingredients, while $24.6\%$ came from processed food, and $17.3\%$ were from UPFs. The characteristics of the study participants according to the meal timing pattern are presented in Table 2. As compared to early eaters, late eaters were younger, were more likely to live in Southern Italy and urban environments, had a higher educational level and were prevalently non-manual workers. Additionally, late eaters were less likely to report chronic diseases (e.g., CVD) or other health conditions (e.g., hypertension and hyperlipidaemia). No relevant differences in BMI, diabetes or history of cancer were found. Differences in dietary factors were also observed between meal timing patterns. Specifically, late eaters tended to consume less energy from carbohydrates while reporting higher energy from fats (Table 3). In multivariable-adjusted regression analyses, we found that late eaters were less likely to consume unprocessed/minimally processed foods as compared to early eaters (β = −0.10; $95\%$ CI −0.14 to −0.06) while reporting the increased consumption of UPFs (β = 0.13; $95\%$ CI 0.09 to 0.18) and processed culinary ingredients (β = 0.05; $95\%$ CI 0.01 to 0.10); eating late was also found to be inversely associated with adherence to the Mediterranean Diet (β = −0.07; $95\%$ CI −0.12 to −0.03) and directly associated with the FSAm-NPS dietary index (β = 0.10; $95\%$ CI 0.05 to 0.14) (Table 4; Model 2). The direction and strengths of these associations were substantially confirmed in all age groups and in men and women, especially for UPF consumption and diet quality indices (Supplementary Tables S1 and S2); however, the relationships of late eating with unprocessed/minimally processed food or processed food intake were stronger in the young group than in the elderly (Supplementary Table S1). Additionally, an effect modification by sex was observed in relation to the consumption of unprocessed/minimally processed foods and culinary ingredients (Supplementary Table S2). Analyses separated by meal type showed that late breakfast eating was associated with the reduced consumption of unprocessed/minimally processed foods and processed foods and a higher intake of UPFs at breakfast, as well as with lower adherence to the Mediterranean Diet and a higher FSAm-NPS dietary index. Similarly, participants who had delayed dinners were more likely to eat processed foods or UPFs and tended to reduce the intake of unprocessed/minimally processed foods, and also reported less adherence to a Mediterranean Diet and a larger dietary share of foods with poor nutritional quality. Finally, late lunch eaters reported a higher intake of processed culinary ingredients (Figure 1). ## 4. Discussion In this large cohort of 8688 adults from the general Italian population, a late-eating pattern was associated with both a higher consumption of UPFs and a lower intake of unprocessed/minimally processed foods, as well as with poorer diet quality. Evidence from population studies has consistently suggested that the timing of meal intake is a reliable predictor of cardiometabolic health outcomes, with late eating being reportedly associated with obesity and glucose intolerance in observational studies [10,36]. The key role of timed meals has been also supported by animal [37] and intervention studies in humans showing that late eating may adversely impact the success of weight-loss therapy [38]. Mechanistic hypotheses to support the association of late eating with adverse cardiometabolic health are likely multifactorial and include the fact that late eating may contribute to circadian misalignment, i.e., a lack of synchrony of light/dark cycles and behavioural rhythms with the endogenous circadian system [38,39,40], which was found to adversely impact both energy balance and glycaemic control [41] and changes in the diversity of the microbiota [42]. A number of studies indicate that late eaters tend to have a lower overall diet quality and higher energy intake [16,17,43,44], which may in part explain the adverse cardiometabolic health associated with delaying meals to later in the day; this was also confirmed by our analyses showing that late eating was associated with reduced adherence to a traditional Mediterranean Diet and higher values of the FSAm-NPS dietary index, which is used to compute the Nutri-Score front-of-pack labels and reflects the consumption of less-nutrient-dense foods. However, others reported that energy intake and overall diet quality were not found to vary significantly across eating times [39]. As all prior studies were focused on the nutritional composition of diets, regardless of food processing levels, we used a complementary approach by examining whether meal timing is differentially associated with the food intakes with different levels of processing according to the NOVA classification. UPF intake is on arise worldwide and constitutes more than half of the total calories eaten in the US, UK and Canada [45,46,47] while being less consumed in Mediterranean countries, such as Italy [48] and Spain [49]. An increasing number of large-scale population studies indicate that elevated intakes of UPFs can be a major threat to human health, being directly associated with an increased risk of cardiovascular disease, cancer and diabetes, as well as reduced survival [23,24]. A systematic review summarizing the evidence for the association between food processing and cardiometabolic factors in adults found that a large dietary share of UPFs is positively associated with worse cardiometabolic health, as reflected by increased levels of overweight and obesity, metabolic syndrome and high blood pressure [50]. Additionally, a high proportion of UPFs in the diet was linked to altered levels of inflammation [51], which was found to be increased in association with mistimed meals in both animals [52] and humans [53]. Both the direct association of the meal timing pattern with UPFs and its inverse relationship with unprocessed/minimally processed foods observed in our study suggest that the degree of food processing could be among the potential mechanisms/factors that link mistimed meals to impaired cardiometabolic outcomes. Besides being nutrient-poor (e.g., rich in fat, sodium and salt, and low in fibre and nutrients), UPFs are a major dietary source of chemicals (e.g., endocrine-disrupting chemicals such as bisphenol and phthalates commonly used in food packaging) and neo-formed compounds (e.g., acrylamide), which may have severe implications for health, as suggested by robust research, ranging from laboratory-based to prospective epidemiological studies [54]. Most importantly, food processing impacts both the nutritional composition (e.g., decreased antioxidant potential of some foods resulting from removing germ and bran) and food matrix (i.e., the ‘architecture’ of the food, which derives from nutrient interactions), which is crucial to the food’s overall health potential, specifically in satiety and glycaemic responses, as well as in determining nutrient bioavailability [55]. While complex, natural, minimally or unprocessed foods have more or less intact structures, and their nutritional properties are substantially unaltered [55], highly processed foods are typically unstructured, fractionated and usually heavily supplemented with free glucose and sucrose, which renders glucose more available for absorption, thereby increasing blood glycaemic response [56]. Diets with a large share of foods with a high glycaemic index are well-established risk factors for cardiometabolic diseases and mortality [57]. Interestingly, in our study late eating was associated with an approximately absolute $1\%$ higher proportion of UPF intake relative to the total food eaten; prior cohort studies showed that even such a small increment possibly leads to a higher risk of mortality both in general populations [24] and among people with pre-existing cardiovascular disease [58]. Despite consuming more UPFs, late eaters also tended to report lower diet quality overall, and in this regard, it is worth noting that most highly processed foods are typically less nutrient-dense [59]. In addition, diets high in UPFs were found to have a higher impact on mortality than the overall diet quality [24]. Lastly, a late meal pattern in our study was associated with younger age, a higher educational level and being single; all these characteristics were reportedly associated with a higher consumption of UPFs in previous cohort studies [48,60], while unmarried individuals were also found to have lower diet quality overall [61,62]. However, our estimates were from multivariable-adjusted models that also account for these socioeconomic and demographic factors, and other drivers for UPF consumption need consideration (e.g., heavy marketing, availability, low cost, attractiveness, high palatability and domination of food supply chains) [20]. ## Strengths and Limitations To the best of our knowledge, this is the first study that analysed meal timing in association with food processing and also with the dietary index underpinning the Nutri-Score front-of-pack label. The major strengths of this study include a large sample size representative of the Italian population, with a complete assessment of diet, lifestyle and other covariates used to minimize, at least in part, confounding. Moreover, the use of 24 h recall is more advantageous than other tools (e.g., food frequency questionnaires) to assess participants’ diets and to classify foods based on the extent of processing according to NOVA [63]. Despite its strengths, among its limitations, we acknowledge the observational nature of our study and the cross-sectional design of the analyses, which limits causal inference. Further, errors in the visual display of foods and potential bias could have been introduced by the interviewer in the telephone-based survey. Additionally, the decline in the use of landline phones may have resulted in an under-representation of respondents. Another weakness is that the study relied on self-reported dietary data, which are susceptible to bias and error, including social desirability and recall bias, imprecision in assessing portion sizes and inadequacies in food composition tables; however, data were collected by trained interviewers, and each participant received by mail, beforehand, a short photograph atlas and guidance notes to estimate food portion sizes. It was not possible to include some unmeasured factors as confounders due to their unavailability; however, it is a weakness in any observational study. Limitations also include that we dichotomized our population into early and late eaters using the population median timing, as a consensus on the most suitable approach to quantifying food timing is still lacking [39]. We also acknowledge that the NOVA classification remains controversial, mainly due to its equivocal definition of ultra-processed food and multiple revisions and refinements over time [64]; however, its utility value in nutrition epidemiology research has been widely acknowledged allowing comparison with previous studies. Finally, the generalizability of our findings might be limited to the Italian population. ## 5. Conclusions As well as reporting poor diet quality overall, late eaters are prone to consume more UPFs and fewer minimally processed food than early eaters. These findings contribute to increased knowledge on the mechanisms underpinning the association between late eating and adverse cardiometabolic health previously reported in several experimental and observational studies [12,13,39]. Anticipating the timing of meals may provide a complementary strategy for reducing UPF consumption and increasing unprocessed or minimally processed food intakes, which typically require more time and effort than ready-to-eat/heat meals. Undeniably, mistimed meals are strongly influenced by several factors, especially socioeconomic conditions that are difficult to tackle. Further research is warranted to test whether the consumption of UPFs could be a mediator of the association between mistimed meals and adverse cardiometabolic health. ## References 1. Roth G.A., Mensah G.A., Johnson C.O., Addolorato G., Ammirati E., Baddour L.M., Barengo N.C., Beaton A.Z., Benjamin E.J., Benziger C.P.. GBD-NHLBI-JACC Global Burden of Cardiovascular Diseases Writing Group. Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019: Update From the GBD 2019 Study. J. Am. Coll. Cardiol. (2020.0) 76 2982-3021. DOI: 10.1016/j.jacc.2020.11.010 2. 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--- title: Effects of Pine Pollen Polysaccharides and Sulfated Polysaccharides on Ulcerative Colitis and Gut Flora in Mice authors: - Yali Wang - Xiao Song - Zhanjiang Wang - Zhenxiang Li - Yue Geng journal: Polymers year: 2023 pmcid: PMC10058757 doi: 10.3390/polym15061414 license: CC BY 4.0 --- # Effects of Pine Pollen Polysaccharides and Sulfated Polysaccharides on Ulcerative Colitis and Gut Flora in Mice ## Abstract Polysaccharides are important biological macromolecules in all organisms, and have recently been studied as therapeutic agents for ulcerative colitis (UC). However, the effects of Pinus yunnanensis pollen polysaccharides on ulcerative colitis remains unknown. In this study, dextran sodium sulfate (DSS) was used to induce the UC model to investigate the effects of Pinus yunnanensis pollen polysaccharides (PPM60) and sulfated polysaccharides (SPPM60) on UC. We evaluated the improvement of polysaccharides on UC by analyzing the levels of intestinal cytokines, serum metabolites and metabolic pathways, intestinal flora species diversity, and beneficial and harmful bacteria. The results show that purified PPM60 and its sulfated form SPPM60 effectively alleviated the disease progression of weight loss, colon shortening and intestinal injury in UC mice. On the intestinal immunity level, PPM60 and SPPM60 increased the levels of anti-inflammatory cytokines (IL-2, IL-10, and IL-13) and decreased the levels of proinflammatory cytokines (IL-1β, IL-6, and TNF-α). On the serum metabolism level, PPM60 and SPPM60 mainly regulated the abnormal serum metabolism of UC mice by regulating the energy-related and lipid-related metabolism pathways, respectively. On the intestinal flora level, PPM60 and SPPM60 reduced the abundance of harmful bacteria (such as Akkermansia and Aerococcus) and induced the abundance of beneficial bacteria (such as lactobacillus). In summary, this study is the first to evaluate the effects of PPM60 and SPPM60 on UC from the joint perspectives of intestinal immunity, serum metabolomics, and intestinal flora, which may provide an experimental basis for plant polysaccharides as an adjuvant clinical treatment of UC. ## 1. Introduction Ulcerative colitis (UC) is typified by mucosal inflammation of the colon, which is one form of inflammatory bowel disease (IBD). The main clinical manifestations of UC are diarrhea, abdominal pain, bloody stools, and weight loss [1,2,3]. IBD is a chronic recurrent intestinal inflammatory disease. With its continuously increasing incidence rate, it has become a crucial public health burden globally [4]. At present, the main clinical drugs for the treatment of UC are aminosalicylate, corticosteroids, thiopurine, methotrexate, and anti-TNF-α drugs [5]. However, these pharmaceuticals lead to some side effects in patients over long-term administration, including nausea, vomiting, heartburn, diarrhea and headache [6]. Therefore, it is of great significance to explore natural products without side effects as adjuvant treatments for improving the treatment of UC. Polysaccharides are important biological macromolecules in all organisms, and they are usually extracted from various plants, animals, fungi, bacteria, and algae. Because of their biodegradability, non-toxicity, and biocompatibility, polysaccharides have been studied as therapeutic agents for many chronic diseases over the past few decades [7]. In recent years, polysaccharides from natural resources have become the research focus of UC disease due to their good safety profile. These polysaccharides are usually related to the regulation of inflammatory cytokines, intestinal flora, immune system and the protection of intestinal mucosa in the treatment of UC. For example, Ganoderma lucidum polysaccharides (GLP) significantly inhibited the secretion of cytokines (e.g., TNF-α, IL-1β, IL-6, IL-17A, and IL-4) and maintained intestinal homeostasis in DSS-induced UC mice [8]. Astragalus polysaccharides (APS) protected the colon by enhancing levels of suppressor T-reg cells and reducing the secretion of IL-17 to ameliorate TNBS-induced colitis in rats [9]. The crude polysaccharides of Korean persimmon vinegar (KPV-0) significantly increased the secretion of intestinal juice and the immunoglobulin content A of feces [10]. Hericium erinaceus polysaccharides (HEP) significantly repaired injury of the intestinal mucosa and significantly increased the levels of sIgA, IFN-γ, and IL-4 to enhance intestinal mucosal immunity in young Muscovy ducks [11]. Therefore, we speculate that pine pollen polysaccharides may affect the intestinal immunity of UC mice. Gut flora plays a key role in the metabolism, development, and function of the host immune system [12]. The active phase of IBD is accompanied by an imbalance in the gut flora [13] and decreased flora biodiversity. Furthermore, during this process, the abundance of Verrucomicrobia, Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria was significantly changed [14,15,16]. For example, harmful bacteria such as E. coli were increased and beneficial bacteria such as Alistipes, Roseburia, and Ruminococcus were decreased [17]. Shao et al. found that polysaccharides of Hericium erinaceus mycelia improved the diversity of microorganisms and simulated the production of short-chain fatty acids (SCFAs), thereby restoring the disordered abundances of Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria and alleviating the UC mice [14]. Both unfermented Yupingfeng polysaccharides and fermented Yupingfeng polysaccharides regulated the balance of gut flora and maintained the healthy intestinal barrier structure and function of weaned rex rabbits [18]. Extracellular polysaccharides (EPS1-1) from Rhizopus nigricans fermentation regulated the intestinal microflora of colorectal cancer model mice and increased the fecal content of SCFAs [19]. Therefore, we speculate that pine pollen polysaccharides may affect the gut flora of UC mice. Recently, the sulfating of polysaccharides is of increasing concern. After artificially sulfated modification, sulfated natural polysaccharides usually exhibit higher biological activities, such as antiviral [20], antioxidant [21], immunomodulatory [22], and anti-aging properties [23]. It has been shown that sulfated modified Astragalus polysaccharides have stronger antiviral activity against the Fasciola virus when compared to unmodified Astragalus polysaccharides [24]. Pumpkin polysaccharides modified by sulfating showed enhanced ability to scavenge superoxide anions, which partially improved the antioxidant activity of the polysaccharides [25]. The sulfated polysaccharides and their sulfated derivatives attenuated the LPS-induced inflammatory response by inhibiting the phagocytosis of macrophages, NO production, and the release of IL-6 and IL-1β. In addition, the effect of sulfated Ganoderma lucidum polysaccharides was more pronounced, indicating that the sulfated modification improved the anti-inflammatory effect of Ganoderma lucidum polysaccharides [26]. Sulfated Ganoderma lucidum polysaccharides had a stronger ability to remove DPPH radicals than their natural counterparts. They also exhibited higher immunomodulatory activity by increasing macrophage phagocytosis and TNF-α production [27]. Nevertheless, the role of sulfated polysaccharides in UC requires validation through further study. Our previous lab work confirmed that the sulfated polysaccharides of Masson pine pollen inhibited the proliferation of HepG2 cells [28], activated macrophages, and improved the body’s immune capability [29]. Therefore, we wondered whether sulfated Pinus yunnanensis pollen polysaccharides also lessened the progress of intestinal-related diseases. In this study, yunnanensis pine pollen polysaccharides were sulfated. The effects of yunnanensis pine pollen polysaccharides and sulfated polysaccharides on UC progression were then investigated at three levels: immunity, metabolomics and metagenomic, thus providing an empirical basis for the exploitation of polysaccharides as clinical drugs. ## 2.1. Extraction of Polysaccharides Broken Pinus yunnanensis pollen was provided by the Yantai New Era Health Industry Company (broken rate > $95\%$). Broken Pinus yunnanensis pollen polysaccharides were extracted using the water extract–alcohol precipitation method. Pinus yunnanensis pollen and distilled water in a ratio of 1:14 were boiled for 4–5 h. Then, the supernatant was collected and concentrated to $10\%$ of the original volume by rotary evaporation. Next, three-fold volume of $40\%$, $60\%$ and $80\%$ ethanol were added and mixed overnight at 4 °C for graded precipitation. The next day, white flocculent precipitate was collected. Considering the yield and biological activity, the polysaccharide precipitated by $60\%$ ethanol concentration was selected for subsequent experiments and named as PPM60. Finally, proteins were removed using the trichloroacetic acid precipitation method [30]. ## 2.2. Monosaccharide Composition The monosaccharide composition of PPM60 was analyzed using 1100 high-performance liquid chromatography system (HPLC, Agilent, Santa Clara, CA, USA). Briefly, 5 mg of PPM60 was hydrolyzed with 0.25 mol/L H2SO4 at 100 °C for 4 h. After cooling, the mixture was completely neutralized with barium carbonate overnight. The supernatant was centrifuged. Next, the 15 µL PPM60 hydrolysate and the standard monosaccharide mixture were vacuum lyophilized. Then, 20 µL PMP (0.5 mol/L) and NaOH (0.3 mol/L) were added and reacted in a water bath at 70 °C for 30 min. 25 µL of hydrochloric acid solution (0.3 mol/L) was then used to neutralize. Finally, 0.5 mL of isoamyl acetate was conducted to the extracted hydrolysate. The HPLC parameters were as follows: Column, Diamonsil-Cl8 (5 µm, 150 × 4.6 mm); Column temperature, room temperature; Flow rate, 1.0 mL/min; Mobile phase, solvent A, acetonitrile; solvent B, 0.2 mol/L H2KPO3–0.1 mol/L NaOH, pH 6.8; Elution conditions, solvent A:solvent $B = 17$:83. Detection wavelength, 250 nm (4 nm band width); reference wavelength, 360 nm (4 nm band width); injection volume, 20 μL. ## 2.3. Preparation of Sulfated Polysaccharides A sulfate derivative, named SPPM60, was obtained using chlorosulfonic acid pyridine. In a fume hood, 2 mL of pyridine was added to the pre-chilled mortar. Then, under ice bath conditions, 2 mL of chlorosulfonic acid was slowly added along the wall while stirring rapidly and continuously. The ice bath was withdrawn as soon as white solid appeared, and subsequently stirred until a yellow-white sulfonated reagent was produced. Later, the formamide polysaccharide solution (6 mL/100 mg) was slowly added and reacted at 45 °C for 4 h. Afterwards, the solution was neutralized with NaOH and transferred to a dialysis bag (Solarbio, Beijing, China) for purification. After dialysis until colorless, the liquid was concentrated using SB-1000 rotary evaporator (EYELA, Tokyo, Japan) and the concentrated liquid was freeze-dried by FDU-1200 freeze-dryer (EYELA, Tokyo, Japan). Finally, the barium sulfate turbidity method was conducted to assess sulfur content, and the degree of substitution. ## 2.4. Infrared Spectroscopy Assay The characteristic absorption peaks of PPM60 and SPPM60 were determined using iS 50 FT-IR spectrophotometer (Thermo, Waltham, MA, USA). PPM60 and SPPM60 were powdered and pressed into tablets. Then, the samples were measured in the frequency range of 4000–400 cm−1 [28]. ## 2.5. Animals and DSS Colitis Model SPF Male C57BL/6 mice, weighing 18–20 g (six weeks old), were purchased from Jinan Pengyue Laboratory Animal Breeding Co., Ltd. (Quality Certification of Laboratory Animals: SCXK (Lu) 20140007). This animal study was conducted in accordance with the ethical guidelines approved by the Committee for the Protection and Use of Shandong Normal University Animals (No. AEECSDNU2019042). Forty mice were randomly divided into four groups ($$n = 10$$): healthy control group (HC); model group (DSS); Pinus yunnanensis pollen polysaccharides group (PM); and sulfated polysaccharides group (SPM). UC mice were induced using $3\%$ DSS (MP Biomedicals, Santa Ana, CA, USA) water solution, replaced with normal water after five days. The control group was given normal water (see Table 1). At the same time each day, mice in PM and SPM groups were treated with 200 mg/kg dose of PPM60 and SPPM60 by intragastrical administration (i.g), respectively. The HC and DSS groups were given equal volumes of drinking water in the same manner. In addition, PPM60 and SPPM60 treatment was used at the modeling stage simultaneously to conduct the prevention program. The mice were weighed, fed, and checked for conditions (e.g., activity, backward hair, etc.) daily. After seven days, the mice were euthanized by cervical dislocation after anesthesia, while biological materials such as blood, colon tissue, feces and cecum contents were collected for subsequent experimental analysis. ## 2.6. Clinical Disease Scores According to a mentioned method [31], the disease activity index (DAI) of mice was calculated daily to evaluate the severity of the disease. Briefly, the animals were evaluated for weight loss (0–4), stool consistency (0–4), and blood in the stool (0–4), resulting in a maximum DAI score of 12. ## 2.7. Hematoxylin and Eosin Staining The colon was fixed in $4\%$ formaldehyde solution (Servicebio, Wuhan, China). After adequate fixation, colon tissue was embedded and pathological tissue sections were prepared. H&E staining was then performed to evaluate colon injury and inflammation. ## 2.8. ELISA The colon tissues were washed with pre-cooled physiological saline and dried with filter paper. Saline was then added at a ratio of 1:9. Next, the tissues were ground for 30 s and stopped for 30 s by a biological sample homogenizer (Aosheng Instrument, Hangzhou, China) three times, and then placed on ice for 5 min. After three cycles, the homogenate were centrifuged at 12,000 rpm/min at 4 °C for 20 min Finally, supernatants were collected to detect the expression of IL-1β, IL-6, TNF-α, IL-2, IL-10, IL-13, and sIgA by corresponding ELISA Kit (Multi Sciences, Hangzhou, China). In addition, the levels of serum CRP and D-lactic acid were determined by the CRP (Multi Sciences, Hangzhou, China) and D-lactic acid (Jiancheng Technology, Nanjing, China) kits according to the manufacturer’s instructions. The absorbance values were measured using Spectra Max Plus Microplate Reader (Molecular Devices, San Jose, USA) and the expression of each molecule was calculated according to the standard curve formula. ## 2.9. Sample Preparation and 1H-NMR Spectroscopy Frozen serum samples were thawed to perform NMR analysis. Then, 500 µL of phosphate buffer solution (K2HPO4-NaH2PO4, 0.1 M, pH 7.4; $30\%$ D2O containing $0.1\%$ TSP, Sigma-Aldrich, St. Louis, MO, USA) was added to 100 µL of serum for nuclear magnetic resonance (NMR) detection. After centrifugation at 10,000 rpm for 10 min at 4 °C, approximately 550 µL of the clear supernatant was transferred into 5-mm NMR tubes (Wilmad-Lab Glass, Warminster, PA, USA) for sampling preparation. All 1H-NMR spectra were obtained using a superconductor shielding FT NMR spectrometer equipped with 13C and 1H double-resonance optimization of a 5-mm CPTCI three-trans detector CryoProbeTM AVANCE 400 III (Bruker, Billerica, Germany) under the following conditions: 400.13 MHz proton resonance frequency, zg30 pulse sequence, 8012.8 Hz spectral width, number of scans was 256 at 298 K, 1 s relaxation delay, and 12 μs pulse length. Topspin 3.2 was used to process the spectral data. ## 2.10. 16S rDNA Amplicon Sequencing Analysis Fecal (F) and cecum content (C) samples were freshly collected under aseptic conditions. The samples were stored at −80 °C until detection. The genomic DNA of the samples were extracted using the cetyltriethylammonium bromide method, and the purity and concentration of the DNA were detected via agarose gel electrophoresis. PCR amplification was carried out on the sequence with the upstream primer ′5-CCTACGGRRBGCASCAGKVRVGAAT-3′ and the downstream primer ′5-GGACTACNVGGGTWTCTAATCC-3′ of 16s V3 and V4 variable regions. A library was constructed using the Ion Plus Fragment Library Kit 48 rxns and was quantified using Qubit and Q-PCR. After qualification, the library was sequenced by Illumina MiSeq sequencing platform (GENEWIZ, Suzhou, China). The raw data were first spliced and filtered to obtain clean data. Operational taxonomic unit (OTU) clustering and species classification analysis were then performed based on valid data. Species annotations were made for the representative sequences of each OTU, and the corresponding species information and species-based abundance distributions were obtained. At the same time, the OTUs were analyzed for abundance, alpha-diversity, Venn plots, and petal plots to obtain species richness and uniformity information for the samples. Information regarding the common and unique OTUs between different samples or groups were also obtained. Statistical analysis methods, such as t-test and MetaStat, were used to test differences in the species composition and community structure of the grouped samples to further explore variations in the community structures between the grouped samples. ## 2.11. Statistical Analyses Statistical analyses were performed using the paired Student’s t-test or multi-way analysis of variance. Statistical analyses were conducted using GraphPad Prism software (GraphPad, Inc., La Jolla, CA, USA). Differences were considered statistically significant when $p \leq 0.05.$ All experiments were conducted independently at least three times. ## 3.1. Monosaccharide Composition and Sulfating of PPM60 According to the results of HPLC, PPM60 is mainly composed of galactose, glucose, xylose, mannose, rhamnose, and an unknown monosaccharide with molar ratio as 12.830:10.449:29.693:1:1.415:1.426 (Figure 1a). The substitution degree of sulfuric acid was 1.45. IR spectroscopy showed that PPM60 had an absorption peak of O-H, with a stretching vibration at 3372.63 cm−1, and a stretching vibration of C-H appeared at 2929.58 cm−1. These are the characteristic absorption peaks of polysaccharides. SPPM60 had a characteristic absorption peak of S=O at 1224.56 cm−1 and a characteristic absorption peak of C-O-S at 831.45 cm−1. In addition, the absorption peak of the O-H stretching vibration of SPPM60 was weaker than PPM60, indicating that -OH was replaced by SO42− (Figure 1b). Furthermore, the substitution degree of sulfation was 1.45. These results demonstrated that we successfully obtained PPM60 and SPPM60. ## 3.2. Effects of PPM60 and SPPM60 on Disease Progression in UC Mice By monitoring the body weight of the mice in each group, we found that the HC group displayed an overall increasing trend and were in a normal growth state. In contrast, the bodyweight of the DSS group showed a sharp downward trend on the fifth day, even exceeding $20\%$ by the seventh day. The DAI scores of the DSS groups also increased sharply on the same day. While the PM and SPM groups also had a significantly reduced body weight and increased DAI score on day five, the overall trend was less than in the DSS group. ( Figure 2a,b). In addition, the DSS mice began to develop loose and/or bloody stools, and the average length of colons was 4.7 ± 0.28 cm, which was significantly shorter compared to the HC group (6.7 ± 0.18 cm). Notably, PPM60 and SPPM60 treatment partially ameliorated the colon shortening phenomenon in PM (5.2 ± 0.09 cm) and SPM (5.6 ± 0.17 cm) mice, respectively (Figure 2c). Figure 2d shows the histologically stained colon tissue of mice from the four groups. The colon structure of the HC group was intact, without damage to the mucosal layer, and the epithelial cells were not shed. In contrast, the colon of mice in the DSS group had obviously damaged mucosal layers, with the mucosal epithelial cells missing (black arrows), and connective tissue hyperplasia (red arrows). Moreover, the damage extended to the submucosa, and there were more inflammatory cell infiltrations in the mucosa and submucosa, including lymphocytes and granulocytes (yellow arrows). In the PM group, the mucosal layer of the colon tissue was also damaged. Differently, the structure of the mucosal epithelium was intact, and there was a small amount of visible connective tissue hyperplasia, as well as a few visible inflammatory cell infiltrations into the mucosa and submucosa (red arrow). Otherwise, there were no other obvious abnormalities. In the SPM group, there was damage to the local mucosal layer of the colon tissue and a small amount of connective tissue hyperplasia (red arrow). The damage extended to the submucosa, and there was a small amount of inflammatory cell infiltration into the mucosa and submucosa. These data reveal that the UC mice model was successfully established by DSS, whereas progression of the disease was inhibited by the PPM60 and SPPM60 treatment. ## 3.3. Effects of PPM60 and SPPM60 on Intestinal Immunity in UC Mice Compared with mice in the HC group, the levels of IL-1β, IL-6, and TNF-α was obviously increased in the DSS group, indicating that there was inflammation in the colon tissue of the mice. The concentrations of IL-1β and IL-6 of mice in the PM and SPM groups displayed a downward trend, while the increase of TNF-α was not relieved (Figure 3a–c). In the DSS group, the concentrations of IL-2, IL-10, and IL-13 were decreased, which had opposite trends in the PM and SPM groups (Figure 3d–f). Serum D-lactic acid in the DSS group was slightly upregulated, which might be related to the hemolysis of samples in the HC group. On the contrary, D-lactic was markedly reduced in the PM and SPM groups (Figure 3g). Furthermore, CRP was clearly upregulated in the DSS group and was inhibited in the PM and SPM groups (Figure 3h). Moreover, there was a significant augmentation of sIgA in the DSS group, while SPPM60 notably reversed the increasing trend (Figure 3i). These results demonstrate that PPM60 and SPPM60 had a positive effect on the intestinal inflammation of DSS-induced UC mice through alleviating intestinal inflammation. Furthermore, compared with PPM60, the effects of SPPM60 on intestinal immunity was slightly stronger. ## 3.4.1. Multivariate Statistical Analysis According to the PCA model (Figure 4a), the HC group was clearly distinguished from the other three groups, but the DSS, PM and SPM groups were not clearly separated. However, in the model of PLS-DA and OPLS-DA (Figure 4b,c), the four groups were clearly separated, and the validation model of OPLS-DA showed that the model had not been overfitted (Figure 4d). We then compared the four groups of mice randomly in pairs; the HC group and DSS group were clearly distinct, and the OPLS-DA model test also showed that the results were relatively reliable (Figure S1). The DSS group and the PM group showed good separation in all three analysis methods (Figure S2). Although the DSS group and SPM group were not very distinct in the PCA analysis, the separation between these two groups in the PLS-DA and OPLS-DA was more obvious. The models were found to be more reliable (Figure S3). ## 3.4.2. Qualitative Analyses of Serum Differentially Expressed Metabolites and Changes in Metabolic Pathways To determine the differential expression of metabolites, we ranked the VIP values obtained by multivariate statistical analysis from high to low, and the chemical shift of VIP ≥ 2 was used to characterize the metabolites. Compared with the HC group, eight possible differentially expressed metabolites were identified in the DSS group (Table 2): N-acetyl-L-alanine, acetic acid, L-fucose, lactic acid, taurine, betaine, acetylcholine, and allose. Compared with the DSS group, seven potential differentially expressed metabolites were found in the PM group (Table 3): N-acetyl-L-alanine, acetic acid, lactic acid, fructose-6-phosphate, allose, D-xylose, and L-carnitine. There was possible differential expression of seven metabolites in the SPM group compared with the DSS group (Table 4): betaine, glyceryl phosphate, L-serine, D-xylose, acetylcholine, lactic acid, and allose. The above-mentioned possible differentially expressed metabolites were entered into MetPA for analysis. As shown in Figure 5a, compared with the HC group, the main changed metabolic pathways of the DSS group mice included pyruvate metabolism, glycolysis/gluconeogenesis, taurine and hypotaurine metabolism, fructose and mannose metabolism, glycine, serine, and threonine metabolism, and primary bile acid biosynthesis. Signal-pathway enrichment analysis of the DSS group (Figure 5b) showed that the changes of the metabolic pathways mainly occurred in pyruvate metabolism, taurine and hypotaurine metabolism, ethanol degradation, betaine metabolism, phospholipid biosynthesis, fructose and mannose degradation, and other metabolic pathways. Compared with the DSS group, the PM group mainly exhibited the following abnormal metabolic pathways: pyruvate metabolism, glycolysis/gluconeogenesis, starch and sucrose metabolism, mutual conversion of pentose, and glucuronate interconversions (Figure 5c). A summary chart of the PM metabolic enrichment pathways mainly focused on amino sugar metabolism, gluconeogenesis, pyruvate metabolism, β-oxidation of long-chain fatty acids, ethanol degradation, carnitine synthesis, and other metabolic pathways (Figure 5d). Compared with the DSS group, the metabolic pathways of the SPM group were mainly associated with glycine, serine and threonine metabolism, glycerophospholipid metabolism, glycerolipid metabolism, pentose and glucuronic acid interconversion, glucuronate interconversions, glyoxylate and dicarboxylate metabolism, and aminoacyl-tRNA biosynthesis (Figure 5e). The enrichment analysis chart (Figure 5f) mainly involved phospholipid biosynthesis, methionine metabolism, glycine and serine metabolism, homocysteine degradation, de novo triacylglycerol biosynthesis, glycerol phosphate shuttle, cardiolipin biosynthesis and phosphatidylethanolamine biosynthesis, and other metabolic pathways. ## 3.5. Effects of PPM60 and SPPM60 on Gut Flora in UC Mice Rarefaction curves are used to reflect the depth of sequencing (Figure 6a). Rank abundances were performed to reflect the richness and uniformity of the species in the sample (Figure 6b), and species accumulation boxplots (Figure 6c) were used to reflect the rate of new species appearance under continuous sampling. The curve and box plots gradually flattened with an increasing number of species, indicating sufficient sampling and the uniform distribution of species. In addition, increasing the data generated fewer new species. This indicated that the depth of sample sequencing gradually became reasonable to analyze the data. For the contents of the mice cecum, the numbers of OTUs in HC, DSS, PM and SPM were 1117, 958, 1091, and 978, respectively (Figure 6d). In the mice feces, there were 1019, 906, 1003, and 1003 OTUs in the HC, DSS, PM and SPM groups, respectively (Figure 6e). Compared with the control HC group, there was a decreased number of OTUs in both the cecum contents and the feces of the DSS group mice. In addition, the species diversity was partially recovered by PPM60 and SPPM60 treatments. Figure 6g shows the relative abundance of flora in the feces and cecum contents at the phylum level. Bacteroidetes and Firmicutes were the main gut flora, followed by Proteobacteria and Verrucomicrobia. Figure 6f shows the relative abundance of flora in the feces and cecum of mice in the four groups at the genus level. In the mice cecum contents, the most abundant bacteria of the HC group were Bacteroides, Ileibacterium, Lactobacillus, and Odoribacter. In the DSS group, the abundances of Bacteroides and Akkermansia were significantly elevated, while the abundance of Ileibacterium was significantly decreased. Instead, the abundance of Akkermansia was decreased in the PM and SPM groups. In addition, the abundance of Ileibacterium in the SPM group was obviously recovered. In the feces of mice, Bacteroides, Ileibacterium, and Lactobacillus were the dominant genera of the HC group. Compared with the HC group, the abundances of Bacteroides, Helicobacter, Akkermansia, Odoribacter, and Turicibacter were increased and the abundances of Ileibacterium and Lactobacillus were decreased in the DSS group. In the PM group, Helicobacter, Lactobacillus, and Akkermansia showed a recovery trend. In the SPM group, there was a regulatory effect on Ileibacterium, Akkermansia, Odoribacter, and Turicibacter. Figure 7 shows the species with significant differences at the genus level. In the mice feces and cecum contents, there were significantly different abundances of Aeroococcus, Akkermansia, Parasuttetella, Enterorhabolus, Parvibacter, Turicibacter, Lactobacillus, Romboutsia, and Arthromitus among the groups. In the feces of mice of the DSS group, all the abundances of Aerococcus, Akkermansia, Parasuttetella, Parvibacter, Turicibacter, and Romboutsia were increased, while the abundances of Enterorhabolus, Lactobacillus and Arthromitus were decreased. Compared with the DSS group, the relative abundances of Aerococcus, Akkermansia, and Parvibacter were re-inhibited, while Enterorhabolus, Lactobacillus, and Arthromitus were re-promoted in the PM group. In the SPM group, Aeroococcus, Akkermansia, Parvibacter, Turicibacter, and Romboutsia were reduced and Enterorhabolus and Lactobacillus were elevated. Therefore, PPM60 and SPPM60 partially reversed the disorder of the gut flora and regulated different flora. ## 4. Discussion Although UC is not directly life-threatening, it is often debilitating and can lead to dangerous complications. Therefore, it is important to explore the treatment of UC. Pinus yunnanensis Franch. is an evergreen coniferous tree of Pinaceae. It is distributed at altitudes between 400 m and 3100 m on mountains, river basins, dry and sunny slopes in Southwestern China, and is one of the main forest tree species [32]. Pine pollen is the male spore of Pinus yunnanensis Franch. According to the Chinese ancient medical code “Compendium of Materia Medica”, pine pollen has the functions of moistening the heart and lungs, benefiting qi, eliminating wind and stopping bleeding. As a traditional Chinese medicine and health food, it has a good relieving effect on fatigue, colds, prostate, anemia, diabetes, high blood pressure, asthma, etc. [ 33]. These beneficial effects are attributed to the various chemical constituents, including nucleic acids, enzymes and coenzymes, proteins, fats, acids, phospholipids, monosaccharides, polysaccharides, flavonoids, vitamins, etc. [ 34]. Thus, pine pollen has received a lot of attention in the food, biochemical and medical fields due to its high values for utilization. Sulfated polysaccharides are a group of polysaccharide derivatives with a complex steric structure and rich biological activity, with highly anticoagulant, antioxidant, antiproliferative, immune system modulating and antitumor effects [35]. However, natural sulfated polysaccharides are relatively scarce. Polysaccharides become acidic polysaccharides containing sulfate groups after sulfating, which can easily bind to specific structural domains of proteins, thus changing their conformation and affecting their biological activity [36]. In this study, a boiling alcohol precipitation method was conducted to extract. Previous experimental results illustrated that the content and activity of crude polysaccharide precipitated by $60\%$ ethanol (PPM60) was high, hence we selected PPM60 for sulfating modification and the production was named SPPM60. We revealed that PPM60 was mainly composed of galactose, glucose, xylose, mannose, rhamnose, and an unknown monosaccharide. The sulfate substitution degree of SPPM60 was 1.45. In addition, SPPM60 also had the characteristic absorption peaks of S=O and C-O-S, and the characteristic absorption peaks of PPM60 were relatively reduced, indicating that the polysaccharide was successfully sulfated. Subsequently, because of its simplicity, reliability and good reproducibility, $3\%$ DSS was used to induce acute UC in mice. The data shows that, compared with the HC group mice, the mice in the DSS group began to show a series of symptoms, including weight loss, increased DAI index, significantly shortened colon length, serious mucosal tissue damage, and a large number of inflammatory cell infiltrations, indicating that we successfully induced UC lesions in mic. Notably, PPM60 and SPPM60 had a certain effect on UC mice to improve the development and pathological changes. Specifically, colon shortening and injury was repaired. Serum CRP is a sensitive indicator of various infections and non-infectious inflammation in the body. It is a non-specific marker of systemic inflammation and one of the commonly used clinical indicators [37]. CRP is involved in the regulation of inflammatory response and is often used to reflect the inflammatory levels of IBD patients [38,39]. One of the pathophysiological characteristics of UC is a persistent intestinal inflammatory response, which can lead to chronic inflammation and tissue damage [40]. Studies have shown that the mRNA and proteins expressions of proinflammatory cytokines, including IL-1β, IL-6, and TNF-α, are increased in UC [41], while the levels of anti-inflammatory cytokines, including IL-4, IL-10 and IL-13, are decreased [42]. The anaerobic fermentation of carbohydrates by flora in the intestine produces D-lactic acid. Mammals only produce a small amount of endogenous D-lactic acid. Therefore, the increase of serum D-lactic acid may be a by-product of anaerobic fermentation by specific bacteria [43]. Clinical studies report that serum D-lactic acid of IBD patients is significantly higher than of control individuals, indicating that the intestinal mucosa of patients with acute IBD maybe damaged [44]. In addition, SIgA is also important for maintaining intestinal homeostasis [45]. Our results reveal that pro-inflammatory cytokines (IL-1β, IL-6, TNF-α), CRP, and serum D-lactic acid were significantly increased, while anti-inflammatory cytokine levels (IL-2, IL-10, and IL-13) were significantly reduced in the UC model group. However, after intervention with PPM60 and SPPM60, the trends of these cytokines, serum CRP and D-lactic acid were reversed. These results indicate that PPM60 and SPPM60 recovered the intestinal barrier by reducing inflammation in UC mice. Non-targeted metabolomics is commonly used to detect changes of metabolites. This method can reveal disease-related metabolic disorders by measuring the changes of multiple metabolites in biological samples such as blood [46]. NMR is one of the main analytical techniques used in metabolomics. It has the advantages of simple sample preparation, good reproducibility, no sample damage and sample recycling [47]. IBD patients have reduced fatty acids, increased acylcarnitine levels, enhanced mitochondrial β-oxidation [48], and increased serum N-acetyl compounds during the active phase of the disease [49], indicating that they have a higher energy requirement for recruiting immune cells to fight inflammation [48]. In addition, the levels of glycolic acid, L-isoleucine, symmetrical dimethylarginine, serine, phosphoric acid ethanolamine, proline, and hexanoyl carnitine are upregulated in the serum of pediatric IBD patients [50]. Compared with the HC group, serum metabolite D-lactic acid levels were increased in the DSS group. On the contrary, D-lactic acid levels in the PM and SPM groups were decreased. These changes indicate that PPM60 and SPPM60 had some reparative effects on the damaged intestinal barrier. Furthermore, after PPM60 intervention, the levels of fructose-6-phosphate, allose and D-xylose were upregulated, whereas the levels of N-acetyl-L-alanine, acetic acid, and L-carnitine were downregulated compared with the DSS group. The pathway analysis also shows that these metabolites were mainly involved in pyruvate metabolism, glycolysis/gluconeogenesis pathways, pentose and glucuronate interconversions. After SPPM60 intervention, betaine, glyceryl phosphate, D-xylose, L-serine and acetylcholine were upregulated. These were involved in glycine, serine, and threonine metabolism, glycerophospholipid metabolism, glyoxylate and dicarboxylate metabolism, and aminoacyl tRNA biosynthesis pathways. Overall, these data illustrate that PPM60 and SPPM60 regulated and repaired the imbalance of serum energy and lipid metabolisms, thereby preventing the disease progression of UC mice. Differently, PPM60 mainly regulated the metabolic pathways related to energy metabolism, while SPPM60 mostly regulated the metabolic pathways related to lipid metabolism. IBD is a series of complex diseases that cause chronic inflammation of the gastrointestinal tract. Compared with healthy individuals, the microbial diversity of IBD patients is greatly reduced [51]. In the small intestine and colon, segmented filamentous bacteria (SFB) can increase the number of host T-reg cells and regulate the differentiation of Th17 cells thereby promoting the production of IL-22-expressing CD4+ T cells [52]. Aerococcus is a harmful bacterium, which can cause diseases such as urinary tract infection (UTI), bloodstream infection (BSI), and endocarditis to spinal infection [53]. Parasutterella is associated with chronic intestinal inflammation, which is significantly increased in patients with irritable bowel syndrome (IBS) and IBS mice [54]. Turicibacter is a type of harmful Erysipelothrichaceae bacterium and is related to the development of Tsumura Suzuki obesity and diabetes [55]. Lactobacillus, a beneficial bacterium of the phylum Firmicutes, has antibacterial activity in vitro. It can be used as a functional food to effectively fight a variety of diseases [56,57,58]. Our experimental data showed that PPM60 and SPPM60 increased the abundance of beneficial bacteria, such as Lactobacillus and segmented filamentous bacteria (SFB). Instead, the abundance of harmful bacteria, such as Aerococcus and Turicibacter was reduced. By regulating the imbalance of gut flora, PPM60 and SPPM60 relieved UC progression. In addition, we also found a significantly increased abundance of Akkermansia in DSS mice. Akkermansia is a mucin-degrading beneficial bacterium of the phylum Verrucomicrobia, and mucin is the only carbon source of Akkermansia. The presence of Akkermansia is associated with healthy intestines and is negatively correlated with several disease states [59]. Akkermansia can adhere to intestinal epithelial cells in vitro, which enhances the integrity of the intestinal cell monolayer and resists the impact of the damaged intestinal barrier [60]. The abundance of Akkermansia is reduced in obese and type 2 diabetic patients, and this reduction is related to poorer intestinal health and impaired metabolic status [61]. Studies have shown that, after DSS treatment, the abundance of Akkermansia significantly increases. Because Akkermansia specifically degrades mucin, the changes of this bacteria may be related to the amount of mucin in the intestine. Akkermansia can not only degrade mucin but can also stimulate mucin synthesis via an autocatalytic process [62]. Lipopolysaccharides (LPS) derived from gram-negative bacteria are the main causes of inflammation. Studies have found that the number of Enterobacteriaceae and Akkermania on the colonic mucosa were increased during the induction of colitis [63]. Nagalingam et al. found that, in the cecum of DSS-induced colitis mice, the abundance of Verrucomicrobia was increased, which may be related to its ability of metabolize sulfur and degrade mucin [64]. Our data show that Akkermansia abundance was significantly increased in the DSS group, while it was decreased in the PM and SPM groups. We analyzed that there were two reasons for this phenomenon: the first is the ability of Akkermansia to degrade and synthesize mucin, and the second is that Akkermansia is a gram-negative bacterium related to inflammation. ## 5. Conclusions Both PPM60 and SPPM60 had ameliorative effects on DSS-induced UC, specifically in improving colon shortening, repairing intestinal injury, reducing intestinal inflammation, regulating serum metabolism, and regulating the balance of intestinal flora. Differently, PPM60 was more effective in inhibiting pro-inflammatory cytokines and mainly regulated metabolic pathways related to energy metabolism. Furthermore, PPM60 downregulated the abundance of harmful bacteria (Akkermansia and Aerococcus) and upregulated beneficial bacteria (Lactobacillus and Arthromitus). Conversely, SPPM60 tended to promote anti-inflammatory cytokines and mainly regulated metabolic pathways related to lipid metabolism. Moreover, SPPM60 downregulated the abundance of Akkermansia, Aerococcus, and Turicibacter, and upregulated Lactobacillus. To summarize, SPPM60 had a better effect on intestinal immunity than PPM60, while the recovery effect of intestinal flora species diversity was weaker than PPM60. 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--- title: Does the Loss of Teeth Have an Impact on Geriatric Patients’ Cognitive Status? authors: - Dana Gabriela Budală - Carina Balcoș - Adina Armencia - Dragoș Ioan Virvescu - Costin Iulian Lupu - Elena Raluca Baciu - Roxana Ionela Vasluianu - Monica Tatarciuc - Ionuț Luchian journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10058759 doi: 10.3390/jcm12062328 license: CC BY 4.0 --- # Does the Loss of Teeth Have an Impact on Geriatric Patients’ Cognitive Status? ## Abstract Significant changes in the microstructure of the brain cause dementia and other mental declines associated with aging and disease. Although research has established a connection between oral health and dementia, the underlying pathologic mechanisms are still unknown. Aim: Our aim was to evaluate dentures’ impact on the cognitive state of geriatric patients. Material and methods: A total of 108 individuals seeking treatment at the Faculty of Dental Medicine in Iasi, Romania, participated in the study, which ran from May 2022 to October 2022. Cognitive dysfunction was assessed using the Mini-Mental State Examination. The acquired data were analyzed with IBM SPSS 26.0, and the p-value was set at 0.05. Results: The average value of the MMSE score was 21.81 ± 3.872. Differences between groups of wearer/non-wearer subjects were statistically significant for most of the questions in the questionnaire. Linear regression analysis showed that individuals with a high MMSE score have prosthodontic treatment. A decrease in the MMSE score is associated with a decrease in masticatory efficiency ($B = 1.513$, $$p \leq 0.268$$). Conclusions: This study provides further evidence that tooth loss is associated with worse cognitive performance. It is thus conceivable that the necessary effects can be achieved by increasing the efforts dedicated to preventing tooth loss in the adult population. ## 1. Introduction The most important trend of the 21st century is the general trend of an aging population. The aging of the population is the outcome of several interrelated changes, including falling birthrates, longer life expectancies, and later deaths [1,2]. By 2050, it is predicted that around $16\%$ of the world’s population will be over the age of 65, which is more than double the present number and a fivefold rise since 1950 [3,4]. Age-related declines in cognitive abilities such as memory, judgment, language, and focus are a natural consequence of the aging process. Neurodegenerative, vascular, and dysthymia/dysphoria disorders are all potential causes. Social, functional, and vocational activities can all be impacted by impairments in cognition and IQ [5,6]. The brain’s microstructure undergoes considerable alterations as a result of aging and diseases, leading to cognitive loss. Changes in brain morphology (the shape and structure of the brain) are a normal part of the aging process, with the most common alteration being significant atrophy [7]. The neuroimaging community has extensively examined age- and disease-related changes in the structure of the brain. For the first time, cross-sectional data may be compared directly to form attributes from atlases that are universally acknowledged [8]. Global brain shrinkage, changes in brain functional responses, and cognitive decline are all common side effects of normal aging [8]. As a result of this, brain changes exhibit a significant degree of individual variation and appear to be reliant upon different factors, such as mastication [9]. Impaired cognitive function is associated with both nonmodifiable (such as age and gender) and controllable (such as blood pressure and diabetes) risk factors [10,11,12]. Cognitive impairment is not an illness but a description of a condition. It means that the person in question has trouble with tasks such as memory or paying attention. They might have trouble speaking or understanding. Additionally, they might have difficulty recognizing people, places or things, and might find new places or situations overwhelming. Despite extensive research, no definitive treatment for this cognitive deficit has yet been found [13]. Since more people with mild cognitive impairment than without it go on to acquire Alzheimer’s disease or similar dementia conditions, researchers have tried to examine and prevent mild cognitive impairment in an effort to diminish the societal and financial costs related to the condition. Potentially modifiable risk factors for cognitive impairment have been identified as poor dental health and poor mastication [14]. According to scientific evidence, frequent sensory input when chewing causes an increase in blood flow to the brain and a greater number of pyramidal neurons in the hippocampus. When it comes to humans, this area of the brain is critical for the generation and retrieval of episodic memory [15,16]. Neurotransmitter function may be negatively affected by insufficient mastication capacity as well as by the absence of afferent stimulation by masticatory receptors. This may result in a decrease in the amount of acetylcholine produced, which is responsible for the stimulation of electrical flow between neurons [17,18]. Poor oral health has been associated with cognitive impairment in several long-term cohort studies [19,20]. A correlation has been shown between the number of teeth in a person’s mouth and their level of cognitive performance. It has also been shown in several case studies that restoring tooth and masticatory function with an appropriate prosthesis can increase functional activity in the brain [21,22]. The periodontal ligament and masticatory muscle are thought to receive their nerve supply from the trigeminal nerve. The attenuation of trigeminal nerve sensory input as a result of ongoing tooth loss has been demonstrated to impair higher-level brain functions including learning and memory. [ 23,24]. Improvements in oral motor performance and shifts in mandibular position are closely connected to deterioration in masticatory muscle function, and degradation of the ά-γ coupling mechanism may be associated with senile dementia in some cases [25]. Previous research has shown a link between dental health and dementia, but the pathogenic processes by which this occurs remain unclear. Despite the fact that we are aware of certain data that suggest otherwise, we are not aware of any meaningful evidence about the impact that dentures play in the cognitive state of older people who are edentate. It is becoming increasingly clear that oral health may play a crucial role in a person’s cognitive performance as they age. Many studies have found a link between the number of natural teeth a person has and their cognitive abilities [26,27]. Even if we are aware of certain statistics that suggest otherwise, we are not aware of any meaningful evidence about the impact that dentures play on the cognitive state of older people who have lost all of their teeth. Although preliminary clinical investigations have supported this logic, it is still just conjectured as to whether or not it is possible to reverse decrease in cognitive function by improving chewing performance through restorative treatments. As a result, the present study was designed to test the hypothesis that dentures, acting through the mastication route, will have an impact on the cognitive state of the senior elderly population. ## 2.1. Study Population The study was conducted with the approval of the Ethics Committee of the Grigore T. Popa University of Medicine and Pharmacy of Iasi (No. $\frac{18}{05.05.2022}$), and the included participants all consented to the procedures. The research was conducted from May 2022 to October 2022. At the recruitment stage, the study objectives were explained, inviting all adults aged 60 years and above to participate in the study. The exclusion criteria were: [1] younger than 60 years old, and [2] cognitive disease already being treated. Patients seeking treatment at the Faculty of Dental Medicine in Iasi, Romania, were eligible for enrolment; a total of 112 patients who agreed to take part in this study were included. The intraoral examination was performed by a single examiner who only considered the number of missing teeth and not the efficacy of treatment for determining the edentulousness type. The patients were given free rein as to how they wanted their mastication assessed, and the goal was to determine whether or not cognitive impairment was inversely proportionate to the number of patients with at least some of their original teeth. ## 2.2. Cognitive Dysfunction Assessment Cognitive dysfunction was assessed using the Mini-Mental State Examination (MMSE), which is a commonly used tool for measuring cognitive function. The MMSE works well as a screening tool to distinguish between patients with and without cognitive impairment. Since its initial publication in 1975, Folstein’s study has been cited about 50,000 times in the Scopus database [28]. Its rapid implementation and widespread use may have contributed to this effect. Furthermore, a recent meta-analysis demonstrated that the instrument’s sensitivity was $85\%$, with specificity around $90\%$, for the diagnosis of dementia in both community and primary care settings [29]. The instrument can also measure changes in cognitive status that may benefit from intervention when administered repeatedly. The measure should not take the place of a thorough clinical evaluation of mental status, however, as it is unable to diagnose the circumstances surrounding changes in cognitive function. The test also significantly emphasizes verbal response, reading, and writing. The Mini-Mental State Examination (MMSE) is used for conducting a complete and methodical evaluation of mental status. The MMSE was translated and validated in Romania [30]. Five cognitive processes are examined in this 11-question test: orientation, registration, attention and calculation, recall, and language. The maximum score achievable is 30. Cognitive impairment is indicated by a score of 23 or less. The MMSE can be administered in just 5–10 min, making it convenient to use frequently and on a regular basis. ## 2.3. Assessment of Covariates People aged 60 and above have varying degrees of cognitive impairment. There is a wide variety of potential causes, and often these factors overlap. Recent epidemiological studies estimate that between $4.7\%$ and $8.7\%$ of the older population may have dementia, while as many as $42\%$ may be living with moderate cognitive impairment (MCI) [31,32,33]. Controlling for demographic covariates such as age, education, race, and neighborhood (or place of residence) will strengthen the study design. Screening tests are advised for the diagnosis of cognitive impairment in persons who have a high suspicion of having Alzheimer’s disease (AD) or other disorders. Therefore, we collected information about participants’ sociodemographic characteristics (i.e., age, gender, education level, place of residence) and health conditions (e.g., presence of chronic conditions). ## 2.4. Statistical Analysis The acquired data were examined with IBM SPSS 26.0 (SPSS Inc. Chicago, IL, USA). The statistical significance was set at $$p \leq 0.05.$$ The descriptive study of the group’s general characteristics was reported as frequencies, means, and standard deviations. We employed the Student’s t-test and the ANOVA test for comparisons. Correlations between MMSE scores and specific variables were determined by applying linear regression (sex, education, edentulous treatment, and masticatory efficiency). ## 3. Results In total, 108 subjects participated in the study, with an average age of 67.79 ± 14.44 (minimum age of 28 and maximum age of 87) and a greater proportion of female subjects ($57.4\%$), with $53.7\%$ having a high school education, and the majority coming from an urban environment ($64.8\%$). A total of $85.2\%$ of the patients reported comorbidities, with cardiovascular, metabolic, and locomotor problems being the most prevalent (Table 1). Concerning dentition-related traits, more than half of the participants had several types of edentation ($51.9\%$), followed by those with complete edentation ($35.2\%$). Only $50\%$ of the edentulous participants underwent prosthetic treatments, $25.9\%$ of them with removable dentures and $24.1\%$ having fixed and removable prostheses. Only $46.3\%$ of the individuals demonstrated adequate masticatory efficiency (Table 1). In Table 2, the distribution of the participants’ answers to the questions of the MMSE questionnaire is presented. The average value of the MMSE score is 21.81 ± 3.872 out of a maximum value of 30. The increased frequency of answers with low scores can be observed in the case of subjects who have teeth not treated with prosthodontic treatment; thus, in the case where the subject had to count backwards from 100 by decreasing by 7, it was observed that $22\%$ of those who did not have prostheses did not have the ability to achieve this, followed by $62\%$ who managed to do this to a small extent. More than half of the non-wearer subjects had reduced ability to recall the names of three previously heard objects as well as to write a phrase with a subject and a predicate (q 5: score 1–$51.9\%$, q 6: score 0–$51.9\%$). Reproducing a drawing was another situation in which $55.6\%$ of the non-wearer subjects encountered difficulties. Differences between groups of wearer/non-wearer subjects were statistically significant for most of the questions in the questionnaire (Table 2). The average value of the MMSE score was 21.81 (SD 3.872) and was associated with edentation treatment ($$p \leq 0.000$$), subjective masticatory efficiency ($$p \leq 0.000$$), and detected comorbidities ($$p \leq 0.000$$). There were no associations between the MMSE and gender distribution, education level, or place of origin (Table 3). Regarding the MMSE forms, depending on the general characteristics, the statistical analysis indicates that female subjects present a higher frequency of moderate MMSE form scores ($35.5\%$), regardless of the level of education, and the mildest MMSE form scores. More subjects with university degrees ($75\%$) and those from the urban environment present more cases of moderate MMSE than those from the rural environment ($34.3\%$). Statistically significant differences were recorded in the case of the edentulous treatment variables, where non-wearer subjects presented more moderate MMSE ($63\%$, $$p \leq 0.000$$), as well as in the case of subjects who declared that they had ineffective mastication ($58.6\%$, $$p \leq 0.000$$) and in the case of those who have comorbidities ($34.1\%$, $$p \leq 0.000$$) (Table 3). Linear regression analysis (Table 4) showed that in the case of the association of the MMSE score and the edentation treatment, the correlation coefficient is positive ($B = 3.986$, $$p \leq 0.004$$), which indicates that individuals with a high MMSE score (close to wave max. 30) have prosthodontic treatment. This relationship is also highlighted in Figure 1, where the regression line is positive and the points are grouped in quadrants I and III, demonstrating a tight, positive, and balanced relationship between the two elements. A negative relationship was detected between the MMSE scores and subjective masticatory efficiency, which indicates that a decrease in the MMSE score is accompanied by a decrease in subjectively evaluated masticatory efficiency in the study participants ($B = 1.513$, $$p \leq 0.268$$) (Table 4, Figure 2). ## 4. Discussions According to recent findings in oral health and geriatric medicine, a new dimension has emerged in the study of significant links between impaired oral function, occlusal/mastication, and specific systemic illnesses such as cognitive and brain functions. Geriatric syndromes, such as memory and cognitive impairments and dementia, can lead to a steady deterioration, which is sometimes accompanied by other comorbidities [34,35]. Cognitive issues are typically more prevalent and disabling in older people as a result of their advanced age. According to the findings of our study, older age was substantially related to the onset of cognitive impairment. This finding was in line with our expectations. It has been widely debated in the literature [36] whether there is a correlation between one’s socioeconomic position and access to dental treatment, and this does appear to be an essential role in cognitive impairment. In our study, likely due to the limited number of subjects, we did not find any link between the patients’ socioeconomic status and cognitive impairment. According to several studies, the existence of natural teeth in humans appears to be linked to higher cognitive performance [37,38]. After conducting a literature review on the relationship between occlusion and human brain function, Okamoto and his colleagues [39] came to the conclusion that “mastication and other movements stimulate activity in the cerebral cortex and could be useful in avoiding degeneration of cognitive ability. It has been hypothesized that rhythmic chewing motions, which enhance blood flow in the brain and stimulate various sections of the cortex, are responsible for this phenomenon and that an increase in blood oxygen levels in the prefrontal cortex, as well as in the hippocampus, may influence learning and memory function [40,41]. Losses in masticatory function, rather than number of teeth, has been found to have a significant effect on cognitive performance [42]. In this context, it is well known that the molars are the teeth that can withstand a greater amount of masticatory power and are the primary determinants of masticatory efficiency [43], and this is true for both natural and artificial occlusion. Therefore, masticatory performance can have a favourable influence on cognitive function [44], regardless of whether it is performed with natural teeth or with prosthetic therapy. The results of our study are similar to those of previous studies in the sense that persons with edentulous arches have reduced masticatory efficiency and low MMSE values. Even more intriguing is the finding that the only significant link between cognitive deterioration and tooth loss was discovered when molars were missing from the mouth after each kind of lost tooth was examined separately. This may be transmitted through the locus coeruleus, which is triggered by a variety of factors including periodontal fibers and proprioceptive jaw muscle spindles [45]. For our study, this could be considered one limitation because we conducted the analysis taking into consideration only the type of edentation and not the type of the remaining teeth. It is undeniable that tooth loss has been associated with the development of memory and cognitive impairment as well as dementia. Evidence suggests that having fewer than 20 teeth increases the likelihood of cognitive impairment and dementia in the elderly [46,47]. The findings of Shimazaki et al. revealed that around $50\%$ of the entirely edentulous and $35\%$ of the partially edentulous who did not wear dentures acquired over time a considerable risk of physical handicap and death [48]. Therefore, preserving as many natural teeth as possible or wearing dentures that are well fitted can be a vital precaution for the oral and physical health of the elderly, especially the more vulnerable population [49]. Greater chewing capacity from more functional tooth units on dental occlusion may lead to extended life expectancy; similarly, a greater selection of nutrients in daily meals is similar to intellectual and social activities for a higher functional quality of life [50]. According to the findings of recent investigations, age-related oral deafferentation and age-related changes in brain activity might result in cross-modal problems, such as loss of the ability to taste and smell food. Because of animal research in which hard food was used as feed, the relationship between oral deafferentation and the neurocognitive and neurogenic brain axis was further established [51]. Consequently, there has been a rise in the belief that dental deafferentation and brain aging are linked, which might lead to new treatments for cognitive decline and neurodegenerative illness in the elderly. In both humans and animals, the reduction in hippocampal brain-derived neurotrophic factor levels is linked to the deterioration of brain and masticatory processes. At the same time, the number of dendritic spines in molar-less mice with the reduced distinction of newly neuronal resulted cells is inhibited, which may be associated with damage in hippocampus-dependent spatial memory, a decrease in the growth and survival of new-born cells in the dentate gyrus, an increase in hippocampal amyloid-beta, and a deterioration of norepinephrine neurons in the locus coeruleus [51]. Despite the fact that our brain is in a permanent state of flux, new connections are always being formed, which might result in the acquisition of new abilities or adjustment to a new oral environment. More research is needed to determine if the concept of “neuroplasticity” is correct. Studies have also demonstrated the distinctive and reversible neuroplasticity of corticomotor excitability in the context of controlling peri-oral tongue muscles during movements. Two weeks following tongue training, it has been demonstrated that the plastic alterations returned to baseline levels. A study by Kumar et al. found that in their study group, denture users’ cerebral activity returned to baseline levels three months following the placement of new dentures, which was similar to the results of previous research. This is a return to the starting point [51]. It is possible that cortical modifications were more “elastic” (i.e., reversible) than “plastic” once the training was discontinued, giving the appearance that the changes were more permanent (i.e., irreversible). The correlation between tooth loss and decreased cognitive performance is supported by the findings of this study. As a result, it is likely that by increasing the efforts that are committed to preventing tooth loss in the adult population it will be possible to achieve the desired results. It is important to note that this evaluation does have certain limitations. As a result of the small sample size, we were unable to obtain reliable estimations of the parameters governing the study’s validity. We also acknowledge that our participants were sampled from one area of the city of Iasi, which may raise questions regarding the generalizability of our results; a future population study could me more randomized, apart from age and presence/absence of teeth. ## 5. Conclusions and Perspectives These findings further highlight the positive impact of periodontal medicine and preserving natural teeth on memory. Beyond the financial repercussions, the true cost of cognitive decline, if we define it as memory impairment as well as personal experiences and relationships, is unquantifiable. As a future perspective for this pilot study, one might convene a multicenter study group, representative for at least a region of Romania and presenting a possible corelation between patients’ cognitive state of mind, prosthetic condition, and quality of life. 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--- title: Analysis of MIR27A (rs11671784) Variant Association with Systemic Lupus Erythematous authors: - Zenat Ahmed Khired - Shahad W. Kattan - Ahmad Khuzaim Alzahrani - Ahmad J. Milebary - Mohammad H. Hussein - Safaa Y. Qusti - Eida M. Alshammari - Eman A. Toraih - Manal S. Fawzy journal: Life year: 2023 pmcid: PMC10058767 doi: 10.3390/life13030701 license: CC BY 4.0 --- # Analysis of MIR27A (rs11671784) Variant Association with Systemic Lupus Erythematous ## Abstract Multiple microRNAs (miRs) are associated with systemic autoimmune disease susceptibility/phenotype, including systemic lupus erythematosus (SLE). With this work, we aimed to unravel the association of the miR-27a gene (MIR27A) rs11671784G/A variant with SLE risk/severity. One-hundred sixty-three adult patients with SLE and matched controls were included. A TaqMan allelic discrimination assay was applied for MIR27A genotyping. Logistic regression models were run to test the association with SLE susceptibility/risk. Genotyping of 326 participants revealed that the heterozygote form was the most common genotype among the study cohort, accounting for $72\%$ of the population ($$n = 234$$), while A/A and G/G represented $15\%$ ($$n = 49$$) and $13\%$ ($$n = 43$$), respectively. Similarly, the most prevalent genotype among cases was the A/G genotype, which was present in approximately $93.3\%$ of cases ($$n = 152$$). In contrast, only eight and three patients had A/A and G/G genotypes, respectively. The MIR27A rs11671784 variant conferred protection against the development of SLE in several genetic models, including heterozygous (G/A vs. A/A; OR = 0.10, $95\%$ CI = 0.05–0.23), dominant (G/A + G/G vs. AA; OR = 0.15, $95\%$ CI = 0.07–0.34), and overdominant (G/A vs. A/A + G/G; OR = 0.07, $95\%$ CI = 0.04–0.14) models. However, the G/G genotype was associated with increased SLE risk in the recessive model (G/G vs. A/A+ G/G; OR = 17.34, $95\%$ CI = 5.24–57.38). Furthermore, the variant showed significant associations with musculoskeletal and mucocutaneous manifestations in the patient cohort ($$p \leq 0.035$$ and 0.009, respectively) and platelet and white blood cell counts ($$p \leq 0.034$$ and 0.049, respectively). In conclusion, the MIR27A rs11671784 variant showed a potentially significant association with SLE susceptibility/risk in the studied population. Larger-scale studies on multiethnic populations are recommended to verify the results. ## 1. Introduction Systemic lupus erythematosus (SLE; OMIM 152700) is a prototypic autoimmune complex disease that is characterized by excessive production of autoantibodies against a broad range of self-antigens [1,2]. Vital organs and tissues are often affected, including the kidney, brain, cardiovascular system, joints, and skin [3]. The pathogenesis of SLE is complex, with evidence of genetic/epigenetic–environment interplay shaping the clinical variability of such a disorder [4,5]. Unraveling the disease susceptibility and phenotype-associated genetic markers is a crucial step toward precision medicine in SLE [6]. MicroRNAs (miRNAs) are a family of noncoding RNAs (ncRNAs) transcribed by RNA polymerase II into primary transcripts (pri-miRNAs) that are then cleaved to form hairpin precursor miRNAs (pre-miRNAs) of 70–100 nucleotides, with the aid of Drosha [7]. These hairpins subsequently undergo further processing by the endonuclease enzyme Dicer, yielding a duplex of 19–22 nt. One strand of the duplex is integrated into the RNA-induced silencing complex and delivers mature miRNAs to the respective mRNA targets [8]. By mediating mRNA degradation and/or translation inhibition through canonical and non-canonical mechanisms, miRNAs play central roles in gene regulation [7]. One of the essential characteristics of miRNAs is their export and migration from their host cells, where they are transcribed/processed into several body fluids, including the blood (circulating miRNAs) in highly stable forms due to their inclusion in the exosomes and/or interaction with several circulating proteins, such as argonaute 2 and nucleophosmin 1, and high-density lipoproteins that protect them from degradations by RNases [9]. This class of ncRNAs, as regulators of post-transcriptional gene expression, has been implicated in several physiological process and pathological disorders, including SLE [10,11,12,13,14,15,16,17,18,19,20,21,22]. MicroRNA-27a (miR-27a) has been identified to be highly conserved throughout vertebrate genomes during evolution (Figure 1) and is considered a member of the miRNA-23∼27∼24 cluster, with several essential biological roles [23,24]. Accumulating evidence indicates miR-27a implication in the pathogenesis of SLE, which can be identified as a potential biomarker for SLE due to its ability to regulate the expression of genes associated with disease phenotypes [25,26,27,28]. Guttilla and colleagues reported that miR-27a, along with miR-96/miR-182, downregulated the transcriptional factor “FOXO-1”, which regulates genes implicated in apoptotic response, cell metabolism, and cell cycle checkpoints [29]. Interestingly, FOXO-1 transcript levels were downregulated in the peripheral blood mononuclear cells (PBMCs) of SLE patients with active disease and were inversely correlated with lupus disease activity [30]. Furthermore, Tardif et al. observed that miR-27a could indirectly downregulate the “matrix metalloprotease-13 (MMP-13) and the insulin-like growth factor binding protein (IGFBP)”, two genes implicated in osteoarthritis [31]. In an independent study, Lin and colleagues reported that miR-27a could block PPARγ transcriptional induction [32]. This factor has been implicated in the etiopathology of several diseases [25], including SLE, as upregulated PPAR-γ was found to modulate monocytes into an M2-like phenotype in patients with SLE [33]. Collectively, it appears that miR-27a could play essential roles in SLE pathology and phenotype and be a novel therapeutic target. Regarding dysregulated levels of miR-27a in SLE, Sourour et al. revealed the upregulation of miR-27a* (the passenger strand) in PBMCs and natural killer (NK)-cell subsets collected from patients with SLE relative to healthy subjects [26]. They found that forced expression of miR-27a* through gain/loss-of-function experiments could impact the expression of “NKG2D”, an activating receptor of NK cells, in SLE patients. Additionally, a significant negative correlation was found between miR-27a* expression in PBMCs of SLE patients and disease activity index (SLEDAI) scores, implying that this type of microRNA could be involved in SLE pathogenesis [26]. By screening B-cell-related miRNAs in the plasma of SLE patients using a customized qRT-PCR miRNA array, Zhang and colleagues demonstrated the diagnostic value of the differential expression of miR-27a with 13 other dysregulated miRNAs in discriminating SLE patients from healthy controls. Furthermore, they found that miR-27a had an area under curve = 0.873, with diagnostic sensitivity = 0.867 and specificity = 0.773 to distinguish SLE patients from patients with rheumatoid arthritis [34]. These findings further support the possibly essential role of miR-27a in the etiopathology of SLE. The human MiR-27a gene (MIR27A; Gene ID: 407018) is located along the short arm of chromosome 19 (Ch:19p13.12), spanning 78 base pairs (bp) (genomic coordinates at 19:13,836,440–13,836,517) on the reverse strand within the “miRNA-23∼27∼24 cluster”, according to the “Human Genome Assembly; GRCh38.p14” (https://www.ncbi.nlm.nih.gov/gene/407018) (accessed 15 December 2022) (Figure 2A). This gene is transcribed into a single 78 bp microRNA 27a (Figure 2B) and has been found predominantly intracellularly in the nucleus and extracellularly in the circulating exosomes and vesicles (Figure 2C). According to the human microRNA disease associations database (HMDD v3.0) (http://www.cuilab.cn/hmdd) (last accessed 20 December 2022), this microRNA can bind and downregulate several target genes, such as “tumor protein p53 (TP53), Cytochrome P450 Family 1 Subfamily B Member 1 (CYP1B1), Adenomatosis Polyposis Coli (APC), Engrailed Homeobox 2 (EN2), GATA Binding Protein 3 (GATA3), SMAD Family Member 4 (SMAD4), Prohibitin 1 (PHB), Low Density Lipoprotein Receptor (LDLR), Nuclear Receptor Binding SET Domain Protein 1 (NSD1), Dihydropyrimidine Dehydrogenase (DPYD), Thioredoxin Interacting Protein (TXNIP), Translocase Of Inner Mitochondrial Membrane 10 (TIMM10), F-Box And WD Repeat Domain Containing 7 (FBXW7), Insulin Like Growth Factor 1 (IGF1), Neuroblastoma RAS Viral Oncogene Homolog GTPase (NRAS), ALF Transcription Elongation Factor 4 (AFF4), Zinc Finger And BTB Domain Containing 20 (ZBTB20), Phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit Gamma (PIK3CG), Peroxisome Proliferator Activated Receptor Alpha and gamma (PPARA/G), Cyclin D1 (CCND1), Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS), Leukemia Inhibitory Factor Receptor (LIFR), Neurofibromin 1 (NF1), Budding Uninhibited By Benzimidazoles 3, Yeast-Homolog Mitotic Checkpoint Protein (BUB3), Homeobox D11 (HOXD11), Epidermal Growth Factor Receptor (EGFR), ATPase Copper Transporting Beta (ATP7B), ATP Synthase Mitochondrial F1 Complex Assembly Factor 1 (ATPAF1), Solute Carrier Family 6 Member 8 (SLC6A8), Enhancer Of Zeste 2 Polycomb Repressive Complex 2 Subunit (EZH2), and Thioredoxin Domain Containing 5 (TXNDC5)” (Figure 2E). Many of these target genes have been implicated in several immune-related process and disorders [27,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54]. Single-nucleotide polymorphisms (SNPs) within miRNA genes were previously reported to be associated with susceptibility to several diseases, including autoimmune disorders [55,56,57], and can alter the expression and/or maturation of miRNA and ultimately affect its functioning [58,59,60,61]. The MIR27A rs11671784G>A variant has been identified and studied for its potential role in various diseases and cancers [62,63,64]. For example, carriers of rs11671784 A have significantly reduced gastric cancer risk and lymphatic invasion [64,65], and the “G allele” has been reported to have a more substantial impact than the A allele in promoting bladder cancer chemosensitivity [66]. Furthermore, this SNP was significantly associated with “age-related macular degeneration” [62]. However, no studies have explored the association between this variant and SLE. Therefore, we designed the present study to test the association of the rs11671784 variant with SLE susceptibility and/or phenotype. ## 2.1. Study Participants A total of 163 adult SLE patients and 163 unrelated age- and sex-matched controls were enrolled in this study. Patients were recruited from the Rheumatology outpatient clinics of Suez Canal University Hospitals, Ismailia. They were diagnosed and assessed according to the “European League Against Rheumatism/American College of Rheumatology” diagnostic criteria for SLE [67]. A thorough review of their clinical assessment sheets was performed to determine disease severity, therapeutic history, and comorbidities. Patients with a history of other autoimmune disorders (e.g., rheumatoid arthritis, alopecia areata, vitiligo, psoriasis, multiple sclerosis, myasthenia gravis, and inflammatory bowel disease) or chronic diseases (e.g., endocrine disorders or malignancies), or a history of long-term treatment were excluded. Laboratory data, including quantification of proteinuria in 24 h, serum creatinine and blood urea levels, type and titer of antinuclear antibodies (ANA-anti DNA), and serum complement levels (C3 and C4), were collected at the time of consent. Controls should have no history of autoimmune diseases or chronic disorders. Renal involvement was defined as an increase in proteinuria (>150 mg/24 h), an increase in serum creatinine (>1.4 mg/dL), or both [67]. The “SLE Disease Activity Index (SLEDAI) score” was used to classify patients according to disease activity into (a) score = 0, i.e., no activity; (b) score = 1:5, i.e., mild activity; (c) score = 6:10, i.e., moderate activity; (d) score = 11:19, i.e., high activity; or (E) score ≥ 20, i.e., very high activity [68]. The study was conducted in accordance with the guidelines of the Declaration of Helsinki, and written informed consent was obtained from participants before taking part. ## 2.2. MIR27A rs11671784G>A Genotyping Five milliliters of blood was collected from each participant in an EDTA tube for hematological and molecular studies and in a plain tube for immune and biochemical studies, as detailed previously [61]. DNA was extracted from whole blood using a QIAamp DNA extraction mini kit (Cat no. 51104; Qiagen, Hilden, Germany) and assessed for concentration/purity by a “NanoDrop ND-1000 spectrophotometer” (NanoDrop Technologies, Wilmington, DE, USA). Genotyping was carried out using real-time polymerase chain reaction allelic discrimination technology on a StepOne real-time system (Applied Biosystems, Waltham, MA, USA). The applied protocol was followed blindly, regardless of the case/control status of the samples, with a final volume of 20 μL, including (a) genomic DNA (20 ng); (b) a TaqMan SNP genotyping assay mix (1 μL of the assay ID: C_176018176_10; Cat no. 4351379, Applied Biosystems, Waltham, MA, USA) to detect the transition substitution of the studied variant in the following context sequence: “GCCACTGTGAACACGACTTGGTGTG[G/A] ACCCTGCTCACAAGCAGCTAAGCCC” in which VIC/FAM-labeled probes specify the “G” and “A” alleles, respectively; (c) a TaqMan Universal PCR master mix (10 μL); and (d) nuclease-free water. Negative controls were applied in each run. The program was set at 10 min for an initial hold (95 °C), followed by a 40-cycle, two-step 15 s denaturation (95 °C) and 1 min annealing/extension (60 °C). “ SDS software version 1.3.1” (Applied Biosystems, Waltham, MA, USA) was applied for allelic discrimination calling [2,69]. About $10\%$ of the total samples were regenotyped as technical replicates, which yielded a $100\%$ recall rate. ## 2.3. Statistical Analysis General statistical analyses were performed with Statistical Package for Social Science (SPSS) software version 23 (IBM SPSS Statistics for Windows, Version 27.0. Armonk, NY, USA: IBM Corp). Categorical variables were compared using chi-square or Fisher’s exact tests. Student’s t-tests, Mann–Whitney U (MW), and Kruskal–Wallis (KW) tests were used to compare continuous variables according to data distribution/variance homogeneity, which were checked by the Shapiro–Wilk test and Levene test, respectively, to compare continuous variables. Data were expressed as mean ± standard deviation (SD). SNPstats software (version 1.24.0) was applied for genotype/allele frequency estimation as previously described [70]. Hardy–Weinberg equilibrium (HWE) testing was checked. Logistic regression analysis was applied, and adjustment for confounding parameters was considered. A two-tailed p-value less than 0.05 was considered statistically significant. ## 3.1. Patient Characteristics This study included 163 SLE patients (147 females and 16 males) and 163 age- and sex-matched controls (148 females and 15 males). The mean age of participants was 35.6 ± 9.6 years for patients and 35.8 ± 9.9 years for controls. Fifty-eight ($35.6\%$) cases had a positive family history of SLE. The median SLEDAI score for patients was 3.0 (IQR = 0.0–6.0). Almost all patients presented with neurological symptoms, and $76.7\%$ of the cohort had renal involvement (Figure 3). Laboratory data of patients with SLE are summarized in Supplementary Materials Table S1. ## 3.2. Allelic Discrimination Analysis In the study population ($$n = 326$$), the minor allele frequency (G allele) was $49\%$ ($$n = 320$$). The heterozygote form was the most common genotype among the cohort, accounting for $72\%$ of the population ($$n = 234$$), while A/A and G/G represented $15\%$ ($$n = 49$$) and $13\%$ ($$n = 43$$), respectively (Figure 4A). Similarly, the most prevalent genotype among cases was the G/A genotype, which was present in approximately $93.3\%$ of cases ($$n = 152$$). In contrast, only eight and three patients had A/A and G/G genotypes, respectively. Compared with controls, the homozygote genotypes were significantly higher (A/A: $25.2\%$ vs. $4.9\%$ and G/G: $24.5\%$ vs. $1.8\%$) in patients with SLE. In contrast, the G/A genotype of MIR27A polymorphism was less prevalent in cases ($50.3\%$ vs. $93.3\%$, $p \leq 0.001$) (Figure 4B). The MIR27A rs11671784 variant conferred protection against the development of SLE in several genetic models, including heterozygous (G/A vs. A/A; OR = 0.10, $95\%$ CI = 0.05–0.23), dominant (G/A + G/G vs. AA; OR = 0.15, $95\%$ CI = 0.07–0.34), and overdominant (G/A vs. A/A + G/G; OR = 0.07, $95\%$ CI = 0.04–0.14) models. However, the G/G genotype was associated with increased SLE risk in the recessive model (G/G vs. A/A+ G/G; OR = 17.34, $95\%$ CI = 5.24–57.38) (Table 1). ## 3.3. MIR27A rs11671784G/A Variant Association with Clinicolaboratory Data Figure 5 indicates that the MIR27A rs11671784 variant is associated with musculoskeletal and mucocutaneous manifestations in patients with SLE ($$p \leq 0.035$$ and 0.009, respectively). It also shows an association with platelet and white blood cell counts ($$p \leq 0.034$$ and 0.049, respectively) (Figure 6). Otherwise, this variant does not show significant associations with other clinical and laboratory characteristics of the patients. ## 3.4. Multivariate Regression Analysis Multivariate analysis failed to define independent predictor risk factors for the severe disease phenotype of the studied cohort with SLE, as indicated by the confidence intervals crossing the vertical line of 1 in Figure 7. ## 3.5. MIR27A Implication in SLE Etiopathology Figure 8 and Table S2 show the experimentally validated gene targets of miR-27a-5p in the SLE Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway (hsa05322), which include several histone variants (e.g., H3F3B) that are involved in the autoantigen clearance/tolerance mechanism, the “major histocompatibility complex class II (MHCII)”, and the “HLA class II histocompatibility antigen-DO alpha chain (HLA-DOA)”, which are implicated in antigen presentation, RNA-binding proteins (e.g., TROVE2 and SNRPB), glutamate ionotropic receptor NMDA type subunit 2A/B (GRIN2A/B), cytokines (i.e., IL10), and cluster of differentiation 28 (CD28) [71,72,73]. KEGG pathway enrichment analysis for MIR27A showed significant implications of its targets in extracellular matrix–receptor interaction, Hippo signaling, and transforming growth factor-beta signaling pathways (Figure 9). ## 4. Discussion Recent evidence suggests that miRNA variants are associated with susceptibility to several autoimmune diseases, including SLE [74]. For example, the “rs3746444” variant of miR-499 has been associated with an increased risk of SLE [75], rheumatoid arthritis [76], and other autoimmune diseases [77,78]. The miR-146a “rs57095329” variant was associated with increased SLE risk in East Asian regions [74,79,80]. The miR-149 rs2292832 polymorphism may confer susceptibility to Kawasaki disease [81], allergic rhinitis, and comorbid asthma in Chinese children [82]. The association of the miRNA-34a rs2666433 variant with SLE susceptibility and the miR-17 rs4284505 variant with susceptibility and severity of SLE were also evident in the present cohort [2,61]. These SNPs can impact biogenesis and/or dysregulate miRNAs, with a subsequent influence on immune development/differentiation or response, leading to loss of immune tolerance and autoimmunity [83,84]. The role of miR-27a in SLE has been studied extensively in recent years. Studies have shown that circulating plasma miR-27a is dysregulated in SLE patients compared to healthy controls, with an area under the curve (AUC) = 0.948, diagnostic sensitivity = 0.818, and specificity = 1.000 [34]. Furthermore, miR-27a is involved in the regulation of genes associated with SLE, such as interferon (IFN)-γ [85], interleukin (IL)-10 [86], and transforming growth factor (TGF)-β [87,88], among others. MiR-27a regulates these genes by binding to their 3′UTR and inhibiting their expression. The role of miR-27a in SLE has been further investigated in the peripheral blood mononuclear cells and natural killer cells of patients with SLE compared to controls [26]. In this latter study, the authors identified aberrant expression of miR27a in the isolated cells and found that forcing miR27a expression enhances NKG2D (natural killer activating cell receptor) mRNA expression and could have a role in SLE etiopathology. Our in silico analysis confirmed the implication of miR-27a in the SLE pathway by targeting several genes coding for variable histone family proteins, RNA-binding proteins, and several immune-response-related proteins, such as HLA class II histocompatibility antigen and CD28, which can modulate antigen processing and presentation by immune cells, autoantigen production, and the clearance mechanism, as depicted in Figure 8. Furthermore, enrichment analysis of miR-27a target genes shows significant involvement of miR-27a in potential pathways that may play a role in SLE etiopathology, such as extracellular matrix–receptor interaction [89], Hippo signaling [90], and transforming growth factor-beta signaling pathways [91]. In addition to its role in SLE, miR-27a has also been found to be involved in other autoimmune diseases, such as rheumatoid arthritis [92] and systemic sclerosis [93]. In a placebo-controlled trial, it was shown that miR-27a is a potential biomarker for the favorable response to methotrexate/disease-modifying antirheumatic drug combination therapy in patients with rheumatoid arthritis [94]. In the present study, we found that the homozygous A/A and G/G genotypes of the MIR27A variant are more common in individuals with SLE than in healthy individuals and that the G/G genotype was associated with an increased risk of developing SLE in the recessive model. In contrast, the G/A genotype revealed a protective effect against the development of SLE. The exact mechanism by which the MIR27A polymorphism could be associated with the risk of developing SLE is not yet known, but it can be speculated to affect the expression level of mature microRNA, which can impact the target genes involved in the immune system. By running the HaploReg v3 tool (https://pubs.broadinstitute.org/mammals/haploreg/haploreg_v3.phpto) (last accessed on 20 December 2022) [95] to predict the effect of the studied variant, we found that this SNP can disrupt the Brachyury (a T-box transcription factor T) and Eomes (a T-box transcription factor), as well as HNF4 (Hepatocyte Nuclear Factor 4), DNA motifs. Brachyury is involved in transcription repression by RNA polymerase II (https://www.ncbi.nlm.nih.gov/gene/20997) is a generated (last accessed 20 December 2022), and Eomes is implicated in CD8 T-cell/natural killer cell differentiation [96] and plays a substantial role in regulating cytotoxic function/development and survival of immune cells [97]. Previous evidence also explained the role of the MIR27A rs11671784 variant in other diseases by influencing the miR-27a maturation and/or expression levels. For example, Katayama et al. reported that this variant can downregulate mature miR-27a with subsequent increased expression of its target genes in bladder cancer cells [66]. Others suggested that it can impact the processing efficiency of miR-27a [98]. Interestingly, Strafella and colleagues computed the minimum free energy (MFE) of a miR-27a hairpin structure, including the variant A allele, which generated a secondary structure with an “MFE = −38.76 Kcal/mol”, whereas the structure with the G allele showed an “MFE = −38.24 Kcal/mol” [62]. They concluded that the rs11671784 polymorphism located in the terminal loop of the pre-miR27a might influence the expression levels of mature miR-27a without substantially, impairing its processing and binding affinity with target mRNAs [62]. All these findings support the significant association of the studied variant with SLE susceptibility/development reported in the present study. Further mechanistic research is needed to understand the precise implications of this polymorphism for SLE. Although the studied variant did not show significant associations with most clinicolaboratory characteristics of the patients, it was associated with musculoskeletal and mucocutaneous manifestations and showed borderline associations with platelet and white blood cell counts. Interestingly, miRNA 27a has been found to play a vital role in osteogenesis, and its expression is downregulated upon osteogenic differentiation [99]. The latter investigators revealed that grancalcin, “a regulator of osteogenesis” in human mesenchymal stem cells, is a target of miR-27a. Furthermore, the reported impact of miR-27a on the overall regulation of “matrix metalloprotease-13” and “insulin-like growth factor binding protein”, two genes involved in osteoarthritis pathophysiology and some skin disorders [25,27,28,31,100,101], could partially support the association of this variant with the identified clinical manifestations in the present SLE cohort. Additionally, miR-27a has been found to attenuate the expression of a critical regulator of hematopoiesis, the “RUNX1 transcription factor”, in K562 cells, which could impact megakaryopoiesis and differentiation [102]. This could partly explain the association of the studied variant with the hematological findings reported in the present study. It is worth noting that besides the studied MIR27A rs11671784 variant, several genetic/epigenetic and environmental factors also participate in SLE susceptibility. Furthermore, the relatively small sample size, the cross-sectional analysis of hospital-based selected cohorts, and the lack of experimental studies to elucidate how this variant might impact the disease could all limit this work. In this sense, large-scale longitudinal studies on multiethnic populations supported with functional analyses are recommended. ## 5. Conclusions We are the first to provide evidence that the MIR27a rs11671784 genetic variant could be associated with SLE susceptibility/risk in the studied population. The homozygous A/A and G/G genotypes of the miR-27a variant were more common in patients with SLE than in healthy individuals, and the G/G genotype was associated with increased SLE risk in the recessive model. Nevertheless, the studied variant did not show significant associations with most clinical and laboratory characteristics of the patients, although there was a significant association with musculoskeletal and mucocutaneous manifestations. 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--- title: 'Nutritional Status among Portuguese and Turkish Older Adults Living in the Community: Relationships with Sociodemographic, Health and Anthropometric Characteristics' authors: - Meryem Elif Öztürk - Rui Poínhos - Cláudia Afonso - Nurcan Yabancı Ayhan - Maria Daniel Vaz de Almeida - Bruno M. P. M. Oliveira journal: Nutrients year: 2023 pmcid: PMC10058781 doi: 10.3390/nu15061333 license: CC BY 4.0 --- # Nutritional Status among Portuguese and Turkish Older Adults Living in the Community: Relationships with Sociodemographic, Health and Anthropometric Characteristics ## Abstract Malnutrition is widespread among older adults, and its determinants may differ between countries. We compared Portuguese and Turkish non-institutionalized older adults regarding nutritional status, sociodemographic, health and anthropometric characteristics and studied the relationships between nutritional status and those characteristics. This cross-sectional study analyzed data from 430 Portuguese and 162 Turkish non-institutionalized older adults regarding sociodemographics, health conditions, the Mini-Nutritional Assessment (MNA-FF) and anthropometry. Turkish older adults were more likely to be malnourished or at risk of malnutrition and had lower average BMI but a higher calf circumference. A higher proportion of the Portuguese sample had tooth loss, diabetes, hypertension, oncologic diseases, kidney diseases, osteoarticular problems or eye problems, while less had anemia. A better nutritional status (higher MNA-FF score) was found among the Portuguese, males, people using dentures, those without tooth loss, hypertension, cardiovascular diseases, anemia or oncological diseases and was related to younger age, higher BMI and a higher calf circumference. Malnutrition and its risk were higher among older adults from Turkey, despite Portuguese older adults presenting a higher prevalence of chronic diseases. Being female, older age, tooth loss, hypertension, anemia, CVD or oncological disorders and having a lower BMI or CC were associated with higher rates of malnutrition among older adults from Portugal and Turkey. ## 1. Introduction The older adult population (≥65 years) is increasing all over the world. Therefore, health measures for older adults are becoming more important, with poor nutritional status and malnutrition being major issues of concern. Malnutrition and unintentional weight loss contribute to a progressive decline in health, reduced physical and cognitive functional status, increased utilization of health care services and increased mortality. Despite that, clinicians and care givers are usually unaware of patients’ nutritional problems. Although malnutrition is widespread among geriatric patients, its diagnosis is usually underestimated; therefore, many do not receive appropriate treatment [1,2]. Malnutrition can be assessed using several tools. In this work, we used the Mini-Nutritional Assessment (MNA). The full form of the MNA (MNA-FF) was developed by Guigoz et al. [ 1994] to screen and assess malnutrition and its risk among older adults [3]. This instrument comprises 18 items that cover information regarding appetite or eating problems, recent weight loss, mobility impairment, acute illness/stress, dementia or depression, body mass index (BMI), living independently, the number of prescription drugs, pressure sores/skin ulcers, consumption of full meals, protein intake, fruit and vegetable intake, fluid intake, mode of feeding, self-perception of nutritional status, self-perception of own health status, mid-upper arm circumference (MUAC) and calf circumference (CC). The short form of the MNA (MNA-SF) considers only a subset of six questions from the MNA-FF, being frequently used as a screening tool [4,5]. The population of older adults differs between countries. These differences regard not only the proportion of older adults but also their characteristics, namely regarding malnutrition. Turkey and Portugal are an example, as they differ regarding socioeconomic and cultural features and present very different population characteristics of older adults. In Turkey, in 2017, older adults comprised $8.5\%$ of the population [6], while they corresponded to $19.1\%$ of the Portuguese population in 2011 [7]. With respect to nutritional status, a multicenter study in Turkey reported that, according to the MNA, $19.0\%$ of community-dwelling older adults had malnutrition, and $29.1\%$ were at risk of being malnourished [8]. In Portugal, also using the MNA, it was found that $1.3\%$ of older adults were malnourished and $14.7\%$ were at risk [9]. The cultural and socioeconomic differences between these two countries may lead to different determinants of the nutritional status. This has implications when tailoring public health interventions, namely when deciding which subgroups of older adults should be the focus of such interventions and when deciding on the applicability of the models and results of research carried out in different countries. In order to better understand these differences and improve the quality of life of older adults, we conducted this study to compare Portuguese and Turkish non-institutionalized older adults regarding their nutritional status, sociodemographic, health and anthropometric characteristics and to study the relationships between nutritional status and sociodemographic, health and anthropometric characteristics. ## 2. Methods The data used in this work were collected in 2015 (Turkey) and 2016 (Portugal) within two cross-sectional studies: the PRONUTRISENIOR project in Portugal and an older adult cross-sectional study in Turkey. The PRONUTRISENIOR project took place at the Family Health Unit (FHU) “Nova Via”, a primary care health center in Vila Nova de Gaia included in ACES Espinho-Gaia (Porto Metropolitan Area, Portugal) covering a heterogeneous population of older adults living in rural, semi-urban, urban, coastal and inland environments with different educational levels and socioeconomic status. Further details on this project are available elsewhere [10]. The Turkish sample was gathered from cross-sectional research conducted in both rural and urban areas of Ankara (capital city of Turkey), which included both community-dwelling and nursing home older adults, but only data from community-dwelling older adults were used in this study. The inclusion criteria for both convenience samples were being at least 65 years old and being community-dwelling, i.e., non-institutionalized. The presence of dependency conditions (namely cognitive impairment) that could constrain free and informed decision-making regarding participation was used as an exclusion criterion. Potential participants were contacted by phone or at the health care center. The acceptance to participate was given through signed informed consent. The study was approved by the Regional Administration of Health (approval number $\frac{2}{2016}$) and was carried out in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki). Data were gathered using standard procedures by trained nutritionists and undergraduate nutrition students during their internship period via face-to-face interviews. Data collection took place at the primary health care centers attended by the participants or at their homes, according to their preference, and completed by phone. In order to allow future comparisons with the results from different studies, both the MNA-SF and MNA-FF were used in the analysis. The MNA-SF includes six items: A—appetite or eating problems; B—recent weight loss; C—mobility impairment; D—acute illness/stress; E—dementia or depression and F—body mass index (BMI). The MNA-FF comprises these six items, plus: G—living independently; H—number of prescription drugs; I—pressure sores/skin ulcers; J—consumption of full meals; K—protein intake; L—fruit and vegetable intake; M—fluid intake; N—mode of feeding; O—self-perception of nutritional status; P—self-perception of own health status; Q—mid-upper arm circumference (MUAC) and R—calf circumference (CC) [4,5]. A better nutritional status corresponds to the absence of health problems (items A to E and I); higher anthropometric measurements (F, Q and R); living independently (G); lower number of prescription drugs (H); higher consumption or intake (J to M); oral feeding (N) and better perception of their own nutritional and health status (O and P). Items G, H, I, K, L, M, Q and R are scored 0 to 1; items A, C, D, E, J, N, O and P are scored 0 to 2 and items B and F are scored 0 to 3. The total scores correspond to the sum of the scores of the individual items (A to F for MNA-SF and A to R for the MNA-FF). For both forms, higher scores correspond to a better nutritional status. The MNA-FF score is categorized into malnourished (<17 points), risk of malnutrition (17 to 23.5) or normal nutritional status (24 to 30) [3]. The categories of the MNA-SF are similar: malnutrition (0 to 7 points), malnutrition risk (8 to 11) or normal nutritional status (12 to 14) [5]. In addition to completing the MNA-FF, all subjects in both surveys answered sociodemographic questions, which included sex, age, education level, household composition, marital status and professional situation. Health-related data were self-reported using a list of diseases and health conditions from which the participant should identify the ones with which they had been diagnosed. Anthropometric measurements were made following the standard methods [11,12,13,14,15] and included: weight, height, mid-upper arm circumference (MUAC), calf circumference (CC) and the computation of the body mass index (BMI). The statistical analysis was performed using SPSS 22.0 for Windows. Descriptive statistics included the means and standard deviations for quantitative variables and relative (%) and absolute (n) frequencies for categorical variables. We applied Pearson’s chi-square tests to evaluate the independence between pairs of nominal variables and Student’s t-tests or Mann–Whitney’s U tests to compare, respectively, means and mean ranks between pairs of independent samples. We performed an ANCOVA with the MNA-FF score as the dependent variable and the sociodemographic, anthropometric and health characteristics as independent variables. The initial model considered the following factors and covariables: country; sex; education level; marital status; professional situation; household composition; tooth loss; using dentures; having diabetes mellitus, hypertension, cardiovascular diseases, kidney diseases or osteoarticular diseases; age; BMI; MUAC and CC. Using a backward method, in each step, we removed the variable that had the least significant effect. We present the last step of this procedure, which includes only the significant relationships between each independent variable and the MNA-FF score, adjusted for the remaining variables included in that step. This analysis was sufficiently powered ($80\%$) to detect an effect size (partial eta-squared; ηp2) of 0.013 or larger. Furthermore, we related each individual item of the MNA-FF with the sociodemographic, anthropometric and health variables using Spearman’s correlation coefficients and Mann–Whitney U tests. Variables with significantly higher (or lower) scores will be indicated with a (+) or (−) sign. In this analysis, we applied Bonferroni’s correction for multiple comparisons. All relationships were considered significant if $p \leq 0.05.$ ## 3.1. Sample Characterization and Comparison between Countries In this study, we included a total of 592 older adults: $72.6\%$ ($$n = 430$$) from Portuguese and $27.4\%$ ($$n = 162$$) from Turkey. From the initial samples of 171 Turkish and 459 Portuguese participants, 9 cases were excluded from the Turkish sample and 29 from the Portuguese sample due to missing data. Table 1 presents and compares the Portuguese and Turkish samples regarding sociodemographic characteristics. We observed that Turkish older adults were more likely to have completed secondary school or to be illiterate, while Portuguese participants had mostly completed primary school. The Turkish sample had a higher proportion of participants living with children, who were a widow/widower and who were housewives/househusbands. Portuguese older adults had a higher probability of having tooth loss, diabetes, hypertension, oncologic diseases, kidney diseases, osteoarticular problems or eye problems, while there was a higher frequency of anemia among Turkish participants. The mean BMI was smaller in the Turkish sample, while the mean calf circumference was larger when compared with the Portuguese sample (Table 2). Regarding nutritional status, Turkish participants were more likely to be malnourished or at risk of malnutrition, both according to the MNA-SF and to the MNA-FF. However, the mean MNA score was significantly higher among Portuguese participants only for the MNA-SF (Table 3). ## 3.2. Relationships of Sociodemographic, Clinical and Anthropometric Characteristics with MNA-FF Scores The final model of the ANCOVA is presented in Table 4. We observe that, on average, the MNA-FF score is higher among the Portuguese; males; participants using dentures and those without tooth loss, hypertension, cardiovascular diseases (CVD), anemia or oncological diseases and participants with younger ages, a higher BMI and higher CC. We note that the effect sizes (ηp2) were larger for CVD and sex. ## 3.3. Relationships of Sociodemographic, Clinical and Anthropometric Characteristics with MNA-FF Items Table 5 shows the relationships between each question that composes the MNA-FF and sociodemographic, health and anthropometric variables. Each reference category was chosen to match the one with the higher adjusted mean in the ANCOVA model. Most of the significant associations were in the same direction as those with the MNA-FF score in the ANCOVA model and are marked with a (+) sign. However, we also found some relationships in the opposite direction, marked with a (−) sign: older adults with higher BMI (question F) were more likely to have hypertension; those who took three or more prescription drugs (question H) were more likely to be Portuguese or to have higher BMI; those who took less full meals (question J) were more likely to be Portuguese, to have hypertension or to have higher BMI; Portuguese participants drank less fluids (question M) and regarding the perception of their health status (question P), Portuguese older adults felt worse. ## 4. Discussion The main aims of this study were to compare Portuguese and Turkish non-institutionalized older adults regarding their nutritional status and to study its relationships with sociodemographic, health and anthropometric characteristics. We also compared the Portuguese and Turkish samples regarding their health and anthropometric characteristics, and, in order to better interpret those results, we analyzed the socioeconomic between-country differences. Moreover, we studied the relationships between those characteristics and each item of the MNA-FF. ## 4.1. Sample Characterization and Comparison between Countries The prevalence of malnutrition and its risk was higher in the Turkish sample, while Portuguese older adults presented a higher proportion of tooth loss, diabetes, hypertension, oncologic diseases, kidney diseases, osteoarticular problems and eye problems. Additionally, Portuguese participants had higher BMI but lower CC, as well as a lower prevalence of anemia. The sociodemographic differences found between Portuguese and Turkish older adults must be taken into account when defining public health interventions to prevent or treat malnutrition. Turkish older adults were more heterogeneous regarding their education level, which may imply some difficulties when defining communication strategies. On the other hand, the lower proportion of Turkish older adults living with their spouses seems to be somewhat equalized by living with their children or other relatives, as the proportion of participants living alone was similar in both countries. In our study, Turkish community-dwelling older adults were more likely to be malnourished or at risk of malnutrition than the Portuguese ones ($4.9\%$ and $31.5\%$ vs. $1.2\%$ and $24.0\%$, respectively). The prevalence of malnutrition risk among European populations of older adults is about one-quarter, with lower proportions among community-living older adults [1,16,17] and, therefore, lower when compared to our results. On the other hand, a study among Portuguese older adults attending senior centers in Lisbon found a higher proportion ($45.4\%$) of older adults malnourished or at risk of malnutrition when compared to both our Turkish and Portuguese samples, thus highlighting the relevance of considering specific sociodemographic characteristics [18]. Some results may be explained by inter-country economical and/or cultural differences. Portugal has a higher Gross Domestic Product (GDP) per capita than Turkey [19]. The GDP is positively correlated with the population’s BMI [20] and with the consumption of processed foods [21]. Tooth loss was more frequent among Portuguese participants, which may be due to a higher intake of sweets [22], which is also associated with a higher BMI [23]. The higher proportion of anemia among Turkish older adults may be related to different eating habits—in particular, a lower consumption of meat and meat products [24] and higher consumption of tea [25]—which may reduce iron absorption [26], together with their lower BMI [27]. In our study, Portuguese older adults had a higher BMI when compared to the Turkish. A higher BMI is related to a lower prevalence of malnutrition [28], but people with a high BMI are more likely to have chronic diseases, such as diabetes, hypertension, kidney diseases or CVD [29]. This is in line with the higher prevalence of such diseases in the Portuguese sample. Moreover, a complementary analysis showed that participants with BMI > 27 kg/m2 ($$n = 344$$, $58.1\%$) had a higher prevalence of diabetes ($32.3\%$ vs. $17.7\%$), hypertension (73.5 vs. $55.2\%$) and CVD ($35.8\%$ vs. $25.0\%$; $p \leq 0.05$ for all). Portuguese older adults, when compared with the Turkish, presented lower CC, despite their higher BMI, which may be interpreted as lower muscular mass [30] and, consequently, higher fat mass. These results highlight the relevance of using different anthropometric measurements to assess older adults’ body compositions. Different patterns of physical activity may explain, at least partially, the opposite differences regarding BMI and CC, implying that more broad lifestyle approaches should be used to promote health among this age group. Portuguese and Turkish participants differed regarding the MNA-SF but not the MNA-FF scores. This suggests that comparisons of the results using different instruments or different forms of the same instrument should be made cautiously. Older adults may be more or less at risk of malnutrition due to specific characteristics, namely dietary ones, as discussed below. ## 4.2. Relationships of Sociodemographic, Clinical and Anthropometric Characteristics with MNA-FF Scores The MNA-FF score was higher among the Portuguese, males and younger older adults. Participants with dentures; without tooth loss, hypertension, CVD, anemia or oncological diseases and those with higher BMI and CC also presented a better nutritional status. Among these relationships, those with sex and CVD had the highest effect sizes. Several studies in different regions are in line with female older adults being more likely to be malnourished [28,31,32,33]. Women have higher rates of depression and widowhood and a lower subjective health status, which are known risk factors for malnutrition [31]. Moreover, some reports show that women have significantly lower pension incomes than men [34,35]. In Europe, low income is associated with food insecurity, especially at low levels of social protection [36], and it is well known that food insecurity (i.e., limited or uncertain availability of nutritionally adequate and safe food) is a potential risk factor for malnutrition [37]. Therefore, sex-specific low income may be a cause of malnutrition as well. However, cultural differences on how much men and women are aware of dietary recommendations and on how dietary intake is related to chronic disease prevention or regarding cooking skills may also be relevant to interpret these results, as discussed by MacNab et al. [ 2018] when interpreting the lower nutritional risk among females in a sample of older adults in the USA [38]. CVD impose a substantial burden on the quality of life. Many patients with CVD have at least one other disease (such as diabetes or hypertension), which will have an even more negative effect on the quality of life [39,40]. Thus, CVD may cause a lower subjective health status and psychological stress or depression [41]. A study with Portuguese older adults attending senior centers showed reports that both CVD and lower self-reported health status were associated with higher nutritional risk [18], and the association between poorer perceived health status and higher risk of malnutrition has also been reported elsewhere [42]. In addition, for individuals with CVD, the MNA score may be affected due to the recommendation to reduce the consumption of red meat [43] if not replaced by other protein sources. The finding that participants with dentures and without tooth loss presented higher MNA-FF scores is different from the one reported in a recent meta-analysis, which showed that edentulism was related to a higher risk of malnutrition among older adults and that the lack of teeth was a risk factor for malnutrition even when adjusting for sociodemographic variables [44]. However, the same meta-analysis reported no differences in the risk of malnutrition between dentate and edentulous people with two complete dentures. This may explain the difference from our results, as, in our sample, despite that we did not record the type (complete or not) of denture, from a total of nine out of ten older adults with tooth loss, about two-thirds had dentures. ## 4.3. Relationships of Sociodemographic, Clinical and Anthropometric Characteristics with MNA-FF Items The relationships of the sociodemographic, clinical or anthropometric variables with some individual MNA items were in the opposite direction from those with the overall MNA-FF score. Taking more prescribed drugs (item H) was more common among participants with higher MNA-FF scores, and this may be related to a higher BMI and its associated comorbidities, which were more common among Portuguese older adults. Portuguese and Turkish participants seemed to differ regarding specific eating features, with the Portuguese consuming a lower number of full meals per day (item J, which does not imply that the overall food intake is smaller) and having a lower fluid intake (item M). These different characteristics may be one of the causes of a higher BMI and a higher likelihood of related comorbidities among the Portuguese sample, which may, in turn, result in a worse perception of one’s own health status. These assumptions are supported by the known relationships between these features (namely, the impact of obesity on health) but may also be due to cultural differences. These results and previous knowledge [45,46] both support the conjecture that the Portuguese have less full meals, drink less fluids [47] and complain more about their health [48,49], namely when compared to Turkish older adults. However, the lack of studies directly analyzing the relationships of the sociodemographic, cultural, clinical and anthropometric characteristics with specific features related to malnutrition hardens the interpretation of such results, despite interest in the development of interventions. ## 4.4. Limitations and Strengths Some limitations should be considered when interpreting the results of our study. The use of two convenience samples with different sociodemographic characteristics is one of them. However, the multivariate analysis allows the interpretation of the adjusted effects of the sociodemographic, clinical and anthropometric characteristics on the MNA-FF scores. The cross-sectional design of the study does not allow causality inference. The clinical data were self-reported and may therefore be biased, as there might be an underestimation of some diseases and health conditions due to a lack of memory. On the other hand, to our best knowledge, this was the first study to compare and relate the nutritional status, health and demographic characteristics between Turkish and Portuguese older adults. We highlight the use of the same methodology and standardized procedures in the two samples. Additionally, the information about the relationships between specific malnutrition-related features (as assessed by the MNA items) and sociodemographic, clinical and anthropometric characteristics provides relevant information for the development of directed and precise interventions. ## 5. Conclusions In conclusion, this study indicates that our sample of Turkish older adults living in the community was more likely to be malnourished than the Portuguese sample. However, Portuguese older adults presented a higher prevalence of chronic diseases. 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--- title: Effects of Resource Availability and Antibiotic Residues on Intestinal Antibiotic Resistance in Bellamya aeruginosa authors: - Yayu Xiao - Peiyu Zhang - Huan Zhang - Huan Wang - Guo Min - Hongxia Wang - Yuyu Wang - Jun Xu journal: Microorganisms year: 2023 pmcid: PMC10058807 doi: 10.3390/microorganisms11030765 license: CC BY 4.0 --- # Effects of Resource Availability and Antibiotic Residues on Intestinal Antibiotic Resistance in Bellamya aeruginosa ## Abstract Widespread and inappropriate use of antibiotics has been shown to increase the spread of antibiotics and antimicrobial resistance genes (ARGs) in aquatic environments and organisms. Antibiotic use for the treatment of human and animal diseases is increasing continuously globally. However, the effects of legal antibiotic concentrations on benthic consumers in freshwater environments remain unclear. In the present study, we tested the growth response of Bellamya aeruginosa to florfenicol (FF) for 84 days under high and low concentrations of sediment organic matter (carbon [C] and nitrogen [N]). We characterized FF and sediment organic matter impact on the bacterial community, ARGs, and metabolic pathways in the intestine using metagenomic sequencing and analysis. The high concentrations of organic matter in the sediment impacted the growth, intestinal bacterial community, intestinal ARGs, and microbiome metabolic pathways of B. aeruginosa. B. aeruginosa growth increased significantly following exposure to high organic matter content sediment. Proteobacteria, at the phylum level, and Aeromonas at the genus level, were enriched in the intestines. In particular, fragments of four opportunistic pathogens enriched in the intestine of high organic matter content sediment groups, Aeromonas hydrophila, Aeromonas caviae, Aeromonas veronii, and Aeromonas salmonicida, carried 14 ARGs. The metabolic pathways of the B. aeruginosa intestine microbiome were activated and showed a significant positive correlation with sediment organic matter concentrations. In addition, genetic information processing and metabolic functions may be inhibited by the combined exposure to sediment C, N, and FF. The findings of the present study suggest that antibiotic resistance dissemination from benthic animals to the upper trophic levels in freshwater lakes should be studied further. ## 1. Introduction Antibiotics are used extensively in therapeutic medicines, disease prevention treatments, and as animal growth promoters [1,2,3], and their use continues to increase. Recent research has shown that global antibiotic consumption increased by $65\%$ and antibiotic consumption in China increased by $79\%$ between 2000 and 2015, and such a growth is projected to continue until 2030 [4]. It has been demonstrated that antibiotic residues in aquatic environments can pose ecological threats to aquatic organisms [5,6]. The presence of antibiotics can promote the emergence of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in aquatic environments [7,8]. In addition, the human-induced lake eutrophication increased microbial activity and antibiotic residue content, as well as the spread of ARB and ARGs [9,10], which increase the risk of bacterial drug resistance in aquatic organisms and in humans. According to predictions based on the current rates of antibiotic-resistance-associated deaths, there would be one such death every three seconds by the year 2050 [11]. Therefore, over the past few decades, the number of research articles addressing the topic has increased globally, with shifts in the intestinal microbiome being the current focus of research. Pathogenic bacteria, such as Microbacterium, Parachlamydiaceae, and Plesiomonas, proliferate in the intestine of Oreochromis niloticus following feeding on oxytetracycline [12]. Previous studies have examined the effect of residual antibiotics in the aquatic environment on intestinal microbiology and ARGs in aquatic organisms [13]. The effects of common antibiotics, such as oxytetracycline, tetracycline, sulfamethoxazole, and FF, on the intestines of fish have been studied previously [12,13,14,15,16,17]. However, our understanding of how the intestinal microbes and ARGs of aquatic organisms respond to the combined effects of sediment and antibiotics remains limited. The intestine has the greatest microbial diversity in organisms. Intestinal microbes are essential for digestion, metabolism, and immune activities in all animals [18,19,20,21,22]. In addition, aquatic environments are continuously exposed to antibiotics owing to persistent residues in the environment [23,24]. The resulting development of drug-resistant microbes, which are the primary ARG hosts, and ABR bacteria development in aquatic environments, increase the risks of gastrointestinal illnesses caused by such bacteria [25]. Both symbiotic and pathogenic microbiota are affected by antibiotic exposure [26]. It has been reported that water input is a primary factor influencing microbial community structure in the intestine of Poecilia reticulata in the Uberabinha River, Brazil, with a positive correlation between ARGs and the dominant genera in intestinal samples, and most microbes are potential ARG hosts [26]. Low-dose florfenicol (FF) exposure causes dysbiosis in host microbiota [21]. With growing concerns over the presence of antibiotics and ARGs in aquatic environments globally, the use of most antibiotics in aquaculture is no longer permitted [14]. Currently, FF is one of the most commonly used antibiotics in aquaculture in most countries [27]. However, FF has been detected in aquaculture environments in recent years in China, for example, in Taihu Lake [28], coastal seawater in Dalian [29], and in the Guangzhou aquaculture area [30]. Therefore, FF was selected as a representative antibiotic in the present study. Bellamya aeruginosa is widespread in lakes and ponds in the middle and lower reaches of the Yangtze River. Nearly 30,000 tons of B. aeruginosa is harvested annually in Chaohu Lake, China, where it is mainly used as human food and for crab farming [31]. B. aeruginosa is a freshwater snail that is and play the role of primary consumer in aquatic food web [32]. However, to the best of our knowledge, the consequences of FF exposure, particularly on B. aeruginosa and its intestinal health and ARGs, has not been investigated comprehensively. In the present study, B. aeruginosa was exposed to legal doses of FF for 12 weeks. The objective of the present study was to investigate the effect of FF and sediment with different nutrients on B. aeruginosa growth, as well as changes in intestinal health and ARG abundance in the host, using metagenomics. We report the impact of organic sediment matter, low-dose antibiotic residues, ARGs, and pathogenic hosts on the B. aeruginosa intestinal microbiome structure and function. The findings of the present study could enhance our understanding of food availability to aquatic organisms and antibiotics abundance in natural lakes, in addition to facilitating health risk assessments. ## 2.1. Antibiotics and Exposure FF was purchased from Shandong Dexin Biology Science and Technology Co., Ltd., (Binzhou, China) and commercial feed was purchased from Cangzhou Zhengda Biological Products Co., Ltd. (Gangzhou, China). We collected approximately 800 B. aeruginosa individuals from Liangzi Lake, Hubei province, China. These organisms were acclimated in four 80-L tanks with dechlorinated water. B. aeruginosa in each tank received oxygen and were fed a commercial feed (Table S2). We also collected sediments from Liangzi Lake to lay out in the experiment tanks. The initial properties of the sediment were 3.01 ± 0.79 mg/g organic phosphorus (P), 0.00 ± 0.01 mg/g organic nitrogen (N), and 16.60 ± 2.11 mg/g organic carbon (C). According to the methods in a previous study [33], submergent and emergent plants from Liangzi lake were oven dried (105 °C), ground, and then rewetted and used as organic matter to be added to the sediment. Two sediment treatments were set up, including one with high organic matter concentration (1.51 ± 0.32 mg/g organic N and 30.46 ± 2.83 mg/g organic C) and one with initial concentrations (0.00 ± 0.01 mg/g organic N, and 16.60 ± 2.11 mg/g organic C). There was no statistically significant change in organic P levels between the two sediment treatments following the aforementioned sediment treatment. Treated sediments (5-cm layer) were put in tanks (40 cm × 40 cm × 50 cm). The tanks were then placed in an open area, supplemented with 40 L of dechlorinated water, and allowed to settle for seven days. B. aeruginosa with an initial mean weight of 1.18 ± 0.19 g were separated randomly into 20 tanks with 10 B. aeruginosa individuals per tank. The added FF was 10 mg/g body weight. The control and experimental groups were as follows: five tanks for FF added with high sediment organic C, organic N (HA), five control tanks with high sediment organic C, organic N (HN), five tanks for FF added with low sediment organic C, organic N (LA), and five control tanks with low sediment organic C, organic N (LN). Over an 84-day study period, B. aeruginosa were fed commercial feed (once every fortnight). Considering that plants have the ability to absorb antibiotics, floating, leaf-floating, submerged plants, and attached algae on tank walls were removed daily throughout the study period. The pH, dissolved oxygen, total N (TN), and total P (TP) were maintained at 8.92 ± 0.57, 10.55 ± 1.76 mg/L, 1.57 ± 1.17 mg/L, and 0.01 ± 0.00 mg/L. ## 2.2. Sample Collection and Chemical Analysis All surviving B. aeruginosa were collected at the end of the experiment and the number of survivors per tank and their final body weights were determined, which were used to calculate the survival rates and weight gain, respectively. The intestinal contents of B. aeruginosa were extracted and stored at −80 °C for DNA analysis. In addition, water samples were collected from each tank for antibiotic analysis. FF concentration was determined using liquid chromatography–mass spectrometry (Waters Xevo TQ-S, Milford, MA, USA). The FF standards were purchased from Dr. Ehrenstorfer GmbH (Augsburg, Germany). Water samples (500 mL) were filtered through a 0.45-m membrane filter before being applied to an Oasis HLB cartridge (200 mg, 6 mL, Waters, Milford, MA, USA) for solid-phase extraction, as previously described [34]. The eluates were then exposed to a gentle N stream (Termovap Sample Concentrator, NK200-18, MIULAB, Hangzhou, China). A final volume of 1 mL was obtained by adding $10\%$ acetonitrile. The samples were then analyzed using a Xevo TQ-S tandem quadrupole mass spectrometer (Waters, Milford, MA, USA). Sediment organic carbon was pretreated with 1 mol/L HCL; then we used an elemental analyzer (Flash 2000, ThermoFisher Scientific, Waltham, MA, USA) to determine its value [35]. Sediment organic nitrogen represented the total nitrogen because organic nitrogen makes up ≥$90\%$ of the total N [36]. Organic P was measured by the content difference of the burned sample at high temperatures (550 °C) minus unburned sample detected in UV spectrophotometry [37]. ## 2.3. DNA Extraction and Metagenomic Sequencing The E.Z.N.A.® Soil DNA Kit was used to extract metagenomic DNA, according to the manufacturer’s instructions (Omega Bio-Tek, Norcross, GA, USA). The DNA sample purity and concentration were evaluated using a NanoDrop2000 UV-Vis spectrophotometer (ThermoFisher Scientific) and a TBS-380 fluorometer (Turner Biosystems, Sunnyvale, CA, USA), respectively. DNA integrity was examined by electrophoresis on $1\%$ agarose gel. Amplicon libraries were created after the DNA was broken up, using the Nexflex Rapid DNA-Seq Kit (Bioo Scientific, Austin, TX, USA). Amplicons were sequenced on an Illumina NovaSeq platform (Wuhan Baiaoweifan Biotechnology Co., Ltd., Wuhan, China). Fastp (https://github.com/OpenGene/fastp, version 0.20.0) was used to remove reads of <50 bp, quality < Q20, and bases beginning with N. BWA (http://bio-bwa.sourceforge.net, version 0.7.9a, accessed on 18 November 2022) was used to remove reads from the host genome. MEGAHIT (https://github.com/voutcn/megahit, version 1.1.2) was used to assemble the optimized reads. Contigs with lengths ≥100 bp were selected for use in gene prediction and annotation. Taxonomic annotations of amino acid sequences from non-redundant gene sets were compared to the RefSeq non-redundant proteins database using Diamond (http://www.diamondsearch.org/index.php, version 0.8.35, accessed on 21 November 2022). ARG access data were obtained from the Comprehensive Antibiotic Resistance Gene Database (version 3.0.9). ## 2.4. Statistical Analysis and Network Analysis The results of the experiment were expressed as the mean ± standard error of the mean. A t-test was used to determine whether there were any significant differences between treatments. R (version 4.0.3) was used to visualize the data. Diversity was assessed and displayed using the R vegan package. The R software (v. 4.0.3) was used to create bar plots, heatmaps, circular bar plots, circular plots, and to perform the correlation analysis. Reads per kilobase per million mapped reads (RPKM) were used to calculate the relative abundances of bacteria and ARGs. Statistical significance was determined at p ≤ 0.05 for the aforementioned analyses. ## 3.1. Effect of Dietary Florfenicol and Sediments on B. aeruginosa Growth The growth of B. aeruginosa was not significantly affected by dietary FF after 12 weeks of antibiotic treatment. Exposure to FF (HA and LA) did not significantly slow growth performance when compared with the controls (HN and LN) (Table 1). However, B. aeruginosa in the two sediment groups differed significantly in terms of weight gain (Table 1). B. aeruginosa grew slowly in sediment with low organic matter. ## 3.2. B. aeruginosa Intestinal Microbiome Structure after Treatments Proteobacteria, Firmicutes, Tenericutes, Bacteroidetes, and Actinobacteria were the top five most abundant phyla in the annotation results of all exposure groups following treatment (Figure 1A). To further explore the changes in the microbial structure, the relative abundances at the genus level were determined (Figure 1B). The most abundant species at the genus level included Aeromonas, Bacillus, Clostridium, Dechloromonas, Mycoplasma, Polynucleobacter, Proteocatella, Pseudomonas, Tolumonas, and Vibrio. All treatment groups could be divided into two groups, with the microbial communities of the HN and HA exposure groups placed in one category, with more abundant species. LN and LA exposure groups were placed in other category, with less abundant species. The microbial communities differed at the phylum and genus levels between the high organic matter content sediment (HN and HA) and the low organic matter content sediment (HN and HA) exposure groups, but not between the no-FF (HN and LN) and FF (HA and LA) exposure groups. Aeromonas, in particular, was detected in all groups and was greatly enriched in the high organic matter content sediment exposure group (HN and HA). It was categorized as a Proteobacterium at the phylum level, whereas at the species level, the genus Aeronomas contains numerous pathogens. ## 3.3. B. aeruginosa Intestinal Antibiotic Resistome Structure after Treatments A total of 286 antibiotic ARG subtypes were detected in the intestines of B. aeruginosa and classified into 23 types. Organic matter in the sediments altered the ARG distribution in the intestine significantly (Wilcoxon test, $p \leq 0.05$), with an increase in the number of ARGs (Figure 2A). Figure 1B shows the 21 types of ARGs, namely aminoglycoside, bacitracin, beta-lactam, bleomycin, carbomycin, chloramphenicol, fosfomycin, fosmidomycin, kasugamycin, macrolide-lincosamide-streptogramin (MLS), multidrug, polymyxin, puromycin, quinolone, rifamycin, sulfonamide, tetracenomycin_C, tetracycline, trimethoprim, vancomycin, and unclassified ARGs. The top ARG types of all samples were multidrug and MLS ARGs. When compared with that in the LN and HN samples, the relative abundance of ARG types did not change significantly following FF exposure (LA and HA). In addition, the relative abundances of ARG types did not differ significantly between the high and low nutrient organic matter level in the sediment treatments. ARG abundance was enriched in HA and HN at the ARG subtype level following nutrient treatments (Figure 2C). Among the top 50 detectable ARGs, MLS and multidrug ARGs were the most frequently detected types. There were 10 ARGs and 13 ARGs classified as MLS and multidrug ARGs, respectively. ## 3.4. Pathogenic Hosts of ARGs in B. aeruginosa Intestines ARG-carrying genes [1618] were identified in the intestinal bacteria of B. aeruginosa. ARGs encoding resistance to aminoglycoside, bacitracin, beta-lactam, carbomycin, chloramphenicol, fosmidomycin, kasugamycin, MLS, multidrug, polymyxin, sulfonamide, tetracenomycin_C, tetracycline, trimethoprim, and vancomycin were among the top 50 genes. ARG-carrying genes were annotated as fragments of Proteobacteria in the HN, HA, and LN groups ($54\%$, $76\%$, and $100\%$, respectively). Additionally, $92\%$ of the ARG-carrying genes in the LA group were annotated as Firmicute fragments (Figure 3). Using the pathogen–host interactions database and a previously summarized pathogen list [38], 13 ARG-carrying genes were identified as pathogen-host-carried genes (Table 2). The pathogen fragments carrying ARGs included aac6-I, aadE, chloramphenicol_exporter, cat_chloramphenicolacetyltransferase, macB, vatB, vatE, tcmA, bcrA, and mexT. Two pathogen fragments carried an ARG that encoded resistance to chloramphenicol, two pathogen fragments carried an ARG that encoded resistance to aminoglycoside, and six pathogen fragments carried an ARG that encoded resistance to MLS. The remaining three ARG-carrying pathogen pieces encoded resistance to bacitracin, multidrug, and tetracenomycin_C, respectively. Notably, Aeromonas hydrophila, which was grouped in the HN and HA groups, was often found in the B. aeruginosa intestine. A. hydrophila is a notoriously difficult-to-treat pathogen that can cause severe disease and infection in the intestines of aquatic organisms. ## 3.5. High Organic Matter Content Sediments Altered the Intestinal Microbe Function Different intestinal bacterial metabolic pathways produce different metabolites that influence all aspects of host physiological functions. The functional pathways of the microbial communities were inferred using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database to understand the functional profiles of the intestinal bacterial community after treatment. In total, 8322 functional pathways were identified in the intestine of S. aeruginosa, (Figure 4). The four groups shared the majority of the functional pathways. Upon calculating the fold difference between the high (HA and HN) and low organic matter content groups (HN and LN), 27 functions were observed to be upregulated (Figure 4A). When the fold difference between no FF exposure (LN and HN) and FF exposure (LA and HA) was calculated, all functional pathways showed no significant differences (Figure S1). Sediment organic matter levels caused functional changes in the intestinal flora rather than FF. Twenty-seven altered functional pathways from 14 categories were selected for the analysis of two treatment factors (Figure 4B). Folding, sorting and degradation function, glycan biosynthesis and metabolism function, and protein families: genetic information processing function were significantly positively correlated with sediment organic matter, whereas the replication and repair function was significantly negatively correlated with the sediment organic matter level. Two unclassified functions (genetic information processing and metabolism) were significantly negatively correlated with FF exposure. ## 4. Discussion Food sources and environmental conditions can influence the growth of benthic consumers. The vast majority of benthic consumers consume surface sediment [39]. C and N from food can theoretically be stored at homeostatic states in body tissues [40]. Sedimentary organic matter fuels the benthic food chain and is an important recycler in lake ecosystem energy flows, as well as the C and N cycles [41,42]. In the present study, exposure to low-nutrient sediments suppressed B. aeruginosa weight gain. Conversely, exposure to FF in the diet at legal doses did not result in such a phenomenon, which is consistent with the findings of some studies on aquatic animals, such as Gadus morhua [43], Oreochromis sp. [ 44,45], and Oreochromis niloticus [46]. In addition, FF can be degraded in an open area by water temperature (10 °C), electrolytes, and UV processes [47,48,49]. This implies that B. aeruginosa growth may be affected more by sediment organic matter (C and N) than by the low doses of antibiotics applied in the present study. B. aeruginosa inhabits the sediment–water interface [50]. It uses organic matter (particularly C and N) in sediments to facilitate energy exchange and growth [40,51]. The composition of the diet shapes the composition of intestinal microbiota and can integrate new genes into the microbiota of the intestine [52]. For example, Eriocheir sinensis intestinal microbiota were composed of bacteria harbored by its food source [53]. Based on these findings, diet modulation could be a potential treatment for dysbiosis caused by antibiotic exposure, such as supplying bee pollen in food to develop the intestinal tract of African catfish [54]. In the present study, organic matter sediment influenced intestinal microbiota community abundance. Microbial community alteration is the major driver of ARG distribution [55]. The present findings showed a potential correlation between Proteobacteria abundance and increased ARG abundance, which is consistent with previous research that discovered Proteobacteria as potential ARG hosts [56]. An increase in Proteobacteria abundance, moreover, is an indicator of dysbiosis. Furthermore, changes in intestinal microbiota may influence various physiological processes [57]. ARGs (aac6-I, aadE, chloramphenicol_exporter, cat_chloramphenicol_acetyltransferase, macB, vatB, and tcmA) were found in the Proteobacteria fragments in the present study. A. hydrophila, Aeromonas caviae, Aeromonas veronii, and Aeromonas salmonicida were detected as ARG-carrying pathogens and are fairly resilient pathogens. They can produce enterotoxins, posing a significant challenge to host microbiota stability and resilience [58,59]. Such hosts can spread ARGs to confer resistance to antibiotics via horizontal gene transfer and mutational events [60,61], resulting in the spread of ARB and increasing the economic burdens in aquaculture [62]. Increased organic matter concentration in sediments is undesirable. In our study, high organic matter sediment enhanced Proteobacteria abundance at the phylum-level and Aeromonas abundance at the genus level. The frequency of pathogen detection in the intestine increases dramatically following exposure to high-nutrient sediments. ARGs in the gut are under selective pressure from organic matter from food, in addition to microbial interactions and effects [63]. It has been demonstrated that sediment organic C influences resistance gene distribution in benthic animals [64]. In another study, the intestinal microbiota in two species of wild crabs served functions comparable to those of sediment [65]. The two ARGs most frequently observed in our samples were MLS and multidrug ARGs. Eutrophic lakes have also been shown to contain a range of ARGs, primarily multidrug ARGs [66]. ARGs can co-occur, and co-selection is likely to enrich the resistance of ARB to unrelated antibiotics [67,68]. Therefore, antibiotic resistance in eutrophic water environments may pose a significant challenge for manipulating the microbiota against ARB. Additionally, our results demonstrate that the metabolic activity of intestinal bacteria increases with an increase in organic matter contents. Three functions actively related to protein processing and lipid metabolism demonstrated a strong correlation with C and N, suggesting that B. aeruginosa has undergone certain dietary adaptations [69,70,71,72,73,74]. Similarly, oyster gut microbiomes respond to higher nutrient levels in the diet by upregulating certain glucose and lipid metabolism activities [75]. However, because sediment C and N have the capacity to suppress DNA transcription, the rise in sediment C and N in the present study has the potential to result in DNA damage. In our study, the metabolic expression of resistance was unaffected by short-term exposure to low-dose FF. Following exposure to our experimental conditions, the metabolic function pathways of the gut microbiota did not significantly change [76]. Furthermore, two unidentified processes associated with the processing of genetic information and metabolism were inhibited following exposure to FF under increasing sediment C and N. Further research should be conducted on the joint effects of eutrophication and antibiotic exposure on microbial structures and their functions. ## 5. Conclusions In conclusion, the organic matter in the sediment facilitated B. aeruginosa proliferation. High organic matter sediments affected the intestinal microbiota and metabolic expression of B. aeruginosa, according to metagenomic sequencing analysis results. Some processes were activated to adjust to the dietary organic materials. However, exposure to sediment C, N, and FF may disrupt several processes involved in metabolism and processing of genetic information. 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--- title: NMR-Based Metabolomics Demonstrates a Metabolic Change during Early Developmental Stages from Healthy Infants to Young Children authors: - Liana Bastos Freitas-Fernandes - Gabriela Pereira Fontes - Aline dos Santos Letieri - Ana Paula Valente - Ivete Pomarico Ribeiro de Souza - Tatiana Kelly da Silva Fidalgo journal: Metabolites year: 2023 pmcid: PMC10058828 doi: 10.3390/metabo13030445 license: CC BY 4.0 --- # NMR-Based Metabolomics Demonstrates a Metabolic Change during Early Developmental Stages from Healthy Infants to Young Children ## Abstract The present study aims to identify the salivary metabolic profile of healthy infants and young children, and to correlate this with age, salivary gland maturation, and dentition. Forty-eight children were selected after clinical evaluation in which all intraoral structures were examined. Total unstimulated saliva was collected, and salivary metabolites were analyzed by 1H Nuclear Magnetic Resonance (NMR) at 25 °C. Partial least squares discriminant analysis (PLS-DA), orthogonal PLS-DA (O-PLS-DA), and univariate analysis were used, adopting a $95\%$ confidence interval. The study showed a distinct salivary metabolomic profile related to age and developmental phase. The saliva of children in the pre-eruption teeth period showed a different metabolite profile than that of children after the eruption. However, more evident changes were observed in the saliva profile of children older than 30 months. Alanine, choline, ethanol, lactate, and sugar region were found in higher levels in the saliva of patients before 30 months old. Acetate, N-acetyl sugar, butyrate, caproate, creatinine, leucine, phenylalanine, propionate, valine, succinate, and valerate were found to be more abundant in the saliva of children after 30 months old. The saliva profile is a result of changes in age and dental eruption, and these findings can be useful for monitoring the physiological changes that occur in infancy. ## 1. Introduction Saliva is a complex biofluid containing numerous biological compounds which has high diagnostic potential for clinical outcomes [1,2,3,4,5,6]. This biofluid contains proteins, lipids, and low-molecular-weight metabolites that are products of cellular physiological reactions, and it performs an essential function in the oral environment [7]. The metabolic profile of saliva reflects the contribution of endogenous oral and systemic metabolism, as well as exogenous components such as oral flora and dietary products [8,9]. The metabolomic approach can determine the signatures of several local and systemic conditions, such as diabetes, periodontal disease, Sjogren syndrome, etc. [ 10,11,12,13]. To this end, this group characterized the profile of salivary metabolites in healthy children of different ages, including infants [14], with and without caries [8,15]. This study also determined the metabolites that are produced by oral microbiota metabolism [9,16] which characterize systemic diseases in children, as well as type I diabetes [12] and renal failure [11,13]. To allow for full saliva-monitoring potential, physiological modifiers such as oral microbiota metabolism products, diurnal variation, tooth eruption, diet, and age should be understood. In infancy, specific events such as salivary gland development and tooth eruption can modify the salivary profile. Salivary gland development begins in the sixth to eighth embryonic week and involves interactions between the epithelium and the underlying mesenchyme to form the functional part of the tissue. The parotid gland is the first to develop, and a hollow tube or duct of major salivary glands is formed in the sixth month of life, dramatically increasing the salivary flow rate [17]. In this period, the sixth month of life, the first primary teeth erupt. The salivary metabolomic profiles before and after this event are thought to be distinct. In the 30th month of life, another critical event occurs during stomatognathic system maturation, where the primary dentition is completely established, increasing the surface area for microorganism colonization and changing the local microbiota population [18,19]. Besides these developmental changes, during the first years of life there is a dietary transition and a significant increase in the diversity of microbial species that colonize the oral cavity [20,21,22], which may also be responsible for altering salivary composition. Neyraud et al. [ 2020] found metabolic profile changes between three and fifteen months of age, with increased 2-aminobenzoic acid, alanine and phenylalanine, hydroxybutyric acid, and acetoacetic acid levels. Glucose, maltose, lactose, and choline decreased over the first year [23]. There is limited knowledge related to the saliva profile of infants in the first months of life, mainly due to the difficulty of obtaining samples during this period. The literature reports that during infancy, some transformation occurs in the protein composition of saliva. Specifically, between three and six months of age there are higher levels of b-2 microglobulin and S-type cystatins [24,25]. The expression of mucins MG1 (MUC5B) and MG2 (MUC7) changes during the first year of life, with MG2 showing higher levels at the beginning of the first year and MG1 showing higher levels at the end [24]. Different glands produce MGs; MG1 is expressed in submandibular, sublingual, and some minor salivary gland cells, while MG2 is expressed in the submandibular gland [26]. Ruhl et al. [ 2005] already observed that most salivary proteins are expressed as early as the first month of life [24]. Sonesson et al. [ 2011] also demonstrated that some salivary proteins, such as mucin MG2 (MUC7) and IgA, increase with age, after comparing saliva from 3-year-old children, 14-year-old adolescents, and 25-year-old adults [27]. Although some information is present in the literature related to the protein content in infant saliva, limited knowledge is available concerning their levels of low-molecular-weight metabolites. Therefore, the present study aims to characterize the salivary metabolomic profile during the early developmental stages of healthy infants and young children, using Nuclear Magnetic Resonance. ## 2.1. Research Subjects Forty-eight systemically healthy infants and children from zero to five years old, without oral lesions or soft tissue lesions, were included in this study. Children with erupted teeth should be in primary dentition, without tooth decay, to be included. All parents of included subjects signed a Free and Informed Consent Form (TCLE) before participation in this study. Data and sample collection were carried out at the Pediatric Dentistry Clinic of the Federal University of Rio de Janeiro, UFRJ. Those responsible filled out a form developed for the study with personal data, anamnesis, health information, and the participants’ hygiene and dietary habits. Then, a trained professional performed the clinical examination of all the children’s intraoral structures, recording the data on a clinical examination form. For the intraoral examination, a mouth mirror, an explorer probe, and a disposable tongue retractor were used. The study protocol and the use of human material were authorized by the Research Ethics Committee (Number 4.712.999). ## 2.2. Collection and Storage of Saliva Samples Samples were collected in the period between 8:00 am and 10:00 am, due to the circadian saliva cycle [28]. Mothers were asked to refrain from feeding 15 min before saliva collection. Infants’ oral mucosa were cleaned using a gauze moistened with filtered water 5 min prior to saliva collection. Children older than 2 years were asked to suspend oral activities for 1 h prior to saliva collection. Unstimulated total saliva of the participants (0.5 mL) was collected using an automatic pipette with sterile tips. It was then stored in sterile plastic tubes (Eppendorf-TM) on ice and centrifuged for 1 h at 10,000× g and 4 °C in the laboratory of the Faculty of Dentistry UFRJ. The supernatant was stored at −80 °C until the moment of analysis. ## 2.3. Sample Preparation for Nuclear Magnetic Resonance (NMR), Data Acquisition and Analysis The samples were prepared and analyzed in a 400 MHz spectrometer at the National Center of Nuclear Magnetic Resonance by Jiri Jonas at Universidade Federal do Rio de Janeiro (CENABIO/UFRJ), who performed hydrogen NMR (1H) of the solutions using a Carl-Purcell-Meiboom-Gill (CPMG) pulse sequence. A mixture of 540 μL of saliva supernatant from the respective subjects plus 60 μL of pH 7 phosphate buffer was prepared, containing $99.8\%$ (to provide a field-frequency lock) and 20 µM of 4,4-dimethyl-4-silapentane-1-sulfonic acid (DSS) (for chemical shift referencing, δ = 0.00 ppm) [14,29]. The spectra acquisitions (0–12 ppm) were performed in a standardized way, with a pre-established receiver gain and number of scans (1024 scans) and a calculated pulse time and signal/noise ratio. The CPMG pulse sequence was used at 298 K (25 °C). Data were subjected to correction and base alignment using the software Topspin 4.1.4 (Bruker Biospin program, Rheinstetten, Germany). 1H-1H total correlation (TOCSY) experiments were also conducted, with acquisition parameters of 2048 × 256 complex points, a spectral width of 12,019 Hz in each dimension, and a mixing time of 70 ms [8,14]. Spectra and spectral regions that could not be corrected for phase and baseline were excluded from the analyses. The marking strategy included the use of the Human Metabolome database (http://www.hmdb.ca/, accessed on 24 June 2022) and previous markings in the literature [8,14,29]. TOCSY experiments were used to confirm the assignments. Thus, the relative abundances of metabolites in the study groups were obtained and subjected to statistical analysis. ## 2.4. Statistical Analysis The statistical program SPSS 20.0 (IBM, Chicago, IL, USA) was used to store and analyze the data obtained, apply normality tests, and stipulate a level of statistical significance of $95\%$ to be used. The spectra referring to the metabolomics data were submitted to the AMIX program (Bruker Biospin, Rheinstetten, Germany) for data extraction. Initially, the spectra were divided into 0.03 ppm buckets, and the water region was removed (4.5–5.5 ppm) to eliminate interference in the spectrum. Although the amount of fluid components does not change, there is evidence of variation in the ratio of water to components. Therefore, since doing so does not interfere with multivariate analysis, the values of each peak of the spectra were normalized, divided by the sum of the signal intensities, and then subjected to the Pareto scaling method [30] before applying the multivariate analysis. The generated data matrix, containing the peaks and integrals of the buckets’ areas, was subjected to multivariate analysis using the Metaboanalyst 5.0 program (www.metaboanalyst.ca, accessed on 24 June 2022). Metaboanalyst 5.0 was also used to obtain the predictive performance of the models; each model was evaluated for Q2, R2, and accuracy (ACC) for cross-validation purposes [31]. Principal Component Analysis (PCA), discriminant analysis with partial least squares method (PLS-DA), and discriminant analysis by orthogonal projections to partial least squares (O-PLS-DA) were also applied. Analysis of the VIP scores based on PLS-DA determined which salivary components contributed most to the differences between groups, related to the presence or absence of teeth [32]. A hierarchical clustering by dendrogram analysis was performed, which considered participants’ ages (< or >30 months) using euclide distance measurement and the Ward clustering algorithm (Metaboanalyst 3.0). For univariate analysis, data were submitted to the t test, adopting a $95\%$ confidence interval. A metabolic pathway analysis was performed using the compound names of the metabolites that resulted from univariate and VIP score analysis as the input variables; the pathway library used was the KEGG human metabolic pathways database (Metaboanalyst 3.0). The confidence interval was set to $95\%$. To improve transparency, data extraction is available in the Open Science Framework repository (https://doi.org/10.17605/OSF.IO/VFXRA, accessed on 24 June 2022). ## 3. Results This study was able to characterize the salivary profile of infants and children in different developmental stages, ranging from 16 to 60 months of life. The group containing infants without teeth consisted of twenty-six subjects (fifteen girls) with a mean age of 2.3 ± 1.9 months. The group of children with teeth consisted of twenty-two subjects (sixteen girls) with a mean age of 44.9 ± 18.1 months. Figure 1 shows the representative 1H NMR spectrum (0.50–4.50 ppm) of children’s saliva after primary teeth eruption (at 20 months). Multivariate analyses were performed to assess metabolite differences between groups. The PCA (Figure S1) was performed using age and dentition as identifiers (PC1 × PC2 and PC1 × PC3), and age presented better separation (Figure S1C,D) compared to tooth eruption (Figure S1A,B). The PLS-DA and O-PLS-DA of children before and after dental eruption (Figure 2A,B), as well as differences in samples from children before and after 30 months old (Figure 2D,E), show separation between groups; the model (Figure 2A) presented satisfactory accuracy and prediction. Of the three main principal components for dental eruption, ACC = 0.86, R2 = 0.74, and Q2 = 0.48. For the first two main components, PC1 and PC2, the PLS-DA presented a variability of $35\%$ (Figure 2A) and the O-PLS-DA a variability of $33.2\%$ (Figure 2B). For the 30-month-old separation, the model (Figure 2D) also presented satisfactory accuracy and prediction with regard to the three main components: ACC =0.95, R2 = 0.86, and Q2 = 0.71. For the first two main principal components, PC1 and PC2, the PLS-DA presented a variability of $35.2\%$ (Figure 2D) and the O-PLS-DA a variability of $32\%$ (Figure 2E). Figure 2C,F shows the VIP scores that were generated from the multivariate analysis, thus indicating the metabolites most responsible for the differences between groups. The highest VIP score demonstrates that the metabolite was the most important for the separation between groups. Thus, acetate, N-acetyl sugar, valine, valerate, and butyrate were present in higher amounts in the saliva of patients after primary teeth eruption compared to saliva before teeth eruption. On the other hand, lactate, glucose, and sugar region were found in greater amounts in the saliva of patients before teeth eruption. Acetate, N-acetyl sugar, and aminobutyrate were present in higher levels in the saliva of patients over 30 months old than in the saliva of those under 30 months old. Lactate, glycerol, glucose, and sugar region were found in greater amounts in the saliva of patients before 30 months old. Table 1 shows salivary metabolites from saliva before and after 30 months of age, using the chemical shift, peak intensity variation, and p values. The intensities of saliva metabolites, presented as mean (arbitrary units), confidence interval, spectrum region (ppm), and statistical analysis of multivariate analysis1 and univariate analysis2, were used. Univariate analysis also showed differences between the groups. Thus alanine, choline, ethanol, lactate, and sugar region were found in higher amounts in the saliva of patients before 30 months of age compared to saliva of patients after 30 months. Acetate, butyrate, caproate, creatinine, leucine, N-acetyl-sugar, phenylalanine, propionate, succinate, trimethylamine, valerate, and valine were higher after 30 months of age than before. Univariate analysis showed salivary metabolites from saliva before and after teeth eruption and found higher amounts of lactate and sugar region before tooth eruption and more butyrate, propionate, and acetate after. Figure 3 shows the change in the intensity of normalized peaks, representing the amount of each metabolite in each child’s saliva showing consistent changes over time. These data are in line with the metabolite production during the children’s growth. It is possible to observe that after 30 months of life, creatinine, N-acetyl sugar, propionate, and valine production increased, and ethanol production decreased. Interestingly, while some metabolites show a constant increase or decrease over time, such as choline, alanine, ethanol, and propionate, others show a threshold at close to 30 months of age, such as acetate, creatine, creatinine, leucine and valine. Beyond this threshold, their values increase and scatter. The figure also shows infants without and with teeth in blue and red, respectively. The dendrogram (Figure 4) demonstrates a distinction between infants < and >30 months of age. In the <30-month-old group, one miss classification (Baby 31) can be observed, as well as two miss classifications (Baby 18 and 25) in the >30-month-old group. The pathway analysis (Figure 5) considers the metabolites acetate, alanine, butyrate, choline, creatinine, ethanol, formate, glycerol, lactate, leucine, n-acetyl-sugar, phenylalanine, propionate, succinate, sugar region, trimethylamine, valerate, valine, caproic acid, and urea. The top 10 metabolites presented a statistical difference; therefore, the most important pathways were Aminoacyl-tRNA biosynthesis ($p \leq 0001$); Glycolysis/Gluconeogenesis ($$p \leq 0.001$$); Valine, Leucine, and Isoleucine biosynthesis ($$p \leq 0.00139$$); Butanoate metabolism ($$p \leq 0.00209$$); Pyruvate metabolism ($$p \leq 0.00757$$); Propanoate metabolism ($$p \leq 0.0161$$); Alanine, Aspartate, and Glutamate metabolism ($$p \leq 0.0175$$); Glyoxylate and Dicarboxylate metabolism ($$p \leq 0.0255$$); Phenylalanine, Tyrosine, and Tryptophan biosynthesis ($$p \leq 0.0327$$); and Valine, Leucine, and Isoleucine degradation ($$p \leq 0.036$$). ## 4. Discussion The present study observed the salivary metabolic profile of healthy infants and young children during different developmental stages. The eruption of teeth is an important event that occurs during the early stages of life, and 1H-NMR metabolomics demonstrated different profiles before and after this event. It was also found that a metabolomic shift in saliva occurs after 30 months old, which represents a threshold where events coincide with the completion of dentition, suggesting that this is related to the maturation of salivary glands and the increasing colonization of surfaces by oral microorganisms. During the first year of life, an infant develops further in association with the natural physiological process of primary dentition eruption, with local and general manifestations [33]. Increased salivary flow is one of the manifestations frequently found in children during the eruption phase of the first primary teeth [33]. There are many physiological modifiers that are difficult to control, which represent limitations to this type of study [34]. Despite this, several factors correlate saliva and its components to the normal growth and development of the child, which may be responsible for the changes observed [35]. Our study showed variation in the salivary metabolites profile related to different pathways, including amino acids and glucose metabolism. The top 10 related metabolic pathways were, respectively, Aminoacyl-tRNA biosynthesis; Glycolysis/Gluconeogenesis; Valine, Leucine, and Isoleucine biosynthesis; Butanoate metabolism; Pyruvate metabolism; Propanoate metabolism; Alanine, Aspartate, and Glutamate metabolism; Glyoxylate and Dicarboxylate metabolism; Phenylalanine, Tyrosine, and Tryptophan biosynthesis; and Valine, Leucine, and Isoleucine degradation. More choline was found within the first year of age than in older children, a finding corroborated by previous studies [36]. Choline is a precursor of several molecules, such as acetylcholine and phospholipids, and its decrease within the first year of life has been related to the decrease in milk consumption [37]. In the present study, children younger than 30 months were more likely to use formula than older children, which constitutes a possible explanation for the reduction of choline levels in this studied population. Changes in the concentration of amino acids in whole saliva can be related to endogenous proteolysis and bacterial metabolic pathways [8,9,14]. The levels of phenylalanine and valine were higher in the saliva samples of patients older than 30 months, which could be related to proteolysis around the teeth eruption site. In addition, the metabolic pathway demonstrated phenylalanine, tyrosine, and tryptophan biosynthesis and valine, leucine, and isoleucine degradation. Barnes et al. [ 2011] showed that increased levels of phenylalanine and valine are also related to the inflammation process that may be active in teeth eruption [38]. In the present study, no important changes were found in proline or its byproducts that could be related to the proteolysis of mucin or PRP, which could be an indication of the maturation process of the submandibular gland [17]. The present study also demonstrated higher levels of organic acids such as acetate, butyrate, succinate, and propionate with age, especially after tooth eruption. Morzel et al. [ 2011] described changes in salivary protein profiles in infants between three and six months old related to dietary modification that occurs during the first year [39]. Such changes in salivary proteins may provide substrates and surfaces for oral microbial adhesion and colonization [20,39,40]. Saccharolytic microflora convert sugars to lactic, formic, acetic, succinic, and other organic acids to obtain energy [38]. The concentration of these metabolites has been related to the bacterial load [41]. Fidalgo et al. [ 2013] used the metabolomic approach to analyze saliva from individuals with primary, mixed, or permanent dentition, from three to twelve years old [14]. This study demonstrated a similar general profile independent of dentition and age; however, some metabolites suggested to be related to oral microorganisms’ metabolites, such as organic acids, were observed in higher levels in permanent teeth. It is suggested that the increase in surface area with tooth eruption favors oral bacteria colonization and bacterial load, resulting in an upregulation of organic acid levels. This was also observed in the current study. It was found that acetate levels were increased in children with erupted primary teeth compared to toothless children. In previous findings, Fidalgo et al. [ 2015] demonstrated that this metabolite was higher with permanent dentition and in the saliva of patients with caries [8]. Acetate is found in the saliva produced by the parotid, submandibular, and sublingual glands [42]. This metabolite is a compound formed by bacterial metabolism, present in the dental biofilm matrix. N-acetyl sugar is a microbial product that was also found in greater amounts in children’s saliva after tooth eruption. This metabolite is an amide derivative of the monosaccharides. Butyrate and propionate are metabolites that are related to bacterial metabolism [29,43]. These metabolites were also found in greater amounts in children after dental eruption. Comparing spectra, the saliva samples of patients with gingival inflammation/periodontal disease were characterized by higher levels of acetate, c-aminobutyrate, n-butyrate, succinate, trimethylamine, propionate, and valine than those of healthy patients [44]. Children after teeth eruption are more prone to developing gingival inflammation [44], which is consistent with our results. Changes were also observed in compounds that may be related to food intake and oral hygiene, such as ethanol and glycerol. A decrease in salivary sugar concentration with age was observed, perhaps because, it is speculated, infants present more frequent feeding than older children. In addition, the feeding of children within the two groups varied between exclusive breastfeeding, use of formulas, and solid foods [25]. Our data showed an increase in creatine and creatinine with age, including, importantly, beyond the threshold of 30 months. Creatine and creatinine are metabolites found in muscle cells, and their increase may be related to the enormous change in weight and height observed during this period of childhood [23]. Creatinine concentration in the blood and urine is a marker of glomerular filtration influenced by several factors and has been correlated with age in previous metabolomics studies [45], therefore corroborating our data. Creatine and creatinine have already been related to age. Barr et al. [ 2005] studied a population with ages ranging from six to seventy years and demonstrated that urinary creatinine increases between 20 and 29 years and decreases thereafter [46]. Gu et al. [ 2009] also demonstrated an increase in urinary creatinine levels with age, from youth to adulthood [47]. The circadian cycle also seems to change the metabolic profile [48]. Our study was not able to distinguish this effect. The study’s design attempted to avoid interference by collecting saliva samples at the same time of day, in the morning. Our study aimed to determine the impact of tooth eruption and uncontrolled changes that occur during the first months of life on salivary metabolomic analysis of healthy infants and children. This information could impact studies in different areas such as dentistry, medicine, nutrition, development, and physiology, and it could influence the full assessment and monitoring of different types of diseases, both oral and systemic [49,50]. A limitation of the present study was the cross-sectional study design. Further studies should be conducted, such as a longitudinal study where the same infant would be followed after tooth eruption and after 30 months. Based on the present study, it is suggested that saliva could be another biofluid used for screening programs, especially considering the difficulties in blood collection in this young population. In this sense, metabolomics offers the opportunity for precision medicine that could be highly informative as well as discriminatory for the early detection of several diseases in infants and children. 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--- title: 'Hybrid Minimally Invasive Esophagectomy vs. Open Esophagectomy: A Retrospective Propensity Score Matched Comparison' authors: - Anna Vincke - Sorin Miftode - Fadl Alfarawan - Maximilian Bockhorn - Nader El-Sourani journal: Medicina year: 2023 pmcid: PMC10058829 doi: 10.3390/medicina59030434 license: CC BY 4.0 --- # Hybrid Minimally Invasive Esophagectomy vs. Open Esophagectomy: A Retrospective Propensity Score Matched Comparison ## Abstract Background and Objectives: Though widely used, only limited data is available that shows the superiority of hybrid minimally-invasive esophagectomy (HMIE) compared to open esophagectomy (OE). The present study aimed to analyze postoperative morbidity, mortality, and compare lengths of hospital stay. Materials and Methods: A total of 174 patients underwent Ivor Lewis esophagectomy in our surgical department, of which we retrospectively created a matched population of one hundred (HMIE $$n = 50$$, OE $$n = 50$$). Morbidity and mortality data was categorized, analyzed, and risk factor analyzed for complications. Results: The oncological results were found to be comparable in both groups. A median of 23.5 lymphnodes were harvested during OE, and 21.0 during HMIE. Negative tumor margins were achieved in $98\%$ of OE and $100\%$ of HMIE. In-hospital mortality rate showed no significant difference between techniques (OE $14.0\%$, HMIE $4.0\%$, $$p \leq 0.160$$). Hospital (OE Median 23.00 days, HMIE 16.50 days, $$p \leq 0.004$$) and ICU stay (OE 5.50 days, HMIE 3.00 days, $$p \leq 0.003$$) was significantly shorter after HMIE. The overall complication rate was $50\%$, but complications in general (OE $70.00\%$, HMIE $30\%$, $p \leq 0.001$) as well as severe complications (Clavien Dindo ≥ III: HMIE $16.0\%$, OE $48.0\%$, $p \leq 0.001$) were significantly more common after OE. In multivariate stepwise regressions the influence of OE proved to be independent for said outcomes. We observed more pulmonary complications in the OE group ($46\%$) compared to HMIE patients ($26\%$). This difference was statistically significant after adjustment for sex, age, BMI, ASA classification, histology, neoadjuvant treatment or not, smoking status, cardiac comorbidities, diabetes mellitus, and alcohol abuse ($$p \leq 0.019$$). Conclusions: HMIE is a feasible technique that significantly decreases morbidity, while ensuring equivalently good oncological resection compared to OE. HMIE should be performed whenever applicable for patients and surgeons. ## 1. Introduction The German S3-Guideline for diagnosis and treatment of squamous cell carcinoma and adenocarcinoma of the esophagus recommends any kind of minimally-invasive esophagectomy, including the laparoscopic-thoracotomic hybrid approach (HMIE) as the surgical procedure of choice for surgical treatment of esophageal cancer instead of open esophagectomy (OE) [1]. A few studies showed less postoperative morbidity as well as shorter hospital and intensive care unit (ICU) stay for the total minimally invasive approach (MIC) compared to OE [2,3]. Nevertheless, for some patients or surgical centers MIC cannot be the method of choice. Instead, a 2020 meta-analysis with a total of 3732 patients showed some disadvantages of MIC compared to Ivor Lewis HMIE [4]. Not only was the operating time of MIC significantly higher, but also significantly more anastomotic leakages occurred. Another meta-analysis by Bras et al. showed a similar overall morbidity rate for HMIE and MIC (HMIE $40\%$, $95\%$ CI: 25–$59\%$; MIC $37\%$, $95\%$ CI: 32–$43\%$; OR 1.13) [5]. For the alternative HMIE approach, only a few current studies showed superiority regarding morbidity and non-inferiority regarding survival in comparison to the OE technique [6,7]. For example, the MIRO trial by Mariette et al. demonstrated a significantly lower major intraoperative and postoperative morbidity in the first 30 postoperative days after HMIE compared to OE [6]. The length of hospital stay was equal in both groups, and variables like postoperative anemia or need of red blood cells (RBCs) were not reported. The objective of this retrospective study was to compare the HMIE and OE approaches regarding the aforementioned perioperative and oncological results in the setting of a single high-volume center with a large matched study population. An additional objective was to compare HMIE and OE regarding factors like hospital stay, as this kind of advantage has been shown for the equivalently recommended MIC technique [8]. ## 2.1. Study Design and Patients In our surgical department 174 patients received an Ivor Lewis esophagectomy for treatment of esophageal cancer from January 2010 until August 2022. HMIE was introduced as a new operating technique for underlying malignancy of the esophagus in 2019. Due to the new implementation, a hybrid approach was favored over MIC. In addition, HMIE is preferred over MIC at our institution, as it seems to be associated with a lower rate of anastomotic leakage [4,9]. This study retrospectively analyzed perioperative morbidity and mortality and the differences between two surgical techniques. HMIE was performed on 50 patients. We paired these with 50 patients treated with OE. All patients with an esophagectomy and reconstruction with gastric pull-up operated on in our surgical department in the aforementioned time span were considered for matching. This study was conducted in accordance with the ethics committee of the University of Oldenburg (AZ 2022-116). A flow chart of the study design is shown in Figure 1. ## 2.2. Preoperative Process Patients were either referred by outpatient physicians or by the gastroenterology department of our hospital. Before receiving any treatment, patients were evaluated for their suitability for surgery by computed tomography (CT) of the neck, thorax, and abdomen and endoscopic ultrasound (EUS). Furthermore, all patients were discussed in a multidisciplinary tumor board to ensure a stage-related therapy. According to the S3-guideline for diagnosis and treatment of squamous cell carcinoma and adenocarcinoma of the esophagus, patients either received neoadjuvant treatment in the form of radiotherapy, chemotherapy, or radiochemotherapy [1,10,11]. Some patients received no neoadjuvant treatment and others were treated with endoscopic submucosal dissection prior to surgery. After completion of neoadjuvant therapy, restaging including CT and EUS was conducted. ## 2.3. Surgical Techniques Directly before surgery an epidural catheter was placed in all patients to ensure adequate postoperative analgesia. All operations were performed by two surgeons at all times. HMIE was done through a 2-stage approach consisting of a laparoscopic abdominal and a muscle-preserving open right thoracotomy phase. The patient was brought in a supine “left lateral” position in combination with a “beach-chair” position (Figure 2). This way, the 2-stage approach could be performed in one setting without the need for re-positioning. During the abdominal phase, the first trocar was usually placed supra-umbilically. After induction of a pneumoperitoneum, four additional trocars were placed in a diamond-fashion where the one in the right upper quadrant must be at least a 12 mm port, which is needed for fashioning the gastric conduit (Figure 2). At first, the stomach was mobilized while preserving the gastric arcade and the right gastroepiploic artery and vein. A two-field lymphadenectomy was performed in concordance with the national treating guidelines for esophageal cancer [1]. Here, the left gastric artery and vein were identified, mobilized, and divided between two clips. Following complete mobilisation of the stomach, a 4–6 cm wide gastric conduit was fashioned by sequential firings of 45 mm Endo-GIA™ (Medtronic) cartridges parallel to the greater curvature, whereas the first firing was applied across the lesser curvature just above the pylorus and nearly perpendicular to the greater curvature. Following the complete mobilisation of the stomach and construction of the gastric conduit, an abdominal drain was inserted through the leftmost trocar and placed under the gastric conduit. This marked the end of the abdominal phase. Following, a muscle-preserving right anterior thoracotomy was performed. The right lung was excluded using a double-lumen tube. The arch of the azygous vein was mobilized and divided using an Endo-GIA™ Curved Tip (Medtronic, Meerbusch, Germany). A routine infracarinal lymphadenectomy was performed. Before fashioning the esophagogastric anastomosis using a 25 mm EEA™ Auto Suture Circular Stapler (Medtronic, Meerbusch, Germany), an intraoperative pathology consultation took place to confirm free resection margins. Finally, two chest drains were placed before closing the thoracotomy—one perianastomotically and one at the base of the lung. All patients were extubated in the OR and transported to the ICU. ## 2.4. Postoperative Management After surgery, all patients were primarily treated at the ICU and when stable enough, transferred to the intermediate care unit (IMC). Later, they were treated at the surgical ward. Enteral nutrition was standardized in all patients and started within 24 h postoperatively. For the first 4 postoperative days patients received nutrition via an intraoperatively inserted nasoduodenal feeding tube. From the fifth postoperative day, oral feeding was started with fluids and increased depending on clinical condition. Routine examination of the anastomosis was not performed. A combination of CT and upper endoscopy (UE) was only performed if an anastomotic leakage was suspected. In patients with severe complications (i.e., anastomotic leakage) a triple nasojejunal feeding tube was inserted after placing the endoluminal vacuum therapy. ## 2.5. Statistical Analysis The data was obtained from the clinical database of our hospital. Statistical analysis was performed using IBM SPSS Statistics 27. Propensity score matching was used for matching OE patients to HMIE patients. The calculation of propensity scores was performed by logistic regression with the matching criteria as independent covariables. The propensity scores were then used to manually match pairs between OE and HMIE patients. The maximum caliper between propensity scores was 0.096 and the median caliper was 0.0056. Matching criteria were gender, age, preoperative BMI, American Society of Anesthesiologists (ASA) classification, location of the tumor in the esophagus, and the type of neoadjuvant treatment received. For statistical testing we used Mann-Whitney U tests for continuous and Fisher’s exact tests for categorical variables. To illustrate associations between possible risk factors and certain outcomes like complications we performed logistic regression. To obtain double robustness with identification of confounders we conducted a multivariate forward stepwise regression in cases where prior tests showed statistically significant differences. ## 3.1. Patient Characteristics Between January 2010 and August 2022, a total of 174 patients underwent Ivor Lewis esophagectomy at the University department for General and Visceral surgery, Klinikum Oldenburg. Among these, 50 patients received HMIE, and the rest were treated with OE ($$n = 124$$). After matching, the median age of the study population was 64 years in the OE group (Range: 32–81 years) and 64.5 years in the HMIE group (Range: 41–83 years). Median BMI was 25.50 in the OE group (Range: 18.00–39.00) and 26.0 in the HMIE group (Range: 19.00–37.00). Patients were ASA classified preoperatively. The distribution of ASA classification was comparable between groups, with the majority being classified as ASA II and III (OE $94.00\%$, HMIE $98.00\%$). About half of the patients received no neoadjuvant treatment (OE $48.00\%$, HMIE $50.00\%$), whereas the predominant rest was treated with either chemotherapy (OE $40.00\%$, $$n = 20$$; HMIE $36.00\%$, $$n = 18$$) or radiochemotherapy (OE $12.00\%$, $$n = 6$$; HMIE $12.00\%$, $$n = 6$$) prior to surgery. One patient of the OE group received endoscopic submucosal dissection. Most cancers were located in the lower third of the esophagus (OE and HMIE $84\%$, $$n = 42$$). The most frequent comorbidities were cardiac, e.g., hypertension or history of myocardial infarction (OE $68.00\%$, $$n = 34$$; HMIE $54.00\%$, $$n = 27$$), followed by pulmonary comorbidities such as allergic asthma or COPD (OE $16.00\%$, $$n = 8$$; HMIE $16.00\%$, $$n = 8$$). A third of the OE patients ($32.00\%$, $$n = 16$$) and almost half of the HMIE patients ($46.00\%$, $$n = 23$$) had a history of smoking, while excessive alcohol consumption was only reported by a few patients (OE $6.00\%$, $$n = 3$$; HMIE $10\%$, $$n = 5$$). Further patient and tumor characteristics are listed in Table 1. ## 3.2. Surgical Results The exact surgical results are displayed in Table 2. The oncological results in the form of the number of harvested lymphnodes (OE Median 23.50; HMIE Median 21.00) and cases with negative tumor margin (R0-resection: OE $98.00\%$, $$n = 49$$; HMIE $100\%$, $$n = 50$$) were comparable across the groups. Only a few patients needed RBC transfusion perioperatively (OE $12\%$, $$n = 6$$; HMIE $2.00\%$, $$n = 1$$) and there was no significant difference between the groups ($$p \leq 0.112$$), but the number of RBCs that needed to be applied per patient was significantly higher in the OE group than in the HMIE group (OE Median 0.00, Maximum 6.00; HMIE Median 0.00, Maximum 1.00; $$p \leq 0.041$$). Hospital stay was significantly shorter for HMIE patients (OE Median 23.00 days; HMIE 16.50 days; $$p \leq 0.004$$). Furthermore, OE patients stayed almost twice as long on the ICU compared to HMIE patients (OE 5.50 days; HMIE 3.00 days; $$p \leq 0.003$$). ## 3.3. Perioperative Morbidity and Mortality Half of the patients had at least one complication ($$n = 50$$). However, complications were significantly more common in the OE group (OE $70.00\%$, $$n = 35$$; HMIE $30\%$, $$n = 15$$; $p \leq 0.001$). Categorized for severity of complications according to the Clavien Dindo classification, severe complications (Clavien Dindo III–V) occurred in $48\%$ of the OE patients ($$n = 24$$), whereas only in $16\%$ of HMIE patients ($$n = 8$$). This difference was also statistically highly significant ($p \leq 0.001$). A chi-square test was performed to test for the influence of complication variables on the overall complication rate. All associations were statistically significant and the φ coefficient for effect size demonstrated the strongest influence for pulmonary complications (χ2[1] = 44.444, p ≤ 0.001, φ = 0667), followed by pneumonia alone (χ2[1] = 41.360, p ≤ 0.001, φ = 0.643) (see Appendix D, Table A4). These were also the most common complications, and though not statistically significant, were more common after OE than after HMIE (pulmonary complications OE $46\%$, HMIE $26\%$, $$p \leq 0.060$$; pneumonia OE $38\%$, HMIE $26\%$, $$p \leq 0.284$$). Nine patients died perioperatively after a median of 19 days, ranging from 7 to 82 postoperative days (OE $14.0\%$, $$n = 7$$; HMIE $4.0\%$, $$n = 2$$; $$p \leq 0.160$$). Anastomotic leakage occurred in a total of 16 patients of the matched study population. A statistically significant difference between the groups could not be proven (OE $22.0\%$, $$n = 11$$; HMIE $10.0\%$, $$n = 5$$; $$p \leq 0.171$$). The anastomotic leakages were categorized in accordance with the classification of the Esophagectomy Complications Consensus Group’s (ECCG) classification. Anastomotic leakages that required surgical therapy (ECCG III) occurred in five patients after OE, while not at all in the HMIE group, but the difference failed to be statistically significant ($$p \leq 0.056$$). Further morbidity data is listed in Table 3. ## 3.4. Risk Factor Analysis Univariate testing with Fisher’s exact test revealed a significant difference between HMIE and OE patients regarding the occurrence of severe complications (Clavien Dindo III–V) ($$p \leq 0.001$$). The OR for HMIE compared to OE was 0.206 ($95\%$ CI 0.081–0.527). In order to test for confounding factors, a multivariate forward stepwise regression was conducted, where surgical technique was confirmed to be an independent risk factor for severe complications. Furthermore, Fisher’s test showed significant differences between ASA categories I/II and III/IV in relation to perioperative death ($$p \leq 0.034$$; OR 1.212; $95\%$ CI 0.521–2.822). In the multivariate regression model, cardiac comorbidities were also significant risk factors for death ($$p \leq 0.037$$). Regarding the occurrence of any complications, OE (univariate $$p \leq 0.001$$, multivariate $p \leq 0.001$; OR 0.206; $95\%$ CI 0.081–0.527) and cardiac comorbidities (univariate $$p \leq 0.040$$; multivariate $$p \leq 0.012$$; OR 2.571; $95\%$ CI 1.122–5.895) could be identified as independent risk factors. No risk factors could be identified for pulmonary complications in univariate analysis. However, multivariate stepwise forward regression proved the differences between OE and HMIE groups ($46\%$/$26\%$; multivariate $$p \leq 0.019$$) and patients with or without preexisting pulmonary morbidities ($18\%$/$54\%$; multivariate $$p \leq 0.033$$) to be statistically significant after adjusting for sex, age, BMI, ASA classification, histology, neoadjuvant treatment or not, smoking status, cardiac comorbidities, diabetes mellitus, and alcohol abuse. The detailed risk factor analysis for outcomes that were shown to have statistically significant risk factors are displayed in Table 4 and Table 5. As mentioned above, Mann-Whitney U tests also showed statistically significant differences between surgical techniques regarding duration of hospital (median 23 vs. 16.5 days; $$p \leq 0.004$$) and ICU stay (median 5.50 vs. 3 days; $$p \leq 0.003$$), as well as regarding the number of applied RBCs (maximum 6.0 vs. 1.0; $$p \leq 0.041$$). A multivariate forward stepwise analysis confirmed this while showing no significant confounding by sex, BMI ≥ 25, ASA III/ IV, neoadjuvant treatment, smoking, pulmonary or cardiac comorbidities, diabetes mellitus, or alcohol abuse (see Appendixe A, Appendixe B and Appendixe C, Table A1, Table A2 and Table A3). ## 4. Discussion In a meta-analysis with a total of 2397 patients from 2019, Yang et al. showed comparable results of HMIE and OE regarding the number of harvested lymphnodes [12]. This was also true for our study population, which not only showed similar numbers of harvested lymphnodes, but also almost the complete number of patients being R0-resected in both groups (OE $98\%$, HMIE $100\%$). These findings also go in line with other retrospective and prospective studies [6,13,14]. HMIE is undoubtedly on the rise in comparison to the open method. The aim of this study was to compare HMIE and OE regarding perioperative and oncological results and with that, to analyze whether HMIE could hold up to the expectations derived from other gastrointestinal procedures where advantages of laparoscopic compared to conventional open procedures have been shown numerous times [15,16]. Some studies have already shown similarly significant differences between HMIE and OE and the results are promising. In our study we were able to confirm a lower overall postoperative complication rate for HMIE compared to OE, and demonstrated an $82\%$ higher risk for the occurrence of complications for the OE group, while the overall complication rate was comparable to other studies with a similar number of patients [6,8]. Furthermore, the risk to develop severe complications, which were categorized by a Clavien Dindo classification of III–V, was $80\%$ higher in the OE group than in the HMIE group. Several studies showed a high pulmonary complication rate for all esophagectomy approaches, and it was frequently shown that this rate was significantly lower for HMIE patients in comparison to OE [17,18]. We were not able to support this observation alone with statistically significant tests, but our data showed a clear tendency in the same direction, as pulmonary complications were observed in $46\%$ of OE patients and only in $26\%$ of HMIE patients ($$p \leq 0.06$$). Additionally, we could confirm the above mentioned assumption after adjustment for sex, age, BMI, ASA classification, histology, neoadjuvant treatment or not, smoking status, cardiac comorbidities, diabetes mellitus, and alcohol abuse ($$p \leq 0.019$$). We were also able to demonstrate a significant influence of pulmonary comorbidities on the development of pulmonary complications after any kind of esophagectomy in said adjusted setting ($$p \leq 0.033$$). The fact that pulmonary complications were significantly more common after OE than after HMIE raises the question of its cause, since all patients received the same kind of thoracotomy. However, the difference between HMIE and OE was the abdominal part, and considering that several studies have shown a higher rate of postoperative pneumonia after laparotomy compared to laparoscopy, the higher number of pulmonary complications in this study’s OE group could be partially caused by the abdominal approach [19,20]. Another possible explanation could be the difference in operating time, and with that the longer duration of mechanical ventilation, which has also been shown to be an independent risk factor for the development of postoperative pneumonia [21]. The rate of anastomotic leakages was higher after OE than after HMIE (OE $22\%$, HMIE $10\%$, $$p \leq 0.171$$). Although not statistically significant, the difference between rates of anastomotic leakages between the groups is remarkable. Known risk factors for said leakages, such as BMI > 30 kg/m2 or < 18.5 kg/m2, diabetes, or a smoking history are distributed equally between OE and HMIE groups, so the different frequencies cannot be explained by these [22]. However, a possible contribution could be a longer impaired circulation during the surgery since the groups are matched as homogeneously as possible, but we detected a difference in the duration of surgery and the needed number of RBCs [23,24]. In general, the results regarding anastomotic leakage rates are heterogenous throughout studies. While some report lower rates for OE compared to HMIE, other studies also show appreciably higher rates of anastomotic leakages after OE compared to HMIE [6,13]. Finally, a 2019 meta-analysis by Yang et al., including 17 studies and 2397 patients, also showed no difference between HMIE and OE (OR 0.95, $95\%$ CI 0.67–1.35) [12]. Our results go in line with the literature here, since in our study the difference between anastomotic leakage rates is not statistically significant ($$p \leq 0.171$$). Besides overall and pulmonary complications, we differentiated between severe complications and minor complications according to the Clavien Dindo classification. We considered complications classified Clavien Dindo III and above as severe, meaning at least the requirement of surgical, endoscopic, or radiological intervention [25]. In our study population these requirements were met by $48\%$ of the OE group and $16\%$ of HMIE patients with an Odds ratio of 0.206 ($95\%$ CI 0.081–0.527), which meant a large increase in risk of almost $80\%$ for OE patients. We were also able to show a significantly shorter hospital and ICU stay, as well as a significantly smaller number of applied RBCs for HMIE compared to OE patients. Since these are rather cost-relevant factors it would be interesting to perform a dedicated cost analysis of both procedures to see whether one is superior in this regard. ## 5. Limitations This study had some limitations. The most important being the retrospective approach with all its weaknesses, including possible information bias, as it is not possible to fully ensure complete data in medical records. Another weakness is the single center setting that limited the size of our study population. Due to the matching procedure, additional patients had to be excluded from the analysis, which on one hand led to a robust handling of confounders, but on the other hand additionally reduced the number of patients. Improvement of ICU management over time could have led to a lower overall complication rate in the HMIE group, of which the majority of patients received their surgery more recently than OE patients. An analysis of risk factors was only conducted for the overall patient collective. To achieve statistically significant effects for analyses of subgroups a larger number of patients would be necessary. It would be interesting to know if the different surgical techniques come with different risk factors for certain complications. One further limitation certainly is the restricted follow-up time. Our data collection was restricted to the hospital stay in which the operation took place. We were able to interpret the immediate oncological results and mortality, but long-term outcome, especially regarding recurrence rate or survival rates, could not be analyzed. ## 6. Conclusions Our study clearly demonstrated reduced postoperative morbidity and in hospital-mortality for HMIE in comparison with OE. Not only were overall complications less likely to occur, but they were less severe than in OE cases. Furthermore, patients stayed significantly shorter in the ICU and were discharged faster when operated on with the HMIE approach. All this confirms the beneficial effects found in other studies and for other minimally-invasive surgical techniques of esophagectomy or other surgeries of the gastrointestinal tract. Summed up, HMIE is a feasible technique that significantly decreases morbidity while ensuring equivalently good oncological resection compared to OE. HMIE should be performed whenever applicable for patients and surgeons. ## References 1. 1. 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--- title: Circulating Plasma Exosomal Proteins of Either SHIV-Infected Rhesus Macaque or HIV-Infected Patient Indicates a Link to Neuropathogenesis authors: - Partha K. Chandra - Stephen E. Braun - Sudipa Maity - Jorge A. Castorena-Gonzalez - Hogyoung Kim - Jeffrey G. Shaffer - Sinisa Cikic - Ibolya Rutkai - Jia Fan - Jessie J. Guidry - David K. Worthylake - Chenzhong Li - Asim B. Abdel-Mageed - David W. Busija journal: Viruses year: 2023 pmcid: PMC10058833 doi: 10.3390/v15030794 license: CC BY 4.0 --- # Circulating Plasma Exosomal Proteins of Either SHIV-Infected Rhesus Macaque or HIV-Infected Patient Indicates a Link to Neuropathogenesis ## Abstract Despite the suppression of human immunodeficiency virus (HIV) replication by combined antiretroviral therapy (cART), 50–$60\%$ of HIV-infected patients suffer from HIV-associated neurocognitive disorders (HAND). Studies are uncovering the role of extracellular vesicles (EVs), especially exosomes, in the central nervous system (CNS) due to HIV infection. We investigated links among circulating plasma exosomal (crExo) proteins and neuropathogenesis in simian/human immunodeficiency virus (SHIV)-infected rhesus macaques (RM) and HIV-infected and cART treated patients (Patient-Exo). Isolated EVs from SHIV-infected (SHIV-Exo) and uninfected (CTL-Exo) RM were predominantly exosomes (particle size < 150 nm). Proteomic analysis quantified 5654 proteins, of which 236 proteins (~$4\%$) were significantly, differentially expressed (DE) between SHIV-/CTL-Exo. Interestingly, different CNS cell specific markers were abundantly expressed in crExo. Proteins involved in latent viral reactivation, neuroinflammation, neuropathology-associated interactive as well as signaling molecules were expressed at significantly higher levels in SHIV-Exo than CTL-Exo. However, proteins involved in mitochondrial biogenesis, ATP production, autophagy, endocytosis, exocytosis, and cytoskeleton organization were significantly less expressed in SHIV-Exo than CTL-Exo. Interestingly, proteins involved in oxidative stress, mitochondrial biogenesis, ATP production, and autophagy were significantly downregulated in primary human brain microvascular endothelial cells exposed with HIV+/cART+ Patient-Exo. We showed that Patient-Exo significantly increased blood–brain barrier permeability, possibly due to loss of platelet endothelial cell adhesion molecule-1 protein and actin cytoskeleton structure. Our novel findings suggest that circulating exosomal proteins expressed CNS cell markers—possibly associated with viral reactivation and neuropathogenesis—that may elucidate the etiology of HAND. ## 1. Introduction Globally, there are ~37.5 million people infected with human immunodeficiency virus (HIV), with 1.5 million new infections in 2020 alone [1]. Although the effective combined antiretroviral therapy (cART) has significantly reduced HIV-associated deaths, ~50–$60\%$ of patients may develop HIV-associated neurocognitive disorder (HAND) [2]. The pathological causes of HAND are still under investigation. Recently, extracellular vesicles (EVs) have had increasing prominence in physiology and pathology research due to their ability to package and deliver payloads (lipids, proteins, or nucleic acids) and molecular signals, enabling cell-to-cell communication and tissue homeostasis [3,4], or to stimulate pathogenesis in numerous diseases [5,6]. Recently, attention has been aimed toward discovering the role of EVs in HIV infection in the body and central nervous system (CNS). Once within the CNS, HIV stimulates neuronal damage using a variety of mechanisms via “direct” or “indirect” neurotoxicity [7]. Several studies have reported that viral proteins are the “direct” cause of CNS dysfunction [8,9,10]. We and others have reported that EVs, or exosomes (well-characterized EVs with a size < 150 nm), released by HIV-1 infected cells containing HIV-1 Tat [11], envelope protein (env) [12], gp120 [13,14], HIV-1 Gag [14], the Nef protein [15], and trans-activation response elements [16,17] may induce neuropathogenesis. Conversely, exosomes have been described as an “indirect” mechanism(s) to accelerate the progression of neurodegenerative disorders such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and/or other neurodegenerative diseases through the supply of proteins or molecules associated with the disease pathology [18,19,20,21,22,23]. Recently, we reported that exosomes released by HIV-infected T-cells or monocytes disrupted mitochondrial dynamics and endothelial nitric oxide synthase (e-NOS) function in primary human brain microvascular endothelial cells (HBMVECs) [11]. Using proteomic analysis, András et al. [ 24] confirmed that HIV and amyloid beta (Aβ) interact to change the EV composition of HBMVEC, with an increase in proteins engaged in exocytosis, vesicle formation, and immune activation. Another proteomic study of EVs isolated from the cerebrospinal fluid (CSF) of HIV-infected patients with clinical manifestation of HAND reported that markers for microglial activation, inflammation, and stress responses were increased in isolated EVs [25,26]. To establish neurocognitive dysfunction using magnetic resonance imaging or scan-based position emission topography methods is costly, and these facilities are limited in developing countries. Diagnosis from CSF for this purpose is an invasive and tedious method. There is a need for a noninvasive technique to address the development and progression of neuropathogenesis, especially in AIDS patients. Recent findings showed that exosomes originating from the CNS can cross the blood–brain barrier (BBB) and carry the pathologic proteins into the blood [27]. Therefore, serum/plasma-derived exosomes from patients with neurological disorders such as PD and AD are being examined for promising biomarkers of neuropathogenesis and clinical progression [21,22,23], and recent studies have characterized plasma EVs/exosome abundance and payload in HIV-infected patients [28,29,30]. We used a liquid chromatography/mass spectrometry (LC-MS/MS)-based proteomic approach to examine circulating plasma exosomal protein links to neuropathogenesis in simian/human immunodeficiency virus (SHIV)-infected rhesus macaques (RM). Plasma exosomes isolated from HIV-infected and cART treated patients have validated key proteomic results of circulating exosomes of RM. ## 2.1. SHIV-Infected and cART-Treated Rhesus Macaque Plasma The rhesus macaques (RM) used in this study were housed at the Tulane National Primate Research Center (TNPRC). In addition to complying with the Animal Welfare Act enforced by the U.S. Department of Agriculture (USDA) and Office of Laboratory Animal Welfare (OLAW) within the National Institutes of Health, the TNPRC is accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International, which exceeds federal statutes and policies. Animal care followed all institutional guidelines and recommendations. Plasma samples from five SHIV-infected and five uninfected control RM were included in this study. For proteome analysis, we included plasma samples from three randomly selected SHIV-infected ($$n = 3$$) and three uninfected animals ($$n = 3$$). The average ages of the SHIV-infected and uninfected animals were 11.8 years (14.49 y, 9.51 y, and 11.45 y) and 8.7 years (6.69 y, 7.72 y, and 11.83 y), respectively. Animals were challenged intravenously with the pathogenic chimeric SHIV-D (50 ng of SIV p27 Gag), which is an R5/X4 tropic virus, like many strains of HIV-1. After plasma viral load (PVL) reached viral set point (~6 weeks post-infection), animals were treated daily s.q. for ~12 weeks with a triple-drug ART regimen (including two nucleotide analogs, Tenofovir (TDF) and Emtricitabine (FTC), to inhibit reverse transcriptase, and dolutegravir (DTG) to inhibit integrase) to bring PVL to undetectable levels, analogous to many clinical drug regimens. Animals were followed up for 86 weeks, and plasma were collection at the time of necropsy. ## 2.2. HIV-Infected and cART-Treated Patient Plasma Samples Normal human plasma was purchased from Sigma-Aldrich, St. Louis, MO, USA (Cat # H4522). HIV-infected and cART-treated (Prezcobix 800 mg-150 mg, Tivicay 50 mg, Etravirin 200 mg) patient plasma was purchased from Innovative Research (Peary Court, Novil, MI, USA). ## 2.3. RNA Isolation and Viral Load Quantification by qRT-PCR SHIV viral load was quantified at the Tulane National Primate Research Center Pathogen Detection and Quantification Core, as previously published [31]. Briefly, RNA was extracted from 500 µL of plasma or exosomes suspension with the High Pure Viral RNA kit (cat. # 11858882001; Roche, Indianapolis, IN, USA) according to the manufacture’s protocol. Reverse transcription was performed with specific primers and quantitative Real-Time PCR was performed in duplicate with primers and probes specific for the gag gene, and armored RNA for hepatitis C virus was used as internal positive control. ## 2.4. Isolation of Exosomes from Rhesus Macaque (RM) and Human Plasma The EVs were isolated from 4 mL of SHIV+/− RM and 1 mL of HIV+/− human plasma by the exoEasy Maxi Kit (QIAGEN, 40724 Hilden, Germany, Cat # 76064) according to the manufacturer’s protocol. Initially, plasma samples were differentially centrifuged at 500× g for 5 min, 2000× g for 10 min and 10,000× g for 30 min to remove cells, cellular debris, and large microvesicles, respectively. Plasma was passed through a syringe filter (Millipore Millex-AA; Cat. # SLAAR33SS) to exclude particles larger than 0.8 µm. Following manufacturer instruction, we added 1 volume of buffer XBP to 1 volume samples, mixed by gently inverting the tubes 5 times, and samples were kept for 15 min at room temperature. The sample/XBP mix was added onto the exoEasy spin column, centrifuged at 500× g for 1 min to remove the residual liquid from the membrane, and then centrifuged at 3000× g for 1 min. Then, 10 mL of buffer XWP was added and centrifuged at 3000× g for 5 min. Finally, EVs were eluted at 600 and 400 µL of XE buffer for RM and human samples, respectively. All the isolation steps were performed at room temperature. The isolated EVs protein concentration was measured using BCA protein assay kit (Pierce, Therma Scientific, Rockford, IL, USA), and were aliquoted with 50 µL of volume and stored at −80 °C until used. ## 2.5. Characterization of EVs by the ZetaView Particle Metrix System Size and concentration of the isolated extracellular vesicles were measured using a ZetaView PMX-430-Z QUATT laser system $\frac{405}{488}$/$\frac{520}{640}$ with fixed cell assembly for size, concentration, and zeta potential (Particle Metrix, Mebane, NC, USA) and the corresponding software ZetaView v8.05.16 SP3. Briefly, the system was calibrated and aligned with diluted (1:250,000) 100 nm polystyrene standard polymer particles in aqueous suspension (Applied Microspheres, Leusden, The Netherlands) before the experiment. Samples were kept at room temperature for 30–45 min to accustom before measurement. Samples were diluted to appropriate concentration (1:1000) in deionized-distilled water (ddH2O) to reach particle numbers ideal for ZetaView Particle Metrix system. All samples were analyzed under the same conditions (room temperature nearly 20 °C to 25 °C, pH 7.0, sensitivity 80, shutter speed 100, and each replicate included eleven positions). ## 2.6. Quantitative Discovery-Based Proteomics Using Tandem Mass Tags (TMT) and Liquid Chromatography Mass Spectrometry (LC-MS) Samples were prepared for discovery-based quantitative proteomic analysis as previously described [32,33,34]. Briefly, the tandem mass tag (TMT) approach uses isobaric tags to differentiate multiplexed protein extracts using LC-MS. Complexity is reduced by the incorporation of an off-line fractionation step: a basic pH reverse-phase liquid chromatography. The fractionated labeled peptide mixtures were run on a Dionex U3000 nano-flow system coupled to a Thermo Fisher Fusion Orbitrap mass spectrometer. Each fraction was subjected to a 95 min chromatographic method employing a gradient from 2–$25\%$ ACN in $0.1\%$ formic acid (FA) (ACN/FA) over the course of 65 min, a gradient of $50\%$ ACN/FA for an additional 10 min, a step to $90\%$ ACN/FA for 5 min, and a 15 min re-equilibration to $2\%$ ACN/FA. Chromatography was conducted in a “trap-and-load” format using an EASY-Spray source (Thermo, Rockford, IL, USA); trap column C18 PepMap 100, 5 µm, 100 A and the separation column was an EASY-Spray PepMap RSLC C18 2 µm, 100A, 75 µm × 25 cm (Thermo Fisher Dionex, Sunnyvale, CA, USA). The entire run was at a flow rate of 0.3 µL/min. TMT data acquisition utilized an MS3 approach for data collection, where survey scans (MS1) were performed in the Orbitrap utilizing a resolution of 120,000. Data-dependent MS2 scans were performed in the linear ion trap using a collision-induced dissociation (CID) of $25\%$, and reporter ions were fragmented using a high-energy collision dissociation (HCD) of $55\%$, detected in the Orbitrap using a resolution of 30,000 (MS3). The LC-MS acquisition data were searched using the SEQUEST HT node of Proteome Discoverer 2.4 (PD) (Thermo). The protein FASTA database was Rhesus macaque, SwissProt tax ID = 9544, version 2021-05-24 containing 44,389 sequences. Static modifications included TMT reagents on lysine and N-terminus (+229.163), carbamidomethyl on cysteines (+57.021), dynamic serine, threonine, and tyrosine phosphorylation (+79.966 Da), as well as dynamic modification of methionine oxidation (+15.9949). Parent ion tolerance was 10 ppm, fragment mass tolerance was 0.6 Da for MS2 scans, and the maximum number of missed cleavages was set to 2. ## 2.7. Cell Culture Primary HBMVECs were purchased from Cell Systems, Kirkland, WA, USA and were cultured as described previously [11]. Briefly, cells were cultured in complete classic medium with $10\%$ fetal bovine serum and culture boost (4Z0-500) and Bac-Off (4Z0-644). For cell propagation, passage reagent group (4Z0-800) was used according to the recommendations. Briefly, HBMVECs were washed with passage reagent group-1 (PRG-1), dissociated with PRG-2, and the enzymatic reaction stopped with ice-cold PRG-3. Cells were centrifuged at 200× g for 7 min at 4 °C. Culture boosts were added to the pellet, and the cells were resuspended in the complete classic medium. Cells were seeded 1:3 or 1:5 in T75 flasks coated with attachment factor (4Z0-210) and incubated at 37 °C with $5\%$ CO2 in $95\%$ relative humidity. Cells were fed with fresh media every 48 h and were used up to passage 9. ## 2.8. Antibodies and Chemicals Antibodies were purchased from the following suppliers: against Catalase (#14097), phospho-DRP1 (#3455), GAPDH (#2118), CORO1A (#92904), and LC3B (#2775) from Cell Signaling Technology, Danvers MA, USA; against CD81 (#sc-23962), CD63 (#sc-5275), and Flotillin-1 (#sc-25506) from Santa Cruz Biotechnology, Dallas, TX, USA; against β-actin (#A5441) from Sigma-Aldrich, St. Louis, MO, USA; against GFAP (#610565) from BD Transduction Laboratory, San Jose, CA, USA; against von Willebrand factor (VWF) (#ab6994), PECAM-1 (#ab28364) from Abcam, Cambridge, MA, USA; anti OMG (#12701-1-AP) and GABRA1 (#12410-1-AP) from Proteintech Group, Inc., Rosemont, IL, USA; and mitochondrial complex III subunit core 1 from Invitrogen Corporation, Fredrick, MD, USA. ## 2.9. Western Blotting We followed our previously described standard laboratory protocol to prepare the lysates from cell/exosome and to perform the immunoblots [11,32,33]. In brief, phosphatase and protease inhibitors containing ice-cold NP40 lysis buffer (Invitrogen, Frederick, MD, USA) was used to lyse either cells or exosomes. The clarified lysate protein concentration was measured by Pierce BCA protein assay (Thermo Scientific). The proteins were separated using a 4–$20\%$ SDS-PAGE gradient gel and transferred onto a PVDF membrane. A 1X blocking buffer (Abcam, Cambridge, MA, USA) was used to block the non-specific binding sites, and to dilute the primary antibodies. The membranes were washed with Tris-buffered saline (Bio-Rad, Hercules, CA, USA) containing $0.1\%$ Tween-20 (Sigma-Aldrich, St. Louis, MO, USA). Membranes were incubated overnight with primary antibodies at 4 °C, then membranes were washed and incubated again with respective secondary antibodies, either goat anti-rabbit IgG at 1:2500 dilution (#7074S, Cell Signaling Technology) or goat anti-mouse IgG at 1:5000 dilution (#7076P2, Cell Signaling Technology) at room temperature for 1 h. Chemiluminescence (LumiGLO, Gaithersburg, MD, USA) and autoradiography were used to visualize the final reaction. In some cases, immunoblot signals were captured using the ImageQuant Las 300 (GE Healthcare, Piscataway, NJ, USA) system. Immune band densitometry was performed using ImageJ Software (NIH, Bethesda, MD, USA, http://imagej.nih.gov/ij/ accessed on 4 November 2021). ## 2.10. Transwell Primary Brain Endothelial Cell Permeability Assay Conventional in vitro BBB modeling was conducted by culturing primary HBMVECs grown in 2D as a flat monolayer by following the published protocols [35]. Permeability across the monolayer of HBMVECs was measured by using transwell units (24-well format, 0.4 µm pore size with high pore density PET track-etched membrane, cat # 353495), which were made to fit in a 12-well plate, purchased from Corning Incorporated, Corning, NY, USA. To create the BBB model, 1 × 105 cells were seeded onto the transwell inserts and cells were allowed to grow for 2 days in complete classic medium. After endothelial cells become confluent on the transwell, cells were treated in fresh culture medium with 10 µg/mL of either Patient-Exo or Control-Exo for 24 h. The cell monolayer’s ability to limit the penetration of a high molecular weight compound was measured by adding 10 µg/mL fluorescein isothiocyanate-labeled dextran (FITC-dextran; molecular weight: 150 kDa, Sigma-Aldrich, St. Louis, MO, USA) to the culture transwell inserts. In the absence of primary HBMVEC, FITC-dextran added to the culture inserts served as controls. After incubation for 10, 30, 60, and 120 min, 20 µL of medium was collected from the lower compartment, and the fluorescence was measured with a spectrophotometer (BioTek Instruments, Winooski, VT, USA) set to $\frac{485}{20}$ nm excitation and $\frac{528}{20}$ nm emission. ## 2.11. Immunofluorescence, Confocal Microscopy, and Image Analysis After experimentation, cultured HBMVECs were fixed with $4\%$ PFA for 15 min at room temperature and washed three times with PBS (5 min per wash). Prior to staining, fixed cells were permeabilized with PBST (PBS with $0.1\%$ Triton X-100) for 20 min. For staining using antibodies, cells were blocked for non-specific binding using PBS containing $5\%$ donkey serum (Sigma-Aldrich Cat. No.: D9663) for 1 h at room temperature, followed by overnight incubation at 4 °C with a rabbit PECAM-1 (CD31) polyclonal antibody (BiCell Scientific Cat. No.: 01004) at a 1:200 dilution in PBS with $5\%$ donkey serum. The following morning, cells were rinsed once with PBS, and then washed for 2 h at room temperature on a rocker, replacing the PBS 2–3 times during this period. Cells were then incubated, protected from the light with a donkey anti-rabbit IgG(H+L) highly cross-adsorbed secondary antibody conjugated with Alexa Fluor 488 (Invitrogen Cat. No.: A-21206) at a 1:500 dilution for 2 h at room temperature on a rocker. Finally, cells were rinsed with PBS once to remove excess unbound secondary antibody, then washed for 2 h at room temperature on a rocker, with the PBS replaced 2–3 times during this period, and then mounted using a ProLong Glass antifade mountant with NucBlue stain (Invitrogen Cat. No.: P36981). For F-actin filament staining, after fixation and permeabilization described above, cells were incubated with Alexa Fluor 488 Phalloidin (Invitrogen Cat. No.: A12379, 300 U, stock concentration 400×) at a 1:400 dilution in PBS containing $5\%$ donkey serum for 30 min at room temperature on a rocker. Then, the cells were rinsed once with PBS, and then washed for 20 additional min with the same solution on a rocker and protected from light. After staining, cells were mounted as described above. Antifade mountant was allowed to cure overnight at room temperature, protected from light. Fluorescence images were collected using a 40× water immersion objective on an Andor Dragonfly 202 (+Leica DMI8) high speed confocal imaging platform equipped with solid state 405 nm and 488 nm smart diode lasers and a Zyla PLUS 4.2 Megapixel sCMOS camera. Using ImageJ Fiji, the raw integrated density for each immunofluorescence image was calculated. Then, using the DAPI staining channel, the number of nuclei were determined via particle analysis. Finally, the raw integrated density calculations were normalized by the number of cells/nuclei. Data are presented as the mean ± SEM of the normalized integrated fluorescence density for each group with the control experiments mean as the reference, i.e., mean of control group being 100 percent. Statistically significant differences were evaluated using either parametric t tests or a one-way ANOVA test with Tukey post hoc, * $p \leq 0.05.$ ## 2.12. Statistical Analysis Only high scoring peptides were included for proteomic analysis, using a false discovery rate (FDR) of <$1\%$. Only one unique high-scoring peptide was essential for inclusion as an identified protein in our results. Proteome Discoverer was also used to determine quantitative differences between biological groups. Quantitative data were collected using a t-test analysis on grouped biological replicates and we performed pair-wise comparisons for fold-change. The normalized abundance quantity of a biological replicate was calculated by averaging four experimental replicates. The data are presented as mean ± standard deviation (SD). For normal distribution, the data sets were assessed by the Shapiro–Wilk or Kolmogorov–Smirnov test, followed by unpaired t test with Welch correction for normally distributed data. When the data did not pass the normality test, a non-parametric Mann–Whitney test was performed, as indicated in the figure legends. The statistical analysis was performed using GraphPad Prism version 9.0.0 for Windows, and $p \leq 0.05$ was considered statistically significant. Hierarchical clustering analysis (HCA) was performed in R Studio (version 1.4.1103) using “Manhattan” clustering and “complete” linkage method. ## 3.1. Characterization of Circulating Plasma Exosomal Proteome of SHIV-Infected and Uninfected RM Initially, we measured the viral load in plasma and in isolated exosomes (crExo) by qRT-PCR. The plasma qRT-PCR results indicated that two SHIV+ samples had low viral copy numbers (3.1 and 3.4 equivalent (Eq.) LOG copies) and one SHIV+ sample was less than 1.9 Eq. LOG copies (the detection limit). All uninfected ($$n = 3$$) plasma samples were negative. In the exosomal fraction, the viral load was less than 1.9 Eq. LOG copies in the SHIV+ samples ($$n = 3$$), and negative in uninfected samples ($$n = 3$$) (data not shown). Although we isolated exosomes from the commercially available exosome isolation kit, we further confirmed the size (nm) and concentration (particles/mL) by the ZetaView analyzer of SHIV-/CTL-Exo ($$n = 5$$/group). Interestingly, both the size and concentration of SHIV-Exo were significantly lower than CTL-Exo (Figure 1a,b). By proteomic analysis, a total of 5654 proteins were quantified, of which 236 proteins (~$4\%$) were significantly, differentially expressed (DE) between SHIV-/CTL-Exo ($$n = 3$$/group) (Figure 1c). Two or more unique peptides were detected in $85\%$ ($\frac{4777}{5654}$) of quantified proteins, and in $89\%$ ($\frac{211}{236}$) of significant DE proteins, indicating the depth of analysis (Figure 1d,e). The hierarchical cluster analysis (HCA) of significant DE proteins were presented in Figure 1f. Moreover, the HCA of top 50 significant up-/down-regulated proteins in SHIV-Exo were presented in Figure 2a,b. We used PCA to decrease the data dimensions for simpler interpretation. According to PCA analysis on all protein expression data, we observed that the CTL-Exo (in red) are clustered separately from the SHIV-Exo (in green). The percentage of variance indicates how much variance was explained by principal component 1 (PC1) and principal component 2 (PC2) and it was $25.2\%$ and $21.6\%$, respectively. Thus, our preliminary proteome comparisons reveal that there are substantial differences between CTL-Exo and SHIV-Exo (Figure 2c). ## 3.2. Hallmark Exosomal Proteins Were Quantified by Proteomic Analysis in crExo of SHIV-Infected and Uninfected RM Like a typical cell membrane, the exosomal membrane consists of lipids and proteins. Tetraspanin proteins CD9, CD63, CD81, CD82, CD151, Tetraspanin-5 (TSPAN5), TSPAN9, and TSPAN14 were abundantly expressed in both SHIV-Exo and CTL-Exo (Figure 3a). Several cytoskeletal proteins were quantified in both SHIV-Exo and CTL-Exo. The relative abundance of actin alpha 1, skeletal muscle (ACTA1), tubulin alpha chain (TUBA1B), tubulin beta chain (TUBB), myosin light chain 2 (MYL2), myosin heavy chain 11 (MYH11), vimentin (VIM), and radixin (RDX) were low in both SHIV-Exo and CTL-Exo. However, the relative abundance of fibronectin (FN1), ezrin (EZR), keratin 1 (KRT1), and keratin 2 (KRT2) were high in both SHIV-Exo and CTL-Exo. Interestingly, the abundance of RDX was significantly higher in CTL-Exo than SHIV-Exo (Figure 3b). Cytosolic enzymes such as glucose-6-phosphate isomerase (GPI), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), fructose-bisphosphate aldolase A (ALDOA), fructose-bisphosphate aldolase C (ALDOC), 2-phospho-D-glycerate hydro-lyase (gamma enolase; ENO1), and pyruvate kinase PKLR (PKLR) were expressed equally in both SHIV-Exo and CTL-Exo (Figure 3c). The exosomes composition reflects to some extent the composition of multivesicular bodies (MVBs). In fact, proteins associated with MVBs, such as tumor susceptibility 101 (TSG101), clathrin light chain (CLTA), clathrin heavy chain (CLTC), syntaxin-7 (CTX7), and syntaxin-8 (CTX8), were also expressed equally in both SHIV-Exo and CTL-Exo (Figure 3d). Exosomes have been shown to be enriched in cholesterol, sphingomyelin, and glycosphingolipids that play important roles in signaling and sorting. In this study, NPC intracellular cholesterol transporter 1 (NPC1), stomatin-like protein 2 (STOML2), stomatin-like protein 3 (STOML3), flotillin-1 (FLOT1), flotillin-2 (FLOT2), sphingosine kinase 2 (SPHK2), sphingosine 1-phosphate receptor 1 (S1PR1), and sphingosine-1-phosphate lyase 1 (SGPL1) were abundantly expressed in both SHIV-Exo and CTL-Exo (Figure 3e). The CD63, CD81, GAPDH, and FLOT1 expression was further validated by Western blotting (Figure 3f). ## 3.3. Different CNS Cell Markers Were Abundantly Detected in SHIV-/CTL-Exo Interestingly, we observed that brain microvascular endothelial cell specific von Willebrand factor (VWF) and platelet and endothelial cell adhesion molecule-1 (PECAM-1), as well as microglial cell markers beta-hexosaminidase (HEXB), spalt-like transcription factor 1 (SALL1), receptor protein-tyrosine kinase (MERTK), and coronin 1A (CORO1A), were differentially expressed in SHIV-/CTL-Exo. In addition, thought provoking, astrocyte cell markers such as glial fibrillary acidic protein (GFAP), protein S100 (S100B), aquaporin-4 isoform a (AQP4), and glutamine synthetase (GLUL) were abundantly less expressed both in SHIV-/CTL-Exo. Two oligodendrocyte markers: myelin basic protein (MBP) and myelin-oligodendrocyte glycoprotein (MOG) were also less expressed in SHIV-/CTL-Exo (but not oligodendrocyte-myelin glycoprotein (OMG)). Moreover, several neuron-specific proteins, including neurofilament heavy (NEFH), neurofilament light polypeptide (NEFL), 160 kDa neurofilament protein (NEFM), synaptophysin (SYP), T-box brain protein 1 (TBR1), stathmin 1 (STMN1), alpha-internexin (INA), axonal membrane protein GAP-43 (GAP43), GABA(A) receptor subunit alpha-1 (GABRA1), and CLPTM1 regulator of GABA type A receptor forward trafficking (CLPTM1), were also quantified in both SHIV-/CTL-Exo (Figure 4a). The expression of several CNS cell markers, specifically VWF, PECM-1, CORO1A, GFAP, OMG, and GABRA1 in SHIV-/CTL-Exo, was further validated by Western blotting (Figure 4b). ## 3.4. Proteins Involved in Viral Reactivation, Inflammation, and Neuropathology-Associated Interactive/Signaling Proteins Were Significantly Higher in SHIV-Exo Than CTL-Exo Pan et al. [ 36] reported that heat shock factor 1 (HSF1) positively regulates transcription of latent HIV infection. We observed a significantly greater increase of HSF1 in SHIV-Exo than CTL-Exo, possibly indicating the positive regulation of latent infection in SHIV-infected RM. Plasma proteins involved in inflammation and complement dysregulation support diagnosis and outcome predictions of mild cognitive impairment and AD. Our proteomic study showed that the abundance of complement factor H (CFH), complement component 8 subunit (C8B), and thioredoxin domain-containing protein (TXN2) were significantly higher in SHIV-Exo than CTL-Exo. Platelet glycoprotein 1b subunit alpha (GP1BA), a thromboinflammatory axis in cardiovascular pathologies, was also significantly higher in SHIV-Exo (Figure 5a). In SHIV-Exo, neuropathology-associated interactive proteins such as amyloid beta precursor protein binding family B number 1 (APBB1), chromogranin A (CHGA), chromogranin B (CHGB), and peptidylprolyl isomerase (FKBP2) were significantly higher in SHIV-Exo than CTL-Exo (Figure 5b). Similarly, neuropathology-associated signaling proteins such as cyclin-H (CCNH), CUGBP Elav-like family member 3 (CELF3), RPTOR independent companion of MTOR complex 2 (RICTOR), CD74, and LIM domain kinase 1 (LIMK1) were also significantly higher in SHIV-Exo than CTL-Exo (Figure 5c). Age-adjusted p-value was also significant ($p \leq 0.05$) for HSF1, CFH, TXN2, APBB1, CCNH, RICTOR, and LIMK1 (Supplementary Materials File S1). ## 3.5. Proteins Involved in Mitochondrial Biogenesis and ATP Production Were Reduced in SHIV-Exo Than CTL-Exo Mitochondrial (Mt) antiviral signaling proteins (MAVS) as well as Mt fission-related Mt fission 1 (FIS1), Mt fission factor (MFF), and Mt fission regulator 1 (MTFR1L) proteins were significantly less expressed in SHIV-Exo (Figure 6a). Proteins involved in ATP production such as NADH-ubiquinone oxidoreductase chain 5 (ND5), Mt complex I subunit B13 (NDUFA5), cytochrome c oxidase subunit 4 isoform 2 (COX4l2), cytochrome c oxidase assembly protein COX20 (COX20), ATP synthase subunit g (ATP5L), ATP synthase subunit alpha (ATP5F1A), ATP synthase subunit d (ATP5PD), mitochondrial ribosome recycling factor (MRRF), 2-oxoglutarate dehydrogenase-like, mitochondrial isoform a (OGDHL), 2-oxoglutarate dehydrogenase-like, and mitochondrial isoform a (COQ6) were also significantly less expressed in SHIV-Exo than in CLT-Exo (Figure 6b,c). Age-adjusted p-value was also significant ($p \leq 0.05$) for MAVS, FIS1, MTFR1L, NDYFA5, COX4l2, COX20, ATP5L, ATP5F1A, MRRF, and COQ6 (Supplementary Materials File S1). ## 3.6. Proteins Involved in Autophagy, Endosomal Recycling, Exocytosis, Sprouting Angiogenesis, Cytoskeleton Organization, and Vesicle Transport Are Downregulated in SHIV-Exo There is increasing evidence indicating that defective autophagy-lysosome pathways are associated with neurodegenerative diseases. Lysosomal associated membrane protein 2 (LAMP2) has been recognized as a receptor for the selective import and degradation of cytosolic proteins in the lysosome, or chaperone-mediated autophagy [37]. In this study, the expression of LAMP2 was significantly impaired in SHIV-Exo. Moreover, the autophagy-related protein 2 homolog B (ATG2B), and autophagy-related protein 9A (ATG9A) were significantly less expressed in SHIV-Exo. Similarly, CDGSH iron-sulfur domain-containing protein 2 (CISD2), an autophagy regulator, was also significantly less expressed in SHIV-Exo (Figure 7a). The expression of several Ras-related proteins: Rab-3C (RAB3C), -5C (RAB5C), and -13 (RAB13) were significantly less expressed in SHIV-Exo (Figure 7b) as were proteins involved in endosomal recycling: (sorting nexin 4; SNX4), exocytosis (synaptogyrin; SYNGR2), sprouting angiogenesis (Jumonji domain-containing 6, arginine demethylase and lysine hydroxylase; JMJD6), cytoskeleton organization (calponin; CNN2), and neurobehavioral problem (PHD finger protein 21A; PHF21A) (Figure 7c). Age-adjusted p-value was also significant ($p \leq 0.05$) for LAMP2, CISD2, RAB3, SX4, PHF21A, JMJD6, and SYNGR2 (Supplementary Materials File S1). ## 3.7. HIV-Infected and cART-Treated Patient-Exo Decreased the Expression of ROS Scavengers, BBB- and Autophagy-Related Proteins as well as Proteins Involved in Mitochondrial Fusion and Electron Transport Chain in Primary HBMVECs The expressions of catalase (CAT) and microtubule-associated proteins 1A/1B light chain 3B type-II (LC3B) were downregulated when cells were exposed with Patient-Exo. Usually, the active autophagy is measured by changes in LC3 localization: tracking the level of conversion of LC3-I to LC3-II provides an indicator of autophagic activity that was significantly impaired in cells exposed with Patient-Exo. In addition, the expressions of phosphorylated dynamin-related protein 1 (pDRP1) and mitochondrial complex-III (MC-II) were downregulated due to exposure with Patient-Exo in primary HBMVEC (Figure 8a,b). ## 3.8. Patient-Exo Increases in BBB Permeability Possibly Due to Loss of PECAM-1 and Actin Cytoskeleton in Primary HBMVECs The transwell migration assay indicated that the brain endothelial cell permeability was significantly increased when cells were treated with Patient-Exo compared with controls (Figure 9a,b). Immunofluorescence assay showed that the expression of PECAM-1 was significantly impaired in cells exposed with Patient-Exo (Figure 9c,d). Several studies have demonstrated that BBB permeability changes as a result of actin reorganization [38,39,40]. In our proteomic study, several actin-related proteins were abundantly less expressed in SHIV-Exo than in CTL-Exo. Interestingly, the expression actin-depolymerizing factor (GSN) was significantly higher in SHIV-Exo (Figure 10a). Our immunofluorescence study showed that HBMVEC exposed with Patient-Exo lost the typical architecture of filamentous actin (F-actin) and accumulated it within the cells (Figure 10b). ## 4. Discussion Extracellular vesicles/exosomes have been involved in regulating the progression of various neurodegenerative diseases by supplying pathogenic proteins or molecules associated with such diseases [18,19,20,21,22,23]. Recent studies have demonstrated the ability to isolate brain-generated exosomes from blood, and exosomes seem to be minimally invasive biomarkers for various neurodegenerative diseases [41]. Moreover, findings have established the possible role of exosomes as diagnostic biomarkers of HAND [25,26,42]. Using proteomics, Guha et al. [ 25] reported that some proteins in CNS cell-specific exosomes were higher in HIV patients with HAND compared with those without HAND. In this study, we have characterized the circulating plasma exosomal (crExo) proteins in SHIV-infected and uninfected RM and their possible link with neuropathogenesis. We applied discovery-based TMT-tag mass spectrometry analysis to compare the relative crExo protein expression in infected and uninfected RM. In the last decade, there has been an exponential increase in the use of discovery-based proteomic approaches in translational research, due largely to the progress of state-of-the-art mass spectrometry (MS/MS). The measurement accuracy is pronounced, and it is possible to identify and quantify peptides and proteins in a sensitive and high-throughput manner. The quantification of the total number of proteins in exosomes has been different in these studies. Recently, Dr. Okeoma and her research group quantified 625 proteins with higher-stringency (≤$1\%$ FDR, and ≥2 unique peptides) from HIV(+)/(−) plasma exosomes [43]. However, in a recent CSF EVs proteomic study, more than 2700 proteins were identified in HIV-infected patients [25]. The chemical labeling methods: either ITRAQ (isobari tags for relative and absolute quantification)- or TMT-tags, which allow high multiplexing are better-suited for multiple samples [44], and this method allows for the identification of even low abundance proteins. This strategy is successfully reflected in our TMT-tag LC-MS/MS analysis and we quantified 5654 proteins (<$1\%$ FDR) and two or more unique peptides were detected in $85\%$ of quantified proteins. CNS cell-specific proteins were differentially expressed in plasma crExo. Several exosomal hallmark proteins (tetraspanins, enzymes, lipid rafts, cytoskeletal, and endosome-specific proteins) that were abundantly expressed in both CTL-/SHIV-Exo indicated the successful isolation of crExo from plasma. The vesicle size, shape, concentration, and presence of exosomal markers exhibited similarities that were isolated from either human serum or plasma, suggesting that serum and plasma are equally useful for isolation of blood exosomes [45]. Exosomes originating in the CNS can cross the BBB, can be isolated from the blood [46] and are an attractive source to identify ongoing disease progression in the CNS [47,48]. Our study supports this concept. Brain microvascular endothelium-, microglia-, astrocyte-, oligodendrocyte-, and neuron-specific proteins were either quantitatively or qualitatively measured in crExo. Upregulated proteins in SHIV-Exo may link to HIV-associated neuropathogenesis. HIV infection in the CNS results from transmigration of infected CD4+ T cells and/or monocytes through the BBB. However, these migrated cells in the CNS do not constitute an HIV reservoir since they have a very short half-life. On the other hand, microglial cells, with their long half-life of years [49], are highly susceptible to HIV infection [50,51], support productive infection [52], and serve as a major CNS reservoir of latent provirus. Moreover, inadequate cART supply in CNS contributes to the persistence of infection in microglial cells [53]. Using a macaque model for AIDS and HAND, Clements et al. [ 54] reported that more than $80\%$ of infected animals develop simian immunodeficiency virus (SIV)-associated neurological symptoms within 90 days. As a host factor, HSF1 significantly contributes to HIV transcription and is essential for HIV latent reactivation [36]. In our study, the abundance of HSF1 was significantly higher in SHIV-Exo than in CTL-Exo, possibly promoting productive infection and deleterious neuroinflammation in CNS. HIV both directly and indirectly increases neuroinflammation and the development of clinical symptoms of HAND. Several studies have shown that exosomes transport both viral and host proteins that facilitate neuroinflammation [55,56,57]. Inflammation and complement dysregulation were important components of AD pathogenesis. To identify inflammatory plasma biomarkers in mild cognitive impairment (MCI) and AD patients, it has been reported that complement factor H (CFH), complement component C3, and C5 were significantly higher in MCI ($$n = 199$$) than control subjects ($$n = 259$$). Additionally, plasma soluble complement-receptor 1, -C4, and -C5 were significantly high in AD patients ($$n = 262$$) [58]. Moreover, the “thrombo-inflammatory” nature of VWF-GP1BA axis becomes progressively identified in different cerebrovascular pathologies [59]. Interestingly, in our study, plasma exosomal CFH and C8B were significantly higher in SHIV-Exo than CTL-Exo. We also observed that both VWF and GP1BA were significantly high in SHIV-Exo. Another common feature of neurodegenerative diseases is oxidative stress [60]. Antioxidant TXN2 is an important cellular component against oxidative stress, which we showed was highly expressed in SHIV-Exo, possibly linked to neuropathogenesis documented in previous studies [61,62,63]. One manifestation of AD is the accumulation of amyloid β (Aβ) peptides in the brain originating from the amyloid precursor protein (APP). APBB1 is an adapter protein that forms a transcriptionally active complex with APP and plays a vital role in Aβ binding and positive regulation of the apoptotic process. We found that APBB1 was significantly upregulated in SHIV-Exo. There is a strong correlation between APP, secretory neuropeptides, CHGA, and CHGB [64]. CHGA induces a neurotoxic phenotype in brain microglial cells [65] and may directly modulate synaptic activity [66]. Using postmortem brain of AD patients, Lechner et al. [ 67] reported that ~$30\%$ of Aβ plaques were co-labelled with CHGA (mostly found in pyramidal neurons), and $15\%$ with CHGB (largely located in interneuron). CHGA is concentrated in the Levy bodies in PD in the Pick bodies, and in the swollen neurons in Pick’s disease [68,69] and tends to accumulate in the senile and pre-amyloid plaques in AD [70]. In addition, elevated levels of CHGA have been measured in the CSF of AD patients [71]. Now it is known that EVs/exosomes can transport their cargo bidirectionally from the brain to the systemic circulation. In our study, both CHGA and CHGB were significantly higher in SHIV-Exo than CTL-Exo, indicating they are increased in the infected RM and possibly associated with the progression of HAND. The CNS is an important HIV reservoir, and CCNH regulate transcription by RNA polymerase II and participate in HIV-1 early elongation complex formation, supporting viral infection and replication in the CNS. Moreover, mTOR activity of RNA-binding protein CELF3 in tau splicing may be a factor promoting neuronal pathology [72]. The signaling protein RICTOR is critical to mTOR function, and Aβ accumulation is associated with an increase in mTOR signaling in postmortem AD brain tissues [73]. Bryan et al. [ 74] reported that the expression of CD74 is increased in neurofibrillary tangles of AD patients. Aβ42 peptides caused spine degeneration and neuronal hyperexcitability via LIMK1-dependent mechanisms in rat hippocampal neurons [75] and a significant increase of phosphorylated LIMK1-positive neurons was identified in areas affected with AD pathology [76]. We found that the expression of CCNH, CLF3, RICTOR, CD74, and LIMK1 was significantly high in SHIV-Exo, indicating their possible link to neuropathogenesis. Downregulated proteins in SHIV-Exo may indicate CNS health imbalance. Mitochondrial function is crucial to organs with a high metabolic rate such as the brain [77]. Several mitochondrial proteins have been found in exosomes. Both Caicedo et al. [ 78] and Goetzel et al. [ 79] showed that several mitochondrial proteins including complex-I (subunit 6) and complex-III (subunit 10) were significantly lower in plasma EVs of patients with major depressive disorder than their matched controls. Recently, Chi et al. [ 80] reported that plasma neuroexosomal NADH ubiquinone oxidoreductase core subunit S3 (NDUFS3) and succinate dehydrogenase complex subunit B (SDHB) levels were significantly lower in AD and in progressive mild cognitive impairment (MCI) than in cognitively normal subjects. Moreover, they observed that plasma neuroexosomal NDUFS3 and SDHB levels were lower in progressive MCI than in stable MCI subjects. Our study supports these findings and we observed that several mitochondrial biogenesis and ETC complex proteins were significantly less expressed both in SHIV-Exo and in HBMVECs exposed with HIV+ Patient-Exo. Defective autophagy, endosomal recycling, and exocytosis pathways are significantly linked with neuropathogenesis. Guo et al. [ 81] reported that α-synuclein preformed fibrils decreased autophagy flux due to degradation of LAMP2 in activated microglia. LAMP-2 deficiency leads to hippocampal dysfunction [82]. Axonal autophagosome maturation defect due to failure of ATG9A sorting underlies pathology in adaptor protein-4 deficiency syndrome [83]. Moreover, CISD2 deficiency enhanced AD pathogenesis. Therefore, downregulated expression of LAMP2, ATG9A, and CISD2 in SHIV-Exo and LC3B-II in HBMVECs treated with HIV+ Patient-Exo may be linked to HAND. A subset of RABs is involved in autophagy regulation, including RAB2 [84], RAB3 [85], RAB5 [86], and RAB18 [87]. In our study, RAB3C, RAB5C, and RAB13 were significantly downregulated in SHIV-Exo. RAB-associated dysfunctions are linked with several neuropathological disorders [88,89]. RABs are critical for maintaining neuronal communication, as well as for normal cellular physiology. Therefore, cellular defects of RAB elements severely impact normal brain functions, leading to development of neurodegenerative diseases [89]. In cells, RAB-proteins are inevitable for endocytic and exocytic pathways. Sorting nexins (SNXs) dysfunction has been linked to several neurodegenerative diseases including AD, PD, and Down’s syndrome [90]. SNX4 is expressed in the brain and SNX4 protein levels are decreased by $70\%$ in brains of severe AD cases [91]. Deletion of CNN2 increases macrophage migration and phagocytosis [92]. Disruption of the PHF21A gene triggers syndromic intellectual disability with craniofacial anomalies, and neurobehavioral problems including autism [93]. JMJD6 regulates the VEGF-receptor 1 splicing, thereby controlling angiogenic sprouting [94]. In neuronal cells, SYNGR2 modulates the localization of synaptophysin into synaptic-like MVs and play a role in the formation and/or the maturation of these vesicles. Therefore, downregulated expression of SNX4, CNN2, PHF21A, JMJD6, and SYNGR2 in SHIV-Exo may relate to neuropathogenesis. Increased BBB permeability by crExo may be an initiating event for HIV-associated neuropathogenesis. BBB injury is common in patients with HIV-associated dementia and is a frequent feature of HIV encephalitis, although the process is not completely understood [95,96,97]. Together with inflammatory mediators (e.g., cytokines and chemokines), several viral proteins may damage the BBB integrity and facilitate BBB permeability [98]. One study reported that microglia-derived HIV-Nef+ exosomes directly impact BBB integrity and permeability [55], while using HBMVEC, Leon et al. [ 99] showed that plasma EVs from patients with preeclampsia disrupt BBB integrity. Using a similar approach, we have shown that HIV+ Patient-Exo significantly increased BBB permeability in primary HBMVEC. Interestingly, the expression of ZO-1, ZO-2, and JAM-A was not significantly downregulated (data not shown), but the expression of PECAM-1 was significantly impaired in HBMVECs after exposure to HIV+ Patient-Exo. Using the same BBB model on primary mouse brain microvascular endothelial cells, Wimmer et al. [ 100] showed that lack of endothelial PECAM-1 increased BBB permeability, although cells maintained intact junctional architecture. In addition, during LPS-induced endotoxemia, blood vessels of PECAM-1-deficient mice exhibited increased BBB permeability [101]. Furthermore, PECAM-1−/− mice displayed impaired BBB integrity and accelerated immune cell infiltration into the CNS [102]. Various studies have also shown that BBB permeability changes due to actin reorganization [38,39,40] and our present findings supports that concept. There is recognition between filamentous actin (F-actin) that makes up the cortical actin ring and stress fibers. During inflammation, stress fibers increase in endothelial cells [103] that increase intracellular tension, reorganize the adhesion complex structure, and generate gaps in the intracellular connections [104], increasing permeability. Therefore, the cortical actin ring is required for adhesion complex structure and BBB integrity [105]. We observed that SHIV-Exo simultaneously expressed a significantly high level of actin depolymerizing factor protein and relatively less expression of several actin cytoskeleton proteins. Moreover, we showed that HBMVECs lose their F-actin cytoskeleton organization once the cells were exposed to HIV+ Patient-Exo. Limitations and potentials of their research. There are several limitations in this study. [ 1] To avoid complexity, we focused only on the host proteins which are possibly linked to HIV-associated neuropathogenesis. However, viral proteins, especially Matrix protein for HIV-1 [106] and other viruses [107], play an important role in viral evasion against antibodies and the ability of HIV-1 Matrix protein p17 to penetrate into the brain possibly influences HAND progression [108]. [ 2] There are possible differences in the behaviors and properties of SHIV and HIV variants. Therefore, we cannot assume that SHIV-Exo will have the same effect as HIV-infected Patient-Exo on HAND. [ 3] Small significant differences for some proteins could be the result of variations over a period of time; therefore, we have to focus on a longitudinal study to ensure that cross-sectional results being observed in this study could be replicated at different time points. [ 4] Since our IRB approval is pending, we only included one of each commercially available patient plasma and healthy donor plasma samples in this study. [ 5] Several studies reported that monocyte chemoattractant protein-1 (CCL2/MCP-1) in plasma is a marker for HAND [109,110,111]. However, in our study, CCL2/MCP-1 was not quantified in either control or SHIV-infected plasma exosomes. ## 5. Conclusions In the brain, EVs/exosomes are engaged in several physiological processes, including BBB permeability, neurogenesis, cell communication, neuronal stress response, synaptic plasticity, and others. Therefore, EVs/exosomes are implicated in the pathology of many neurodegenerative diseases. Many studies have shown the ability of exosomes to isolate brain-generated exosomes from blood, while apparently being minimally invasive biomarkers for various neurodegenerative diseases including HAND. Much is already known about the contribution of CNS cells in HAND. 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--- title: Identification of Potential Inhibitors for the Treatment of Alkaptonuria Using an Integrated In Silico Computational Strategy authors: - Sumera Zaib - Nehal Rana - Nadia Hussain - Hanan A. Ogaly - Ayed A. Dera - Imtiaz Khan journal: Molecules year: 2023 pmcid: PMC10058836 doi: 10.3390/molecules28062623 license: CC BY 4.0 --- # Identification of Potential Inhibitors for the Treatment of Alkaptonuria Using an Integrated In Silico Computational Strategy ## Abstract Alkaptonuria (AKU) is a rare genetic autosomal recessive disorder characterized by elevated serum levels of homogentisic acid (HGA). In this disease, tyrosine metabolism is interrupted because of the alterations in homogentisate dioxygenase (HGD) gene. The patient suffers from ochronosis, fractures, and tendon ruptures. To date, no medicine has been approved for the treatment of AKU. However, physiotherapy and strong painkillers are administered to help mitigate the condition. Recently, nitisinone, an FDA-approved drug for type 1 tyrosinemia, has been given to AKU patients in some countries and has shown encouraging results in reducing the disease progression. However, this drug is not the targeted treatment for AKU, and causes keratopathy. Therefore, the foremost aim of this study is the identification of potent and druggable inhibitors of AKU with no or minimal side effects by targeting 4-hydroxyphenylpyruvate dioxygenase. To achieve our goal, we have performed computational modelling using BioSolveIT suit. The library of ligands for molecular docking was acquired by fragment replacement of reference molecules by ReCore. Subsequently, the hits were screened on the basis of estimated affinities, and their pharmacokinetic properties were evaluated using SwissADME. Afterward, the interactions between target and ligands were investigated using Discovery Studio. Ultimately, compounds c and f were identified as potent inhibitors of 4-hydroxyphenylpyruvate dioxygenase. ## 1. Introduction Alkaptonuria (AKU) is a rare monogenic hereditary multisystemic disease inherited in an autosomal-recessive pattern [1]. The disease is known since 1500 BC as several reports have suggested AKU symptoms in Egyptian mummies of that time [2]. It is ultra-rare as its incidence is 1:250,000 to 1,000,000 with most reported cases in India, Slovakia, and Jordan due to consanguineous marriages [3]. It was first described by Dr. Archibald Garrod who described it as genetic disease and coined the concept of “inborn errors of metabolism” [4]. Furthermore, Boedeker suggested the name of AKU which was derived from the term Alkapton. The term Alkapton is of Greek origin that is kápton which means “to gulp down” [5]. It is characterized by high levels of serum and urine homogentisic acid (HGA) due to mutations in the nucleotide sequence of homogentisate 1,2-dioxygenase (HGD) [1]. These alterations in the nucleotide sequence interfere with functioning of HGD [6]. HGD metabolizes HGA, an intermediate product of phenylalanine/tyrosine pathway which is converted to fumarate and acetoacetate in normal individuals but not in AKU as shown in Figure 1 [7,8]. HGA being a reducing agent is oxidized by a slow spontaneous irreversible process imparting black color to the urine and was first explained as “as black as ink” by Scribonius in 1584 [9,10]. In addition to the blackening of urine, the eyes and ears also develop pigmentation, but it takes two to three decades to be visible externally [10]. The pigment is actually a bluish-black melanin-like pigment formed by the oxidation of HGA in connective tissues by a process known as ochronosis [3]. This melanin-like pigment is actually benzoquinone acetic acid [11]. Moreover, the patients also suffer from knee and backbone pain that originates gradually in two to three decades [12]. Additional manifestations of AKU include arthritis, aortic stenosis, joint damage, musculoskeletal tears, renal stones, and calcification of the vascular system [8,13,14,15]. The destruction of joints in AKU is attributed to the alterations in extracellular matrix, deterioration of collagen fibers and loss of proteoglycans [2,16]. Consequently, the cartilage becomes stiff and unable to bear the mechanical stress. This whole process begins in calcified tissues and continues to the hyaline cartilage inducing remodeling and destruction of subchondral plate [17]. It is not understood how HGA interacts with collagen matrix at the molecular level. A microscopic analysis of pigmented cartilage revealed a close relationship between early pigmentation and collagen fiber periodicity [10]. Although collagen fibers abide by the pigmentation, but biomechanical and metabolic alterations, such as those that take place in cartilage as a result of ageing naturally, make tissues vulnerable to ochronosis [10]. After the depletion of protective components such as proteoglycans and glycosaminoglycans, HGA easily binds with collagen [18]. In case of bone remodeling, two factors namely RANKL/osteoprotegerin (OPG) ratio and the Wnt/β-catenin signaling pathway are vital. RANKL/osteoprotegerin (OPG) ratio has significant role in the formation of osteoclast; on the other hand, Wnt/β-catenin signaling pathway controls the division and differentiation of osteoblasts [19]. In AKU, elevated levels of HGA inhibits Wnt signaling pathway by induced deterioration of osteoblast functionality [20]. Cardiac symptoms linked to alkaptonuria are minimal. The most common is aortic ochronosis that causes aortic stenosis and requires surgical treatment. The pulmonary and tricuspid valves are the subsequent rarely afflicted, followed by the mitral valve [21]. Certain patients have indeed reported involvement of the aortic, sternal, and coronary arteries. Despite the fact that alkaptonuric patients’ aortic walls have pigmentation, there is evidence of reduced aortic distensibility [21]. Although it is rare, but some AKU patients can also manifest neurological symptoms such as Parkinsonism. Basically, HGA fuse with the melanin to form a complex in substantia nigra which interferes with the formation of dopamine-melanin complex [22]. Patients may also suffer from depression due to physical impairment from pigment buildup in the skin, darkened urine, acute arthralgia and rigidity, and recurrent surgeries [22]. The musculoskeletal abnormalities in AKU are often deferred till the fourth decade of life and frequently precedes with the onset of spinal arthropathy [23]. Recently, AKU has been categorized as secondary amyloidosis because of the deposition of serum amyloid A (SAA) fibers. The SAA is a biomarker of inflammation as produced at 100–1000 times in higher amounts than normal plasma levels (4–6 mg/L) during chronic inflammation [24]. SAA fibers are mainly produced by the under expression of cathepsin D in the chondrocytes in AKU patients which has role in regulating the levels of secondary amyloid fibrils [25]. In addition to high levels of SAA fibers, HGA can also disrupt the Hedgehog signaling in chondrocytes by shortening the cilia and upregulating the expression of Gli-1 protein [26]. The disease can be diagnosed by measuring the excretory level of HGA in urine which is estimated to be 8 g/day [27]. However, the normal urine levels of HGA in healthy individuals are <1.1 µmol/L as compared to AKU patients in which millimolar levels of HGA exists [7,16]. This HGA secreted in the urine is not only obtained from the glomerular filtration but a major percentage of HGA urine is obtained from the renal tubular secretion [28]. In addition to HGA in urine, the bacterial load of urine of infected male patients is also 2–3 times greater than female AKU patients [29]. Moreover, it can be confirmed by the genetic analysis for mutations in HGD gene. Three mutations namely M368V, V300G and P230S are most common in the HGD gene in AKU patients [6]. The ocular symptoms are also beneficial in the diagnosis of AKU as $83\%$ of the AKU patient’s manifest symmetric scleral pigmentation [30]. This pigmentation is due to the deposition of pigment specifically in the sclera (Osler’s sign) having impairment in ocular tendons [30,31]. AKU can also be misdiagnosed due to its rarity and asymptomatic presentation for several years. The impairment and ochronosis of joints can be confused with the rheumatoid arthritis, hyperparathyroidism and ankylosing spondylitis [32], whereas ocular symptoms can be mistakenly diagnosed as ocular melanosarcoma [33]. To date, alkaptonuria is without a specific cure; however, it is being managed via physiotherapy, painkillers, and surgery for replacing joints [34]. Additionally, several studies have reported the use of nitisinone, which is a US Food and Drug Administration (FDA)-approved drug for tyrosinemia type 1, to ameliorate AKU by arresting ochronosis [35]. However, the FDA has not approved its use for alkaptonuria treatment because the use of nitisinone has caused acquired tyrosinosis, elevated liver transaminases, and corneal crystals [1,27,36]. Therefore, alkaptonuria specific drug is required with minimal side effects to treat the patients. Therefore, in the current study, computational approaches were used to identify potent and druggable inhibitors of alkaptonuria through targeting 4-hydroxyphenyl pyruvate dioxygenase. This enzyme is an alpha-keto acid dependent oxygenases and catalyzes the oxidative decarboxylation of 4-hydroxyphenyl pyruvate (HPP) to form homogentisic acid (HGA) [37]. The acquired results showed promising compounds that could further be validated through experimental work and serve as a potential treatment for the very rare inherited disorder, alkaptonuria. ## 2.1. Target Identification According to the literature and KEGG pathway, homogentisate 1,2-dioxygenase (EC number: 1.13.11.5) was mutated, resulting in the enhanced level of homogentisic acid, as shown in Figure 2. 4-Hydroxyphenylpyruvate dioxygenase was the suitable target for treating AKU due to its role in the synthesis of homogentisic acid. The targeted protein was downloaded from the PDB database (PDB id: 3ISQ). This protein is made up of just one chain A having 393 amino acids, and so far no mutations have been reported in this protein. In addition, its resolution was 1.75 Å [38]. ## 2.2. Binding Site Prediction The protein was loaded in SeeSAR protein mode, followed by the selection of a co-crystalline ligand with the most binding affinity than the other four natural ligands in order to automatically select the binding site for docking. However, the binding site just consisted of a limited number of amino acid residues that were expanded by shifting the protein in the binding site mode. The binding site mode enables the visualization of all the unoccupied binding pockets in the target protein as represented in Figure 3. It consists of 10 binding pockets with different acceptors, donors, hydrophobicity, DoGSiteScore, surface area, and volume, as shown in Table 1. The one in yellow was selected because it has the highest DoGSiteScore that accurately predicts the druggable pocket in a protein [39]. Moreover, DoGSiteScore was preferred for the selection of binding site because it has been shown to outperform other existing methods for druggable pocket prediction. The DoGSiteScore is predicted by utilizing a machine learning algorithm that considers various physical and chemical parameters, such as solvent accessibility, flexibility, and amino acid composition to predict the potential binding sites for small molecules in a protein [39]. ## 2.3. Ligand Evaluation As reported in the literature, nitisinone is being used in some countries to treat AKU, but it is not a specific treatment to this disease. Therefore, nitisinone was docked with the 4-hydroxyphenylpyruvate dioxygenase in the docking mode of SeeSAR. The target-nitisinone complex was transported to the binding site mode where surrounding residues were added to the selected pocket to enhance the interaction sites. Therefore, total active site residues were increased from 23 to 29 as elucidated in Figure 4. Furthermore, the HYDE scoring of each atom in the nitisinone was determined in order to estimate the contribution of the sole atom in the overall millimolar estimated affinity of nitisinone. It can be seen in Figure 5 that oxygen atoms at position number 4, 6, and 8 have HYDE energy of −4.8, −1.0, and −0.7 kJ/mol, respectively. Similarly, the HYDE of carbon atoms at position 11, 12, and 14 are −0.9, −3.1, and −0.7 kJ/mol, respectively. The lower the HYDE scoring, the higher will be the importance of that particular atom in the overall structure [40]. ## 2.4. ReCore and Molecular Docking The nitisinone molecule was shifted to Inspirator mode, which modifies the compounds using ReCore. Here, the groups of atoms, having unfavorable HYDE energy were replaced with appropriate fragments that were generated from the fragment library by ReCore. This process resulted in 54 new compounds that were moved to docking mode functionality in SeeSAR, where 540 poses were generated (10 for each compound), as represented in Figure 6. ## 2.5. Selection of Best Hits Selection of hits and their optimization is a crucial step in the drug discovery process as it determines the success of the subsequent stages of drug development [41]. The use of bioinformatics tools, such as SeeSAR BioSolveIT, has greatly enhanced the hit selection process, enabling researchers to effectively identify the most promising compounds for further testing. Therefore, all the 540 poses were exported from docking mode to analyzer mode where their estimated affinities, torsions, clashes, and optibrium properties were calculated. A total of 10 compounds were obtained after screening that have the highest binding affinities, least torsions, no clashes, and low molecular weight, as shown in Table 2. They were named in alphabetical order from a to j. Among them, compound h is nitisinone. The docked complexes of compounds c and f with their best hits are shown in Figure 7, while the best hits for compounds a, b, d, e, and g–h are given in Supplementary Materials Figures S1–S8. The binding affinities of all 10 compounds (a–j) are shown in Figure 8. ## 2.6. ADME Analysis The ADME analysis was performed by SwissADME. According to ADME properties, the selected hits have molecular weight less than 500 g/mol, hydrogen bond acceptors were less than 10, molar refractivity was between 57.75 and 76.07, and topological polar surface area (TPSA) ranged from 75.25 to 112.58 Å. Moreover, the consensus log P values were less than 1.99, whereas log S predicted that all the hits were soluble as elucidated in Table 3. Owing to pharmacokinetic properties, all the hits have high gastrointestinal absorption and were unable to cross the blood–brain barrier (BBB) depicting the safety of central nervous system, as shown in Figure 9 via the boiled egg. This study aims to synthesize drugs that will work outside the central nervous system (CNS) so drugs that will not cross the blood–brain barrier are preferred. The inhibition of cytochrome P450 (CYP) varies, while all obeyed Lipinski, Ghose, Veber, Egan, and Muegge drug-likeness rules with a 0.55 bioavailability score. Furthermore, no PAINS alerts have been observed and synthetic accessibility was from 2.06 to 3.76. All compounds showed lead likeness properties [42]. Compound g, h, and j were excluded because they have shown to inhibit the CYP, thus they can contribute to the toxicity when administered to the patient subsequent to further analysis. Compound g inhibits CYP1A2 and CYP2C19, while compound h inhibits CYP2C19. In addition, CYP1A2 is inhibited by compound j. ## 2.7. Protein-Ligand Interactions Protein-ligand interactions perform a crucial role in many biological processes, including cell signaling, drug design, and protein–protein interactions. The identification and understanding of these interactions are essential for the development of new drugs and therapeutic strategies [43,44]. The docked complexes of hits were analyzed for interactions by using Discovery Studio. The data revealed that the compound c interacts with the active site of target protein by hydrogen bonding, halogen interaction, and pi-cation interaction. Three conventional hydrogen bonds are formed between the O9, and Trp25; O16, and Arg48; and O19, and Arg119 of the receptor. Similarly, the halogen interaction is formed between Glu81 of binding site and F4 of the ligand, whereas nitrogen containing heterocyclic aromatic ring of the ligand forms pi-anion bond with the Arg119 of the protein. Other than compound c, compound f also showed conventional hydrogen bonding with Arg48 and Arg119. These conventional hydrogen bonds are formed by the interaction of N4 and O9 with the amino groups (NH2) of Arg48 and Arg119, respectively. In addition, the pi-donor hydrogen bond is present between OG1 of Thr145 and the five cornered ring of the ligand. Contrarily, the ligand also form hydrophobic interaction with the ligand in the form of alkyl bond. This alkyl bond is formed between the Val57 of receptor and C11 of the ligand as shown in Figure 10. Compounds a, b, d, e, g, h, I, and j were excluded because of the unfavorable interactions, such as positive-positive interactions due to the presence of positively charged nitrogen in their structures. ## 2.8. Validation of Ligand Specificity In order to validate the specificity of compounds c and f, reverse docking was performed. For this purpose, both compounds were docked against the druggable sites of macromolecular targets predicted by SwissTargetPrediction. Compound c does not show any appreciable affinity with all the predicted targets, which include cathepsin K, CYP17A1, phosphodiesterase 10A, JAK3, and ERK2, as shown in Figure 11. Likewise, compound f also exhibits least affinities with the macromolecular ligands predicted by SwissTargetPrediction, such as hepatocyte growth factor receptor, caspase 3, JAK 3, endothelin ETB receptor, and arachidonate 5-lipoxygenase as elucidated in Figure 12. ## 3.1. Target Identification The target for drug designing was selected from the literature via PubMed; moreover, the mutated protein in AKU was determined via the literature and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. KEGG is a database for metabolic pathways that consists of reference pathway databases to provide insight into the relative size and degree of overlap of these pathways [45]. A three-dimensional structure (3D) of the target was downloaded from Protein Data Bank (PDB) database-a sole repository of experimentally resolved 3D structures of large molecules across the world [46]. This selection of the protein was made by considering the resolution of protein (less than 2.5 Å), structure completion (greater than $90\%$), and availability of the ligand. ## 3.2. Binding Site Prediction After loading the protein and selecting the co-crystalline ligand in the protein mode of SeeSAR12.1.0, the complex was moved to the binding site mode. Here, all the unoccupied spaces and residues at the active site were evaluated. Subsequent to the selection of an appropriate binding pocket, the number of residues at the selected active site were increased. The purpose was to enhance the number of interactive sites for ligands [47]. ## 3.3. Ligand Evaluation The structure of nitisinone (ligand) was downloaded from PubChem and evaluated in the analyzer mode of SeeSAR12.1.0 after performing its standard docking. The contribution of each atom in the overall binding affinity between ligand and target protein was investigated by HYdrogen bond and DEhydration energy (HYDE) scoring. The HYDE score is based on two parameters, namely, the hydrogen bond energy and the hydrophobic effect. In addition to score prediction, HYDE can also be visualized by a very intuitive coloring scheme that conveniently segregates the favorable and unfavorable contributions of atoms in the target-ligand complex [40,48]. ## 3.4. ReCore and Molecular Docking The unfavorable atoms were replaced with various fragments preserving conformational information and generating new compounds using ReCore [49]. ReCore is used for designing drugs based on fragments utilizing 3D fragment library known as “index” and is developed by BioSolveIT. It utilizes a vector-based scheme to generate 3D scaffolds altering the core elements of molecules within seconds [50,51]. Afterwards, these compounds were docked with the target protein using FlexX docking functionality in SeeSAR. This molecular docking depends on incremental construction algorithm, in which ligands are cleaved into fragments and each fragment is placed at multiple sites in the binding pocket [52]. ## 3.5. Selection of Best Hits Subsequent to docking, at least 10 poses were generated for each compound and their estimated affinities, torsions, clashes, and optibrium properties were analyzed in the Analyzer mode of SeeSAR. The estimated affinity ranges from millimolar to picomolar, whereas torsions and clashes can be visualized in the form of specific colors. The green color indicates the best results whereas orange and red colors represent the need to re-consider the bond angles and bond lengths between atoms [53]. Therefore, compounds with the best results were screened representing the best hits. ## 3.6. ADME Analysis Absorption, distribution, metabolism, and excretion (ADME) properties of the hits were examined via SwissADME, an online tool that requires SMILES of compounds as input, and interprets results in the form of graphs, tables, and even in spreadsheet form. The interpretations include structure and bioavailability radar, physiochemical properties, lipophilicity, solubility, pharmacokinetics, drug-likeness, and medicinal chemistry of each input [54]. In addition, protein binding, CYP450 inhibition, and blood–brain barrier permeability are also predicted. This information can be used to assess the likelihood of a drug candidate being successful in clinical trials, and its potential for efficacy and safety [55]. ## 3.7. Protein-Ligand Interactions Further analysis and examination of docked complexes were carried out through Discovery Studio 2021 molecular visualization software, which represents the 2D interactions between ligand atoms and specific amino acids in the active site [56]. These interactions include hydrogen bonds, hydrophobic interactions, van der Waal forces, and electrostatic interactions represented by specifically colored dotted lines [57]. An overview of the methods used in this study is shown in Figure 13. ## 4. Conclusions Alkaptonuria, a congenital disorder of tyrosine metabolism, leads to a build-up of a substance called homogentisic acid (HGA) in the body, which can lead to a range of health issues. The disease is caused by mutations in the HGD gene and is passed down from parent to child in an autosomal recessive pattern. Symptoms usually begin to appear in adulthood, and can include joint pain and stiffness, arthritis, and heart valve damage. There is currently no cure for alkaptonuria, but treatments are available to manage its symptoms and prevent complications. Therefore, novel compounds based on the structure of nitisinone were produced by fragment replacement feature of ReCore. Upon docking of these compounds, the hits were screened and analyzed by SwissADME for potent inhibitors. Compound h is nitisinone, which not only inhibits CYP, but also exhibits unfavorable positive-positive interactions with the protein binding site. Compounds c and f showed optimum druggable properties against 4-hydroxyphenylpyruvate dioxygenase. These potent compounds do not inhibit cytochromes and have high gastrointestinal absorption. Moreover, these compounds can be synthesized and could exhibit lead-likeness with no PAINS alerts. The selected potent inhibitors showed better estimated affinities than nitisinone. 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--- title: A Modified Technique for Preventing Lens–Iris Diaphragm Retropulsion Syndrome in Vitrectomized Eyes during Phacoemulsification authors: - Zhiyi Wu - Tian He - Zhitao Su - Ye Liu - Jingliang He - Yanan Huo journal: Journal of Personalized Medicine year: 2023 pmcid: PMC10058855 doi: 10.3390/jpm13030418 license: CC BY 4.0 --- # A Modified Technique for Preventing Lens–Iris Diaphragm Retropulsion Syndrome in Vitrectomized Eyes during Phacoemulsification ## Abstract Background: Lens–iris diaphragm retropulsion syndrome (LIDRS) is common in vitrectomized or high myopic eyes during phacoemulsification. We evaluated the results of a modified technique for cataract treatment using phacoemulsification in vitrectomized eyes. Methods: In this retrospective study, we enrolled thirty-four vitrectomized eyes treated with modified phacoemulsification (Modified Group) and nineteen vitrectomized eyes treated with routine phacoemulsification (Control Group). The modified technique comprised irrigation with a balanced salt solution underneath the pupil before phacoemulsification instrument entry, lens implantation and stromal hydration to stabilize the anterior chamber and equilibrate the pressure between the anterior chamber and posterior cavity. Results: We compared the incidences of intra and postoperative complications and visual outcomes between modified and routine phacoemulsification. Pain, LIDRS and difficulty in stromal hydration were significantly more common in the Control Group than in the Modified Group ($p \leq 0.05$). There were no significant differences in the rates of posterior capsular rupture, iris trauma, lens dislocation, or posterior capsular opacification between the Modified and Control Groups ($p \leq 0.05$). However, there was no significant difference in visual acuity between the groups ($p \leq 0.05$). Complications such as loss of nuclear fragments into the vitreous cavity, cystoid macular edema, retina redetachment, suprachoroidal hemorrhage and vitreous hemorrhage did not occur either intra or postoperatively in any of our patients. Conclusions: Our modified technique prevents LIDRS and complications arising during cataract surgery in vitrectomized eyes. Aside from this, the results of modified and routine phacoemulsification are similar in vitrectomized eyes. ## 1. Introduction A cataract is an eye disease that involves the opacification of the crystalline lens of the eye or its envelope. There are many known causes of cataracts, including the natural aging process, nutritional disorders, metabolic abnormalities such as diabetes, chronic ocular inflammation and certain injuries. Intraocular surgery is the gold standard for cataract surgery. But it can format or accelerate cataracts, especially pars plana vitrectomy (PPV), which is a microsurgical technique to treat certain disorders affecting the posterior segment of the eyes. During vitrectomy surgery, three small incisions are made in the eye in order to place the following instruments: a fiberoptic light source to illuminate the inside of the eye, a vitreous cutter, and an infusion cannula to maintain proper intraocular pressure during the surgery. Advances in PPV surgical techniques and instrumentation have revolutionized the treatment of posterior segment disorders. However, there remain some surgical risks of significant vision loss, including retinal detachment, corneal endothelial decompensation and cataract formation or progression in phakic eyes. Nuclear sclerotic cataract development is the most frequent complication after pars plana vitrectomy (PPV) in the phakic eye [1,2]. However, phacoemulsification is a challenge in the vitrectomized eye because of the lack of vitreous support, the unstable anterior chamber depth and the density of the nuclear cataract. In addition, intraoperative complications such as intraoperative ocular pain and lens dislocation can also increase the difficulty of surgical procedures. Additionally, the risk and incidence of complications are higher in cataract surgery after a previous PPV than in non-PPV eyes. Hence, phacoemulsification in the vitrectomized eye is associated with higher rates of intra and postoperative complications [3,4,5,6,7,8]. Lens–iris diaphragm retropulsion syndrome (LIDRS) was first described in 1992 by Zauberman and further named by Wilbrandt and Wilbrandt in 1994 [9,10,11,12,13,14,15,16,17,18,19]. The incidence rate of LIDRS in vitrectomized eyes during phacoemulsification widely varies, ranging from $4.5\%$ to $100\%$ [11,12]. The syndrome is characterized by the anterior chamber (AC) deepening, followed by pupil dilation and a typical concave iris configuration. During cataract surgery, as the initial corneal incision is made, fluid is lost from both the AC and the vitreous cavity, resulting in the loss of AC and vitreous body volumes. When phacoemulsification or irrigation/aspiration (I/A) probes are inserted, the irrigation causes significant differences in the pressure between the anterior and posterior compartments. The AC deepens, and the iris bows posterior to the lens, blocking fluid passage from the AC. The surgeon must adjust the operative plane by positioning the instruments deeper, which may deform the incision and compromise performance. During phacoemulsification or cortical aspiration, the probe is positioned posterior to the iris plane, resulting in changes in fluid dynamics. Fluid may enter the vitreous cavity through zonular defects, increasing posterior cavity pressure and causing shallowing of the AC and miosis. IDS can lead to complications, such as posterior capsular rupture (PCR), iris trauma, expulsive choroidal hemorrhage and choroidal detachment. The literature on LIDRS prevention during cataract surgery in vitrectomized eyes is scarce [6]. To minimize LIDRS and LIDRS-related complications, we modified the technique by irrigating a balanced salt solution (BSS) into the vitreous cavity through a syringe with a bent, blunt-tipped needle. This technique stabilized the AC intraoperatively, preventing abrupt excursions of the iris–lens diaphragm and making emulsification, cortical aspiration, intraocular lens (IOL) implantation and stromal hydration safer. In this retrospective study, we compared the intra and postoperative complications of the modified (Modified Group) and routine (Control Group) phacoemulsification surgeries in eyes after 23-gauge PPV. ## 2.1. Participants We retrospectively reviewed the medical records of 59 patients (62 eyes) who underwent consecutive phacoemulsification and IOL implantation after a previous 23-gauge three-port PPV surgery between 12 January 2015 and 31 December 2016 in the Eye Center of the Second Affiliated Hospital of Zhejiang University School of Medicine. Patients with in situ silicone oil were excluded from the study. This study followed the tenets of the Declaration of Helsinki. The Ethics Committee of the Second Affiliated Hospital of Zhejiang University School of Medicine approved this study (No. 2015-003). Data were gathered on age, sex, indications for PPV, indications of PPV, preoperative evaluations, intraoperative observations and complications. The patients were followed-up postoperatively on day 1, as well as 1, 2, 4, 8, 12 and 24 weeks after their cataract surgery. Visual acuity and intraocular pressure assessments and slit-lamp examinations were performed, and any postoperative complications were noted. Neodymium-yttrium-aluminum-garnet (Nd: YAG) laser posterior capsulotomy was performed for residual posterior capsular opacification. ## 2.2. Surgical Techniques All vitrectomy and cataract surgeries were conducted by a single experienced surgeon using the associate vitrectomy and phacoemulsification machine (Stellaris PC; Bausch + Lomb: Rochester, NY, USA). All the patients underwent cataract surgery under topical anesthesia (proparacaine hydrochloride $0.5\%$). In the Control Group, a side port corneal incision was created with a blade initially. A small amount of viscoelastic was then injected into the anterior chamber before the 2 mm superior corneal incision was made. A continuous curvilinear capsulorrhexis was made under viscoelastic in all eyes. Hydrodissection was performed using a BSS supplemented with adrenaline. The nucleus was chopped using the “phaco-chop” or “stop-and-chop” methods. A 30° phacoemulsification probe was used for all the patients. Cortical clean-up was performed using an I/A probe. A foldable IOL (CT ASPHINA 509M; Carl Zeiss Meditec: Jena, Germany/iSert® 250; Hoya Surgical Optics Inc.: Chino Hills, CA, USA) was implanted into the capsular bag. Any residual viscoelastic material was completely removed from the AC and behind the IOL with an I/A probe. The stromal hydration of the side port and main incision was performed using the BSS. At the end of the procedure, a $0.1\%$ TobraDex® ointment (Alcon Laboratories, Inc.: Fort Worth, TX, USA) was administered. The main steps of the modified technique, including phacoemulsification, I/A, IOL implantation and stromal hydration, were the same as those of routine cataract surgery. However, to stabilize the AC, we irrigated the BSS underneath the pupil using a syringe with a bent, blunt-tipped needle for a few seconds, which allowed the fluid to enter the vitreous cavity (Figure 1). This irrigation was performed before phacoemulsification, I/A probe entry, IOL insertion and stromal hydration to enable pressure equilibration between the anterior and posterior cavities, to prevent abrupt excursions of the iris–lens diaphragm and to facilitate sculpting and nuclear fragmentation (Figure 2). The surgeries were recorded using a video system and analyzed for both groups. The settings for phacoemulsification (Stellaris PC) were as follows: phacoemulsification power, 0–$50\%$ (depending on the grade of the nucleus), and vacuum limit, 350 mmHg. The bottle height was 90 cm above the patient’s head. ## 2.3. Statistical Analysis SPSS 23.0 software (IBM: Armonk, New York, NY, USA) was used for all statistical analyses. Data were presented as the mean ± standard deviation or as n (%) for categorical variables. We used Student’s t-test for normally distributed variables, the Kruskal–Wallis test for non-parametric variables, and the chi-squared or Fisher’s exact tests, as indicated for the analyses of categorical variables. Snellen’s best-corrected visual acuity measurements were converted to the logarithm of the minimum angle of resolution (logMAR) equivalents for the purpose of data analysis. A p-value of <0.05 was considered statistically significant. ## 3. Results This retrospective study enrolled 59 patients (62 eyes). Seven patients (nine eyes) with in situ silicone oil were excluded from this study. The mean age of the patients in the Modified Group was 64.03 ± 13.12 years, whereas that of patients in the Control Group was 57 ± 12.31 years ($p \leq 0.05$). There were twenty-one male and thirteen female patients in the Modified Group and thirteen male and six female patients (19 eyes) in the Control Group ($p \leq 0.05$). The interval between PPV and phacoemulsification was not significantly different between the Modified (8.39 ± 4.7 months) and Control (9.9 ± 5.22 months) Groups. Table 1 summarizes the indication for PPV. The indications for PPV in the Modified Group were retinal detachment in $\frac{18}{34}$ eyes ($52.9\%$), macular hole in $\frac{5}{34}$ eyes ($14.7\%$), proliferative diabetic retinopathy in $\frac{5}{34}$ eyes ($14.7\%$), epiretinal membrane in $\frac{4}{34}$ eyes ($11.8\%$) and retinal vein occlusion in $\frac{2}{34}$ eyes ($5.9\%$). In contrast, in the Control Group, the indications for PPV were retinal detachment in $\frac{8}{19}$ eyes ($42.1\%$), a macular hole in $\frac{5}{19}$ eyes ($26.3\%$), proliferative diabetic retinopathy in $\frac{3}{19}$ eyes ($15.8\%$), retinal vein occlusion in $\frac{2}{19}$ eyes ($10.5\%$) and epiretinal membrane in $\frac{1}{19}$ eyes ($5.3\%$; Table 1). The indications for PPV were not significantly different between the Modified Group and Control Group (all $p \leq 0.05$). Table 2 summarizes the intraoperative observations and complications encountered. Not all vitrectomized eyes developed LIDRS in our study. Characteristically, the anterior chamber depth appeared abnormal as soon as irrigation commenced. The iris-lens diaphragm bowed posteriorly, causing the anterior chamber to deepen excessively and the pupil to dilate widely. During nuclear sculpting, the deepening of the abnormal anterior chamber necessitated steeper angulation of the phacoemulsification probe, and the nucleus was also noted to be more mobile than usual. Intraoperatively, LIDRS was noted in $\frac{2}{34}$ eyes ($5.9\%$) in the Modified Group and in $\frac{8}{19}$ eyes ($42.1\%$) in the Control Group ($p \leq 0.05$; Table 2). Patients with $\frac{11}{19}$ eyes ($57.9\%$) in the Control Group complained of sudden pain (in the range of 2–3 out of 10 on the numerical rating scale) when instruments entered the AC, whereas none of the 34 patients in the Modified Group felt pain ($p \leq 0.05$). In the Control Group, $\frac{1}{19}$ eyes ($5.3\%$) had PCR, and the IOL was placed in the ciliary sulcus. Additionally, in the Control Group, $\frac{2}{19}$ eyes ($10.5\%$) developed iris trauma during aspiration of the cortex and viscoelastic material. However, IOL dislocation occurred in only $\frac{1}{34}$ eyes ($2.9\%$) in the Modified Groupand was replaced in the capsular bag immediately. Difficulty in stromal hydration was observed in $\frac{4}{34}$ eyes ($11.8\%$) in the Modified Group and $\frac{7}{19}$ eyes ($36.8\%$) in the Control Group ($p \leq 0.05$). Cataract surgery was completed in all cases, in both the Modified Group and the Control Group. No complications, such as loss of nuclear fragments into the vitreous cavity, cystoid macular edema, retinal redetachment, suprachoroidal hemorrhage, or vitreous hemorrhage, occurred either intra or postoperatively in any of the patients. Posterior capsular opacification was evident in $\frac{9}{34}$ eyes ($26.5\%$) in the Modified Group and in $\frac{5}{19}$ eyes ($26.3\%$) in the Control Group ($$p \leq 0.99$$); this was successfully removed using the Nd: YAG laser. No patients in either group required any surgical intervention in the 24-week follow-up period (Table 2). The final visual outcomes were dictated by the nature of the retinal pathology present at the time of the initial vitrectomy procedure. The mean preoperative best-corrected visual acuity of the Modified Group was 1.11 ± 0.46 logMAR units, and that of the Control Group was 1.13 ± 0.52 logMAR units. Both improved significantly at 24 weeks after surgery, to 0.58± 0.35 logMAR units in the Modified Group and 0.59 ± 0.43 logMAR units in the Control Group (both $p \leq 0.005$). The final visual acuity was similar between the groups ($p \leq 0.05$). External segment, ocular motility, pupillary function and intraocular pressure were within normal limits in both groups. ## 4. Discussion PPV was first developed by Machemer in 1971. It is an effective, small-gauge, safe surgery that is essential in the treatment of a variety of posterior segment pathologies, including retinal detachment, macular hole, proliferative diabetic retinopathy, vitreous hemorrhage due to diabetic retinopathy or vein occlusion, preretinal membrane and endophthalmitis. However, performing a vitrectomy can induce cataracts, particularly with the use of intraocular gas, even in young patients. Cataracts eventually occur in almost all eyes after PPV [13]. The causative factors of cataract formation or acceleration after PPV have been linked with the use of intraocular gas, oxidation of lens protein, light toxicity, length of operative time and oxygen tension within the eye. In non-vitrectomized eyes, the vitreous body (especially the vitreous base) limits the flow of fluid from the posterior chamber into the vitreous cavity, preventing changes in volume and pressure in both the AC and posterior segment. However, phacoemulsification in vitrectomized eyes is more technically challenging than that in nonvitrectomized eyes [14]. The primary reason for this is the loss of vitreous counterpressure in vitrectomized eyes. Some vitrectomized eyes also have localized zonular weaknesses caused by loss of the vitreous scaffold, stretching of the zonules by expansile gas or oil, or damage to the zonular apparatus during vitrectomy [15]. This may lead to faster and easier fluid exchange between the AC and posterior cavity. Extremely stretched zonules can be easy to break, causing lens dislocation. Additionally, strong fluctuations in the AC or the iris–capsular bag diaphragm may cause patients pain and trigger unexpected abrupt agitation, increasing the difficulty of the surgery [16]. The nucleus tends to be harder than in age-related nuclear sclerosis, requiring longer phacoemulsification time during the procedure. Together, the unstable posterior capsule and zonules, extended operative time and increased pain experienced by the patients increase the likelihood of complications such as expulsive choroidal hemorrhage or choroidal detachment. With the increasing use of vitrectomy in the treatment of various posterior segment disorders, we expect to see an increase in the number of such cataracts being referred to general ophthalmologists and anterior segment surgeons. Unfortunately, most complications are unpredictable. Specific surgical experience and skills related to the management of complications during cataract surgery in vitrectomized eyes are required. Many studies have reported that phacoemulsification is surgically more challenging in vitrectomized eyes than in nonvitrectomized eyes because various anatomic changes within the eye confer a higher risk of complications. In 1992, Zauberman [8] first described the phenomenon of AC deepening, excessive pupil dilation and a concave shape of the iris during phacoemulsification. Wilbrandt and Wilbrant further studied this syndrome and named it LIDRS in 1994 [7]. LIDRS are more likely to happen in eyes that have had multiple or extensive PPV for diabetic proliferative retinopathy and retinal detachment. However, less LIDRS or abnormally deep AC was evident in eyes that had undergone a limited “core vitrectomy”, such as for a macular hole or epiretinal membrane. In our study, of the ten patients noted to develop LIDRS, eight had undergone thorough PPV for retinal detachment or diabetic proliferative retinopathy. These eight patients previously had thorough vitreous removal through peripheral indentation and trimming of the vitreous base in order to relieve anterior vitreous traction. These procedures may have caused structural damage in the vitreous base region, resulting in abnormal laxity of the zonules. Szijarto et al. [ 17] observed a deep or fluctuating AC in $93\%$ of vitrectomized eyes, implying that the occurrence of LIDRS is related to the loss of the vitreous body, especially the vitreous base. Other studies have reported that the rate of LIDRS-related complications, such as PCR during cataract surgery in vitrectomized eyes, ranges from 0 to $11.4\%$ [6,7,17,18,19,20,21,22,23]. The rate of dropped nuclei ranges from 0 to $4.5\%$ [6,7,17,18,19,20,21,22,23,24], while the rate of zonular dialyses ranges from 0 to $5\%$ [6,7,17,18,19,24], and the rate of iris trauma ranges from 0 to $0.2\%$ [20,21,24]. The rate of posterior capsular opacification requiring Nd: YAG laser capsulotomy after cataract surgery reportedly ranges from 2.2 to $44\%$ in vitrectomized eyes, depending on the follow-up period [6,17,18,19,24]. The rate of retinal detachment in the early postoperative period after cataract surgery in vitrectomized eyes ranges from 1.2 to $6\%$ [17,18,19,24]. The rate of decentration and dislocation of the IOL is around 2 to $2.9\%$ [18,22], whilst the rate of hypotony with choroidal effusion ranges from 0 to $0.6\%$ [18,20,21], and the rate of vitreous hemorrhage ranges from 0.6 to $6\%$ [18,19]. Valesová L et al. reported in 2004 that the incidence of intraoperative complications in the posterior perfusion cataract surgery was slightly higher than in the standard cataract surgery group; there were no special complications in the standard cataract surgery group. Furthermore, the safety of the two surgical methods was consistent [25]. In this study, our findings were significantly different from the study by Valesová L et al. in 2004, as the method in our study differs from theirs. Our method is simple, fast, safe, non-invasive and does not require additional equipment. However, their study used an invasive method to create a new perfusion hole in the eye, which would increase the eyeball damage, the length of the operation and the back pressure, resulting in other complications. In addition, their study showed that their invasive approach does not reduce the risk of surgery. In contrast, we experienced significantly fewer complications during cataract surgery using the modified technique. Pain upon the entry of irrigation into the AC did not occur in the Modified Group; however it was reported by $57.9\%$ of the Control Group ($p \leq 0.05$). The rates of LIDRS and iris trauma were also significantly lower in the Modified Group than in the Control Group (both $p \leq 0.05$). Immediately closing corneal incisions after surgery is important for preventing postoperative complications such as hypotony, choroidal effusion and endophthalmitis. However, stromal hydration can be hindered by ocular hypotony during surgery in vitrectomized eyes. Sachdev et al. [ 20] reported a rate of early postoperative hypotony and serous choroidal detachment of $1.3\%$ after cataract surgery in vitrectomized eyes. Other authors have reported the use of $\frac{10}{0}$ sutures to seal the corneal incision [18]. However, in our study, irrigation with a BSS before sealing the incisions seemed sufficient for solving this problem and preventing related complications. The rate of difficulty in sealing the corneal incision was significantly lower in the Modified Group than in the Control Group ($p \leq 0.05$). One patient ($2.9\%$) in the Modified Group experienced IOL dislocation caused by excessive irrigation during stromal hydration. The IOL was repositioned, and relatively good visual performance was attained without further treatment. Patients who develop cataracts after PPV surgery may undergo a phacoemulsification cataract surgery. Although visual acuity in a normal eye typically improves after cataract surgery, the visual prognosis after surgery for post vitrectomy cataract may be uncertain. Visual acuity and other outcomes after phacoemulsification cataract surgery in eyes undergoing vitrectomy are dependent on multiple factors, although primarily on the retinal condition and the avoidance of complications during cataract surgery. In our experience, the patients who had undergone PPV for macula-on retinal detachment or a macular hole experienced a better improvement in visual acuity after cataract surgery. The patients who had undergone PPV for macula-off retinal detachment or proliferative diabetic retinopathy experienced less visual improvement. There were no severe complications, such as dropped nuclei, expulsive choroidal hemorrhage or choroidal detachment, in the present study. The number of eyes that received Nd: YAG laser treatment after cataract surgery did not differ between the two groups in this study; this confirms the safety of the modified procedure. The timing of irrigation in our modified technique is important. As both the AC and vitreous body fluid are continually lost from the corneal incision, we balanced the pressure between the AC and posterior segment by irrigation of a BSS underneath the iris at four time points: [1]Before the first entry of the phacoemulsification probe;[2]Before the first entry of the I/A probe;[3]Before the insertion of the IOL; and[4]Before the hydration of the stromal incision. This modified irrigation regimen allows fluid to enter the posterior segment, resulting in pressure equilibration. Using the above steps not only made operating on these eyes safer, since the phaco handpiece could be held in a normal position, but it also greatly enhanced the patient’s comfort. As shown in Table 2, this irrigation significantly decreased the incidences of pain, LIDRS, PCR and difficulty in stromal hydration (all $p \leq 0.05$). In our study, all of the patients had phacoemulsification cataract surgery through a superior corneal incision instead of a scleral tunnel. In our opinion, it is preferable to have a steeper angulation of the phacoemulsification probe when operating on vitrectomized eyes. Using a corneal incision also avoids conjunctival scarring or postoperative infection resulting from occult filtration. In our experience, LIDRS does not only occur in phakic eyes after PPV; it also occurs in eyes with high myopia as a result of synchysis, greater AC and axial lengths, a floppy posterior capsule and zonular laxity. High myopia eyes with elongated stretched zonular fibers are more prone to develop LIDRS during phacoemulsification cataract surgery. Additional techniques can be used in vitrectomized and high myopic eyes to minimize IDS, such as reducing the height of the liquid bottle to about 90 cm, using a low-flow rate and vacuum limit, and using a finger to press the corneal incision. A longer, better self-sealing corneal incision and a shorter interval between each step may decrease fluid loss and intraocular pressure fluctuation, meaning that the AC may remain watertight. Other authors have advocated different solutions for stabilizing the AC, such as forming the AC with viscoelastic material during the routine phacoemulsification procedure [2]. An AC maintainer and an irrigating chopper have also been reported to prevent AC fluctuation [26,27]; however, an AC maintainer requires an additional corneal incision. The use of an irrigating chopper in microincisional cataract surgery in tandem with cold phacoemulsification technology has been reported; however, the issue of wound burns persists because of the “naked” phacoemulsification needle [3,6,28]. Joshi [29] modified the sleeve of a phacoemulsification probe to increase fluid flow and deepen the capsular bag, with the aim of decreasing the fluctuation in the AC. However, both prospective and retrospective comparative studies on the prevention of LIDRS in vitrectomized eyes after cataract surgery are lacking [7]. Our study had certain limitations. There are significant astigmatic changes during the early postoperative period and posterior capsular transparency changes during the late postoperative period. Continued follow-ups of the patients are necessary to monitor the long-term refractive stability and visual acuity of these procedures. ## 5. 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--- title: 'Time-Varying Risk Factors for Incident Fractures in Kidney Transplant Recipients: A Nationwide Cohort Study in South Korea' authors: - Sang Hun Eum - Da Won Kim - Jeong-Hoon Lee - Jin Seok Jeon - Heungman Jun - Jaeseok Yang - Myoung Soo Kim - Hye Eun Yoon journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10058856 doi: 10.3390/jcm12062337 license: CC BY 4.0 --- # Time-Varying Risk Factors for Incident Fractures in Kidney Transplant Recipients: A Nationwide Cohort Study in South Korea ## Abstract Little is known about the time-varying risk factors for fractures in kidney transplant recipients (KTRs). Using the Korea Organ Transplantation Registry, a nationwide cohort study of KTRs, the incidence, locations, and time-varying predictors of fractures were analyzed, including at baseline and post-transplant 6-month variables in KTRs who underwent KT between January 2014 and June 2019. Among 4134 KTRs, with a median follow-up of 2.94 years (12,441.04 person-years), 63 patients developed fractures. The cumulative 5-year incidence was $2.10\%$. The most frequent locations were leg ($25.40\%$) and foot/ankle ($22.22\%$). In multivariable analysis, older recipient age at baseline (hazard ratio [HR], 1.035; $95\%$ confidence interval [CI], 1.007–1.064; $$p \leq 0.013$$) and higher tacrolimus trough level (HR, 1.112; $95\%$ CI, 1.029–1.202; $$p \leq 0.029$$) were associated with higher risks for fractures. Pretransplant diabetes mellitus had a time-dependent impact on fractures, with increasing risk as time elapses (HR for diabetes mellitus 1.115; $95\%$ CI, 0.439–2.832; HR for diabetes mellitus × time, 1.049; $95\%$ CI, 1.007–1.094; $$p \leq 0.022$$). In conclusion, KTRs had a high risk of peripheral skeletal fractures in the first 5 years. At baseline recipient age, pretransplant diabetes mellitus and tacrolimus trough level after KT were responsible for the fractures in KTRs. ## 1. Introduction Previous studies have described that the incidence of fractures increases in kidney transplant recipients (KTRs) versus the general population [1] and the risk exceeds that in dialysis patients in the first 1 to 3 years after transplantation [2]. These findings suggest that the bone remains fragile despite improvements in bone and mineral disturbances following kidney transplantation (KT). Chronic kidney disease (CKD) patients have chronic kidney disease–mineral bone disease (CKD-MBD), a disorder of mineral and bone metabolism. CKD-MBD encompasses biochemical abnormalities of calcium, phosphorus, parathyroid hormone (PTH), vitamin D, bone disease, and vascular calcification, which all contribute to fractures [3]. Preexisting CKD-MBD, consequences of KT-specific therapies including glucocorticoid use, and progressive graft dysfunction after KT contribute to high risks of fractures [4]. Several large-scale studies have examined factors that predispose KTRs to fractures [5,6]. However, the incidence of fractures varies widely from 3.3 to 99.6 fractures per 1000 person-years, with a 5-year cumulative incidence of 0.85–$27\%$ [5]. This is because the patient characteristics, study quality, the definition of fractures, and follow-up duration differed among studies. In addition, the changing patterns of treatments, such as the corticosteroid-free regimen adopted after 2000 and the increase in mean recipient age, were not reflected in recent studies. Thus, existing studies have poor consensus on general risk factors and transplant-specific risk factors for fractures in KTRs. Most of the previous studies included baseline variables when investigating predictors of fractures. However, the effect of a fixed baseline variable may change over time, or the risk factor itself may change over time [7]. After KT, laboratory variables change as the allograft function recovers and the early post-transplantation period accompanies the greatest change in immunosuppressants. The present study aimed to investigate the incidence of and assess the time-varying risk factors for fractures following KT by including baseline and post-transplant variables in the analysis. ## 2.1. Study Population and Data Collection Data were obtained from the Korea Organ Transplantation Registry (KOTRY), a prospective multicenter nationwide cohort study of KTRs in South Korea. Forty-one transplantation centers participated in the KOTRY. In the KOTRY, pretransplant and follow-up data are collected by each center at baseline and post-transplantation after 6 months and 1 year, and then annually. Therefore, the collected dataset is complete for each participant. A total of 5403 KTRs aged ≥ 18 years who underwent KT between January 2014 and June 2019 were enrolled in the KOTRY. Among them, 1269 KTRs lacked post-transplantation 6-month data because their post-transplant periods were less than 6 months. Therefore, this study included 4134 KTRs in the analysis. The KOTRY provided patient demographics at the time of transplantation, including age, sex, height, weight, body mass index (BMI), smoking status, primary renal disease, date of dialysis initiation, dialysis modalities used before KT, dialysis vintage, KT date, donor type, other medical comorbidities, and individual patient treatments following KT. BMI was calculated as the patient’s weight in kilograms divided by height in meters squared (kg/m2). Baseline laboratory parameters included serum levels of hemoglobin, creatinine, albumin, corrected calcium (Ca), phosphorus (P), and intact PTH at the time of transplantation. Serum levels of hemoglobin, creatinine, albumin, corrected Ca, and P, and tacrolimus trough levels at 6 months after KT were collected. Data on medications taken at 6 months post-transplantation including vitamin D analogs, tacrolimus, cyclosporine, mycophenolic acid, mammalian target of rapamycin (mTOR) inhibitor, and corticosteroids were also collected. The estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation [8]. Death-censored graft loss and rejection treatment within 6 months post-transplantation were also included. The outcome of this study was fracture occurrence. The information on fracture occurrence was collected in the original registry, which was identified by medical records from patients’ charts. All incident fractures were identified regardless of cause, and traumatic fractures were not assessed separately according to trauma level, as previously described [9]. This is because judging the level of trauma is subjective, as fractures at all locations were included, and high trauma non-spine fractures were also associated with a low bone mineral density as low trauma non-spine fractures [10]. All patients provided written informed consent before KOTRY enrollment. The study was performed in line with the principles of the Declaration of Helsinki and approved by the Institutional Review Board of Incheon St. Mary′s Hospital (OC19OISI0172). ## 2.2. Comparison of Clinical Characteristics and Cumulative Incidence of Fractures Patients were divided into two groups: those who developed fractures (fracture group) and those who did not develop fractures (no fracture group). We compared the clinical baseline characteristics between the two groups, including demographic characteristics, laboratory findings, use of vitamin D analogs, and transplant-specific factors such as percentage of panel reactive antibody, the presence of a human leukocyte antigen donor-specific antibody, the positivity of cross-match testing, type of induction therapy (interleukin [IL]-2 receptor antibody or anti-thymocyte globulin), and main immunosuppressant type (tacrolimus, cyclosporine, mycophenolic acid, mTOR inhibitor, and corticosteroid). Laboratory parameters and medication use at 6 months post-transplantation and death-censored graft loss and rejection treatment within 6 months of post-transplantation were compared between the two groups. The cumulative incidence of fractures was also compared between the two groups. ## 2.3. Statistical Analysis Continuous data are expressed as mean ± standard deviation or median with interquartile range, and comparisons were made using Student′s t-test or the Mann–Whitney U-test as appropriate. Categorical data are expressed as numbers with percentages and were compared using the chi-square test. The time to the first fracture was modeled using the Kaplan–Meier method. The Cox proportional hazard (PH) model was used to identify risk factors for fractures. The univariable analysis was followed by multivariable analyses using the forward conditional method. To determine the variables to be included in the multivariable model, the univariable Cox PH regression analysis is applied first to identify the impact of individual variables. Variables are identified as significant using a 0.2 significance level in the univariable analysis. To test the assumption of proportionality after the construction of the multivariable model, the scaled Schoenfeld residuals have been used. If the model displayed non-proportionality for variables included, the stratified Cox PH model and time-dependent Cox PH model were used to identify baseline and 6-month post-transplantation risk factors for fractures [11]. The results are presented as hazard ratios (HR) with $95\%$ confidence intervals (CI). In all analyses, a p-value < 0.05 (two-tailed) was considered to indicate statistical significance. The statistical analyses were performed using R statistical software (version 4.1.3; R Foundation for Statistical Computing, Vienna, Austria). In addition, all graphs were generated using Prism software (GraphPad, San Diego, CA, USA) and R statistical software. ## 3.1. Patient Characteristics at Baseline Table 1 shows the baseline characteristics of the patients by study group. The mean recipient age was 49.00 years and the mean BMI was 23.09 kg/m2. Among the 4134 KTRs, $59.19\%$ were male, $22.62\%$ were smokers, and $28.96\%$ had diabetes mellitus. The median time on dialysis was 30.33 months [interquartile range (IQR), 3.87–85.25 months]; $14.85\%$ of the patients underwent preemptive transplantation, while $7.89\%$ of the patients underwent re-transplantation. The fracture group was older and had a higher prevalence of diabetes mellitus and diabetic nephropathy as the primary renal diseases than the no fracture group. The fracture group had lower baseline intact PTH levels, more frequently used IL-2 receptor antibody, and less frequently used anti-thymocyte globulin as an induction regimen than the no fracture group. ## 3.2. Patient Characteristics at 6 Months Post-Transplantation Laboratory data at 6 months post-transplantation were compared between the two groups. The fracture group had a lower serum P level and Ca × P product value. Tacrolimus was used more frequently as the maintenance immunosuppressant than the no fracture group, although it was not statistically significant. There were no significant differences in serum levels of hemoglobin, albumin, and corrected Ca, eGFR, proportions of death-censored graft loss, and rejection treatment within 6 months, and medications including vitamin D analogs, cyclosporine, mycophenolic acid, mTOR inhibitor, and corticosteroids. Despite the tendency of a lower tacrolimus dose in the fracture group, the serum tacrolimus trough level was significantly higher in the fracture group (Table 2). ## 3.3. Fracture Incidence and Location During a follow-up of 12,441.04 person-years (median, 2.94 years), 63 patients developed incident fractures. The cumulative incidence of fractures was $2.10\%$ at 5 years (Figure 1). The most frequent fracture locations were the lower leg [$$n = 16$$ ($25.40\%$)] and foot/ankle [$$n = 14$$ ($22.22\%$)]. Less common fracture sites were the vertebra [$$n = 9$$ ($14.29\%$)], upper arm/forearm [$$n = 7$$ ($11.11\%$)], hand [$$n = 6$$ ($9.52\%$)], skull/face [$$n = 4$$ ($6.35\%$)], rib/thorax [$$n = 3$$ ($4.76\%$)], hip/femur [$$n = 3$$ ($4.76\%$)], and clavicle/scapula [$$n = 1$$ ($1.59\%$)] (Figure 2). ## 3.4. Predictors of Incident Fractures Risk factors for incident fractures were analyzed (Table 3 and Table 4). In the univariable analysis, fracture risk was influenced by recipient age, pretransplant diabetes mellitus, preemptive KT, and the use of IL-2 receptor antibody and anti-thymocyte globulin as induction therapy. Among the variables at 6 months post-transplantation, serum P level, Ca × P product, and tacrolimus trough level were associated with incident fractures in the univariable analysis. In multivariable analysis, since pretransplant diabetes mellitus violated the proportional hazards assumption with a p-value of less than 0.05 by scaled Schoenfeld residuals, we applied the stratified Cox regression (Table 3). Recipient age (HR, 1.035; $95\%$ CI, 1.007–1.064; $$p \leq 0.013$$) and tacrolimus trough level (HR, 1.112; $95\%$ CI, 1.028–1.202; $$p \leq 0.008$$) were significantly associated with a higher risk of fractures. Furthermore, to identify the time-varying effect of pretransplant diabetes mellitus, we performed an extended Cox regression analysis with diabetes mellitus as a continuous time-varying coefficient (Table 4). In this multivariable model, recipient age (HR, 1.035; $95\%$ CI, 1.007–1.064; $$p \leq 0.013$$) and tacrolimus trough level (HR, 1.112; $95\%$ CI, 1.029–1.202; $$p \leq 0.008$$) were significantly associated with a higher risk of fractures. The fracture-free survival rate of KTRs with pretransplant diabetes mellitus was significantly lower than that of KTRs without pretransplant diabetes mellitus ($p \leq 0.001$), and the survival curve declined steeper as the time after KT elapsed (Figure 3A). Pretransplant diabetes mellitus showed an increased hazard ratio over the length of the follow-up period (HR, 1.049; $95\%$ CI, 1.007–1.094; $$p \leq 0.022$$) (Table 4 and Figure 3B). ## 4. Discussion This study demonstrated the time-varying tacrolimus trough level and time-varying effect of baseline diabetes mellitus affected the risk of fractures in KTRs. In this nationwide cohort study of 4134 KTRs, the 5-year cumulative incidence of fractures after KT was $2.10\%$. The most common fracture sites were the leg and foot/ankle. Older recipient age at baseline and higher tacrolimus trough level at 6 months post-transplantation increased the risk of fractures, and pretransplant diabetes mellitus showed an increased risk of fractures as time elapsed. Previous reports demonstrated that KTRs are more susceptible to fractures in the early rather than late post-transplantation period. KTRs had a 1.34-fold greater risk of hip fractures than dialysis patients in the first 3 years after transplantation, and the risk decreased to a level comparable to that of dialysis patients after 3 years [2]. Similarly, the fracture risk of KTRs was up to 4.6-fold higher than that of the general population in the first 3 years after KT [12]. These findings suggest that KT does not restore the bone fragility of preexisting CKD-MBD, despite the improvement in mineral metabolism disturbances [13]. As vertebral fractures were closely related to mortality in CKD patients [14] and KTRs with fractures were more likely to experience graft loss or mortality [15], fractures continue to be a significant problem after KT. The cumulative incidence of fractures ranged widely from $0.85\%$ to $27\%$ in previous studies [5]. A recent study reported a 3-year cumulative incidence of non-vertebral fractures of $1.6\%$ and a 10-year cumulative incidence of $1.7\%$ [16], consistent with the results of this study. Although fracture incidence of KTRs was reported in various studies, the relatively low incidence in this study can be explained by the emergence of corticosteroid-limiting or withdrawal protocols after 2000 [17] and advances in the management of CKD-MBD that persist after transplantation. In the present study, the foot/ankle and lower leg were the most common fracture locations, a finding consistent with those of previous reports [9,18]. The high incidence of fractures in the peripheral skeleton, an atypical site of osteoporotic fractures, suggests that various factors are involved in post-transplantation bone fragility. Pre-transplant renal-specific bone factors, post-transplant changes caused by immunosuppressive therapy, gradual allograft dysfunction, and continued mineral metabolism disturbances may impact peripheral fractures [19]. Vitamin K deficiency is also known to affect vascular calcification and poor bone quality in CKD patients, and it was also associated with incident fractures in de novo KTRs [20,21]. Immunosuppressive treatments alter the bone structure, function, and formation in combination with persistent secondary or tertiary hyperparathyroidism [22]. Glucocorticoid-induced osteopenia occurs because of impaired osteoblastogenesis and early osteoblast apoptosis, affecting the trabecular bone of the axial skeleton in particular [23]. In addition, the cumulative dose of glucocorticoids negatively correlates with bone turnover and volume [22]. In murine models, cyclosporine stimulated osteoclast activity more than osteoblast activity, resulting in bone loss [22,24], while tacrolimus induced severe trabecular bone loss [25]. An in vitro study showed that sirolimus interfered with osteoblast proliferation and differentiation [26], while everolimus reduced cancellous bone loss in ovariectomized rats by decreasing osteoclast-mediated bone resorption [27]. The susceptibility of the peripheral skeleton to fractures was demonstrated in a study using an early corticosteroid withdrawal protocol [28]. Interestingly, the bone mineral density in the peripheral skeleton showed progressive deterioration despite early corticosteroid withdrawal, whereas cortical bone mass and strength in the central skeleton were preserved. This is due to persistent hyperparathyroidism and elevated remodeling rates, which result in cortical and trabecular losses and decreased bone strength in the peripheral skeleton [28]. In this study, older age and diabetes mellitus at baseline were risk factors for fractures, as reported by previous studies [5,6,12,29]. However, dialysis modality, dialysis vintage, deceased donor, and female sex were not associated with fractures, a finding that is inconsistent with those of other reports [5,12,30]. In South Korea, most end-stage kidney disease patients are receiving hemodialysis and the proportion of peritoneal dialysis accounts for less than $10\%$ in the past 10 years [31]. The effect of dialysis modality on fractures may not be clearly determined because of the low number of peritoneal dialysis patients. Recent studies also reported that donor type is not significantly associated with fracture risk [6,15]. As this study lacks data on menopausal status, estrogen therapy, or specific osteoporosis treatments, the reason for the lack of an association between the female sex and fractures is unclear. Since this study included KTRs performed in 2014–2019, these patients might have been treated with different drugs for CKD-MBD and osteoporosis than those in the early 2000s. Advances in drugs for CKD-MBD and osteoporosis might have weakened the effect of the female sex on fractures. The reason for the insignificant effects of dialysis vintage on fractures in this study is also unclear. We speculate that the different populations and study periods may have affected these discrepant results. Interestingly, pretransplant diabetes mellitus showed an increased hazard ratio over the follow-up period. Diabetes mellitus is a well-known risk factor for fractures, even in the absence of kidney disease. Proposed pathophysiologic mechanisms are the direct effects of chronic hyperglycemia on bone microarchitecture, inefficient distribution of bone mass, and insufficient repair and adaptation response of bone. Increased risk of falls because of visual impairment and neuropathy may all increase the risk of fractures in patients with diabetes mellitus [32]. In a recent study using the US Renal Data System, the risks for upper extremity and lower leg fractures were significantly higher in dialysis patients with diabetic nephropathy than those with other renal diseases [33]. Since hyperglycemia worsens with the use of calcineurin inhibitors and corticosteroids, the ongoing effect of hyperglycemia on bone health may increase the risk for peripheral skeleton fractures, as post-transplantation periods increase in KTRs with diabetes mellitus. In this study, we aimed to evaluate the effect of time-varying factors on fractures since various factors change after KT, including allograft function, mineral metabolism, and immunosuppressants. Phosphate is a major factor in CKD-MBD, and hyperphosphatemia is closely related to fractures in CKD patients [34]. Conversely, in KTRs, hypophosphatemia was associated with increased fracture risk [35]. In this study, KTRs with fractures had a significantly lower serum phosphorus level at 6 months post-transplantation compared to KTRs without fractures. However, hypophosphatemia at 6 months post-transplantation did not predict future fractures in this study. Among the post-transplantation variables, a higher tacrolimus trough level at 6 months post-transplantation was associated with an increased risk of fractures. As tacrolimus is bound to plasma proteins in the circulation, especially albumin, circumstances affecting plasma protein concentration may change the tacrolimus level [36]. Since our data did not include long-term tacrolimus levels, the results are insufficient to conclude that long-term high tacrolimus levels directly impact bone health. However, there is evidence that tacrolimus affects bone structure in the current literature. In rat models, calcineurin inhibitors, cyclosporine, or tacrolimus, stimulate bone mass loss independent of corticosteroid treatment [37]. It was shown that tacrolimus induced trabecular bone loss and high-turnover osteoporosis in rats [25]. In comparison with cyclosporine, the reduction in trabecular bone mass was more marked in tacrolimus-treated rats [38]. In a study with corticosteroid withdrawal protocol, there was a progressive decline in cortical and trabecular bone density at the peripheral skeleton, despite of preservation of bone mineral density at the central skeleton [28]. Thus, higher tacrolimus trough level may have contributed to a more severe trabecular bone loss at the peripheral skeleton in KTRs. This study has several limitations. First, confounders associated with fractures such as previous fractures, alcohol consumption, physical fitness, exercise, menopausal status, estrogen replacement therapy, intact PTH level at 6 months post-transplantation, treatment for hyperparathyroidism, including parathyroidectomy, and cumulative doses of corticosteroids were not analyzed, nor was dual X-ray absorptiometry used. Especially, the lack of data on cumulative doses of corticosteroids might have underreported the detrimental effects of steroids on bone fractures in this study. Second, the fracture events may have been underestimated; the incidence of vertebral fractures may have been missed because non-traumatic vertebral fractures can be undiagnosed unless actively searched for. Third, the long-term time-varying variables beyond 1 year after KT were not analyzed because of insufficient data. Fourth, defining fractures according to the level of trauma could not be conducted. However, the current study has strengths, including being a nationwide cohort study that included relatively recent KTRs and using complete data from comprehensive medical records. In addition, medications and laboratory parameters at 6 months post-transplantation were included to assess the time-varying effect of certain factors and the effects of time-varying variables, which were not evaluated in previous studies. In conclusion, KTRs are susceptible to peripheral skeletal fractures in the first 5 years. Baseline recipient age and pretransplant diabetes mellitus were associated with fractures in KTRs, and the strength of association with diabetes mellitus increased over the follow-up period. A tacrolimus trough level after KT may be associated with the risk of fractures, which needs verification with tacrolimus levels in the long term. 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--- title: Patient Satisfaction with a Dedicated Infusion Pump for Subcutaneous Treprostinil to Treat Pulmonary Arterial Hypertension authors: - Marcin Waligóra - Barbara Żuławinska - Michał Tomaszewski - Pere Roset - Grzegorz Kopeć journal: Journal of Personalized Medicine year: 2023 pmcid: PMC10058864 doi: 10.3390/jpm13030423 license: CC BY 4.0 --- # Patient Satisfaction with a Dedicated Infusion Pump for Subcutaneous Treprostinil to Treat Pulmonary Arterial Hypertension ## Abstract Background and Objectives: Parenteral prostacyclins are crucial in the pharmacological treatment of pulmonary arterial hypertension (PAH). Indeed, subcutaneous administration of treprostinil has been associated with considerable clinical and hemodynamic improvement, right-sided heart reverse remodeling, and long-term survival benefit. However, evidence on patient perceptions about handling a subcutaneous infusion pump for self-treatment administration and nurse views about training the patients are lacking. This study aimed to describe the perception of PAH patients and nurses regarding the use of the new portable I-Jet infusion pump for the self-administration of subcutaneous treprostinil, as well as its real-world training needs. Materials and Methods: The study is an open, observational, prospective, single-center, non-interventional study. Patients with PAH on stable therapy with subcutaneous treprostinil were invited to take part in the study at their start of use of the portable I-Jet infusion pump for the self-administration of treatment. Participants filled in a questionnaire to report their satisfaction with the use of the pump, as well as their compliance, confidence, convenience, preferences, technical issues, and perceptions of the training they received. Results: Thirteen patients completed the questionnaire after being on the pump for 2 months: $69\%$ were females and the mean age was 51 years. The most frequent PAH etiologies were congenital heart disease ($46.2\%$) and idiopathic PAH ($38.4\%$). Most patients were either World Health Organization (WHO) functional class II ($53.8\%$) or III ($46.2\%$). Ten patients ($76.9\%$) found the pump easy and convenient to live with. All patients declared themselves to be fully compliant and confident in using the pump ($$n = 13$$) at the end of the study follow-up. Ten patients ($76.9\%$) would choose the new pump in the future. None of the patients made reference to technical issues that required additional hospital visits. Eight patients ($61.6\%$) reported that learning how to use the I-Jet infusion pump was easy or very easy, and none considered that further training was needed. One trainer nurse was interviewed and confirmed the satisfaction of patients and the simplicity of usage and training. Conclusions: PAH patients were highly satisfied with the use of the new portable I-Jet infusion pump for self-administering subcutaneous treprostinil. Convenience and ease of use were valuable and commonly reported features. Moreover, the training requirement was simple. These preliminary findings support the routine use of the I-Jet infusion pump. ## 1. Introduction Pulmonary arterial hypertension (PAH) is a rare form of pulmonary hypertension characterized by progressive obliterative vasculopathy of the distal pulmonary arterial circulation that usually leads to right ventricular failure and death [1,2]. Parenteral prostacyclins are a key part of the medical therapy for PAH [3,4]. Continuous administration of the drug, either subcutaneously or intravenously, is required [2]. Subcutaneous (SC) administration of treprostinil has been associated with considerable clinical and hemodynamic improvement, right side heart reverse remodeling, and increased long-term survival benefit [5,6]. SC administration using infusion pumps implies less risk of systemic infection or catheter dislocation than intravenous administration [7] and is sometimes considered to have less life-threatening complications [8,9] and is easier to use for patients having difficulties with intravenous therapy [10]. Continuous SC treprostinil infusion is delivered through an SC catheter, employing an ambulatory infusion pump (Figure 1). Patients must be thoroughly trained in self-use and programming of the pump as well as the connection and care of the infusion set. Several different infusion pumps have been used to administer treprostinil subcutaneously, most of them resembling SC insulin infusion pumps [11]. In Poland, three different subcutaneous infusion pumps are available, including the I-Jet infusion pump, the micro SC infusion pump (Apex, China), and the Canè Crono (Canè, Italy) (Supplementary Table S1). The new I-Jet infusion pump (Everaid®, South Korea) is an ambulatory pump that has been designed exclusively for SC administration of treprostinil and is approved in the European Union (EU) (European CE (Conformité Européene) mark by CE Mark Notified Body 1639; Ferrer is the legal representative) [12]. The design of the I-Jet infusion pump was oriented towards incorporating features that improve ease of use to benefit PAH patients’ comfort (Table 1) [12]. Patient perspectives and the route of administration in long-term chronic conditions can enhance adherence and persistence. Better treatment adherence and persistence, improved clinical and therapeutic outcomes, and better health-related quality of life might be several outcomes of I-Jet pump use [13,14,15]. Nevertheless, patients with chronic conditions report higher adherence and persistence with treatment, confident self-management, and lower total costs with nurse support, medication reminders, injection training, and pen disposal [16]. Moreover, nurse support improves patient self-management of treatment recommendations and enables patients to discuss their adherence problems with healthcare [17]. This manuscript describes the experience of PAH patients using the new portable I-Jet infusion pump. Satisfaction and reliability for first-time users are described as well as patients’ compliance, convenience, preferences, and perceptions of technical aspects of the pump and the training received in hospital. The trainer nurse’s views on patient satisfaction and training needs were assessed. ## 2.1. Study Design All participating patients had their pumps changed (from Apex to I-Jet) due to a substitution of infusion pumps by the hospital provider in mid-2021 as consequence of a public tender. Physicians had no role in the hospital public tender. This circumstance was an opportunity to assess how changing the device may affect the user’s life. We decided to conduct the observational study described in this manuscript. This was an open, observational, prospective, single-center, non-interventional study designed to describe the satisfaction of PAH patients and their trainer nurse with the portable I-Jet infusion pump after 2 months of use. The study was conducted at the Department of Cardiac and Vascular Diseases, John Paul II Hospital, Krakow, Poland. ## 2.2. Study Objectives The primary objective of the study was to assess whether the I-Jet infusion pump was a satisfactory and reliable self-management option for first-time users. The secondary objectives of the study were to explore: Satisfaction: determine overall satisfaction assessment, most-liked features, service satisfaction, and I-Jet infusion pump setup, design, size. Technical performance: evaluate technical performance of the I-Jet infusion pump and occlusion alarms. Benefit: determine convenience of living with the I-Jet infusion pump and patients’ acceptance of the system. Quality of life: determine quality of life improvement or not worsening Education: identify educational aspects for improving the use of the I-Jet infusion pump. Trainer’s insight: describe the nurse experience. ## 2.3. Population All patients were adults (older than 18 years) with an established PAH diagnosis. Patients who were on stable therapy with subcutaneous treprostinil, with no PAH worsening signs in the previous 3 months, no change in PAH-specific treatment, were on stable doses of diuretics, and attended John Paul II Hospital, Krakow, Poland were consecutively recruited into the study between August and October 2021. Patients signed the informed consent form (ICF), were recruited into the study, and changed the previously used device (Apex pump) to the portable I-Jet infusion pump. The exclusion criteria were any serious disease that could contraindicate participation in the study according to the investigator’s judgement; any psychological and/or physical condition that may negatively affect the proper follow-up of study procedures, such as any serious, not corrected hearing and/or visual loss, or difficulties in self-managing the I-Jet infusion pump, including any physical, cognitive, or behavioral limitations; being under legal protection; and any other health ailment that would preclude self-care. All patients were treated according to the European Society of Cardiology clinical practice guidelines [2]. ## 2.4. Research Tools The Patient Satisfaction Questionnaire (PSQ) (Supplementary Figure S1) was developed to assess the satisfaction of patients with the I-Jet infusion pump. The questionnaire included 30 items. Likert-type responses ranged from 1 (very dissatisfied), 2 (dissatisfied), 3 (neither dissatisfied nor satisfied), 4 (satisfied), to 5 (very satisfied). The questionnaire included 8 questions on pump features and technical performance; 4 questions on pump set up/usability; 7 questions on daily use/simplicity; 4 questions on training, learnability, and supplemental training materials; and 7 questions on additional services and recommendations for patients. The Patient Benefit and Education Questionnaire (PBEQ) (Supplementary Figure S2) was developed to collect data about the convenience of the I-Jet infusion pump from the patient’s point of view and best practices and educational aspects. The questionnaire included 17 questions: 10 questions had a yes/no answers; 4 questions required the most convenient option to be chosen; and 3 questions had a Likert-type response scale. The Cambridge Pulmonary Hypertension Outcome Review (CAMPHOR) questionnaire is an established, validated, PAH-oriented tool for the measurement of health-related quality of life (Supplementary Figure S3). The questionnaire was used to evaluate the quality of life at baseline and at the end of the study for patients with the I-Jet infusion pump. The CAMPHOR questionnaire contained 65 items measuring symptoms (25 questions), activity (15 questions), and quality of life (25 questions). Symptoms and quality of life were both scored out of 25, and activity was scored out of 30. Scores were negatively weighted so that a higher score reflected worse quality of life and greater functional limitation [18]. Medical device incidences (MDIs) and adverse drug reactions (ADRs) were reported through the phone during the duration of the study. The study was managed by an independent clinical research organization (CRO) and included pharmacovigilance supervision on safety concerns. ## 2.5. Data Collection After screening (visit 0), the study consisted of 3 data collection visits: visits 1 and 3 were on site and visit 2 was a telephone call. At visit 1, the ICF was signed off; patients were trained on the use of the I-Jet infusion pump by a nurse; they took home basic information on the disease; the pump was provided; and clinical, demographic, and quality of life (CAMPHOR) data were collected. The PBEQ was provided and was to completed after 28 days of using the pump. After 1 month, patients received a follow-up telephone call to collect MDIs and ADRs, resolve technical issues, and assess the patient’s compliance and ability to self-manage the pump. A reminder to answer the PBEQ was given. Visit 3 (8 weeks) took place at the hospital and responses to the CAMPHOR questionnaire, PBEQ, and PSQ were collected. Moreover, pump functionality was checked and treatment was optimized if necessary (Figure 2). At the end of the study, the trainer nurse was invited to provide insights on the training experience in a 30 min, in-depth qualitative interview conducted by telephone (Supplementary Figure S4). ## 2.6. I-Jet Infusion Pump The I-Jet infusion pump is a CE marked infusion pump suitable for continuous subcutaneous infusion of liquid medicine (Figure 3) [12]. It has an icon-based color screen and is equipped with alarms and vibrations for patient safety. The pump runs quietly and continuously in the background 24 h a day. Treprostinil is stored in a 3 mL syringe inside the pump, which needs to be changed every 3 days [12]. ## 2.7. Training Patients were trained on the use of the I-Jet infusion pump by a trainer nurse with 20 years’ experience in training patients treated with subcutaneous treprostinil. Training focused on how to use the pump, frequency of changing the infusion site, actions to be taken in case of an occlusion alarm, and changing the treprostinil syringes (Supplementary Table S2). Training was conducted by the same instructor, a research nurse employed by John Paul II Hospital. ## 2.8. Statistical Analysis Descriptive statistics were performed. For continuous variables, the number of patients, means, standard deviations, medians, and minimum and maximum values were determined. For categorical variables, absolute and relative frequencies were ascertained. ## 2.9. Ethical Considerations The study was conducted in accordance with the Helsinki Declaration, and all patients gave their consent to participate in the study. The local bioethical committee approved the protocol of the study (2KBL/OIL/2021). ## 3.1. Baseline Characteristics In early 2021, a total of 143 patients with an established diagnosis of PAH were treated at John Paul II Hospital, Krakow, Poland: 14 had reactive PAH and were, therefore, treated with calcium channel blockers instead of PAH targeted therapy; 18 of the remaining 129 patients were candidates to receive SC treprostinil. These 18 patients were identified, contacted, and informed of the planned change of the infusion pump. Before changing the pump, 3 of them died and 1 was switched from treprostinil to inhaled iloprost for medical reasons. Among the remaining 14 patients, 1 had a right heart decompensation and did not meet the inclusion criteria to entry the study, while 13 patients provided consent and participated in the survey. The mean age was 50.8 (standard deviation (SD): 14.4) years and $69.2\%$ of participants were females (Table 2). The most frequent PAH etiologies were congenital heart disease ($46.2\%$) and idiopathic PAH ($38.4\%$). A total of $53.8\%$ of patients were assessed as having World Health Organization (WHO) functional class II and $46.2\%$ had WHO functional class III. The median time from PAH diagnosis was 7 years and from initiation of therapy with treprostinil was 13 months. All patients had at least one comorbidity and $76.9\%$ had at least 3 different comorbid conditions. The most frequent comorbidities were chronic cardiac failure ($92.3\%$), metabolism and nutrition ($38.5\%$), and blood and lymphatic system ($30.8\%$) disorders. The mean (SD) 6 min-walk distance (6MWD) was 380 [129] m at the first visit and 375 [131] m at the third visit. Among the 13 participants, 6 ($46.2\%$) were on SC treatment for 1 to 3 years and the remaining 7 ($53.8\%$) were on SC therapy for at least 3 months. The median dose of treprostinil during the study was 39.5 (12.9) ng/kg/min with a stable flow rate across the 3 study visits [Mean = 3.876 mL/hour]. ## 3.2. Patients’ Satisfaction Overall, $76.9\%$ of the patients were satisfied with the I-Jet infusion pump (Figure 4). ## 3.3. Patients’ Satisfaction with Physical Characteristics of the I-Jet Infusion Pump Regarding the style and design and size and weight of the I-Jet infusion pump, 9 ($69.2\%$) and 7 ($53.8\%$) patients were satisfied, respectively. A total of 10 ($76.9\%$), 10 ($76.9\%$), and 11 ($84.6\%$) patients were satisfied with the usability of the keyboard, access to the battery, and access to the syringe compartments, respectively. A total of $53.8\%$ of patients were neither dissatisfied nor satisfied with the legibility of the LCD color display (Figure 5). ## 3.4. Patients’ Satisfaction with Usability Characteristics of the I-Jet Infusion Pump Here, $92.3\%$ (12 out of 13) of the patients were satisfied with the fact that the pump was water resistant and that the flow rate could be set at very precise 0.001 mL steps. Patients were also satisfied with the easy access to the settings menu ($$n = 9$$, $69.2\%$); the user-friendly design of the software interface ($$n = 9$$, $69.2\%$); the content shown on the display ($$n = 7$$, $53.8\%$); the handling of the i-life syringe ($$n = 11$$, $84.6\%$); and the battery change process ($$n = 12$$, $92.3\%$) (Figure 6). ## 3.5. Technical Performance of the I-Jet Infusion Pump Regarding the technical performance of the I- JET infusion pump, only one patient reported an occlusion alarm at the third visit. None of the patients reported technical issues that would require a hospital visit over the 1-month period of observation. None of the patients reported errors that would lead to replacement of the I-Jet infusion pump. ## 3.6. Patients’ Reported Benefits All patients ($100\%$) declared themselves to be fully compliant and confident with the use of the I-Jet infusion pump ($$n = 13$$) at the end of the 1-month study follow-up, and $70\%$ declared that the I-Jet infusion pump did not hinder them from carrying out any everyday activities in their lives. A total of 11 ($84.6\%$) patients reported good control of SC administration of treprostinil with the I-Jet infusion pump. Among the 13 patients, $69.2\%$ changed their infusion site every 3–4 weeks. The arm was the preferred infusion site. Out of 13 patients, 10 ($76.9\%$) found the device easy/convenient to live with and $76.9\%$ preferred to use the I-jet infusion pump in the future (Figure 7). ## 3.7. Health-Related Quality of Life No changes in the scores of symptoms, activities, or quality of life were observed at the end of the study compared to baseline (Table 3). The CAMPHOR scores indicated that patients perceived good quality of life with no physical limitations or symptoms throughout the study. ## 3.8. Education and Training According to the responses, 9 ($69.2\%$) patients were satisfied with the quality of the instructions, the training materials, and the overall I-Jet infusion pump service, while 10 ($76.9\%$) patients were satisfied with the comprehensibility of the operating instruction manual (Figure 8). All patients ($$n = 13$$, $100\%$) considered that the training for first use of the I-Jet infusion pump was appropriate. For 8 ($61.6\%$) of the patients, learning to use the I-Jet infusion pump was easy, and all agreed that a re-training session was not necessary (Figure 9). ## 3.9. Safety Evaluation All patients ($100\%$) reported that administration with the new I-Jet infusion pump was safe. No MDIs or ADRs were reported during the duration of the study. ## 3.10. Nurse Insight The trainer nurse was interviewed at the end of the study. She had been practicing PAH nursing for 20 years. She was a full-time employee at the pulmonary hypertension center at John Paul II Hospital. She had experience in managing CADD MS3® (Smiths Medical) and micro SC (Apex®) infusion pumps and this was her first time using the I-Jet infusion pump. The nurse reported that all patients only needed support from a healthcare professional on the infusion pump features and functionality at the beginning of therapy. She confirmed the ease of training and satisfaction of patients with the I-Jet infusion pump. She was very satisfied with the I-Jet infusion pump’s size, display, and refill process, the keypad, the alarm set up, and the occlusion alarm. She agreed that the I-Jet infusion pump was a reliable self-management device for PAH patients. She felt that the I-Jet infusion pump may have improved patients’ quality of life. ## 4. Discussion This study described the real-life experience and satisfaction of PAH patients after switching to the new portable I-Jet infusion pump for the first time and using it for two months. Patients were highly satisfied with its physical aspects, such as the design, size, and weight, as well as the technical features of the pump. Most PAH patients found its use comfortable and safe. Simplicity of handling and comfort for carrying out everyday life activities were highly rated. According to other research findings, the portability and small size of the infusion pump were related to the satisfaction of patients [19]. Compared with the use of a traditional fixed-syringe pump, the I-Jet infusion pump was easy to use and allowed freedom of movement and comfort in performing common activities of daily living, which increased the satisfaction of patients and nurses alike [19]. Better disease control and reduced time spent on drug preparation are other features of infusion pumps that are considered of importance for patients [20,21]. Patient satisfaction with treatment is highly relevant in the management of PAH for which there are multiple approved therapies available [22]. However, meeting patients’ needs and expectations might be challenging due to various type of drugs and their administration, with each switch hampering QoL. Changes in effectiveness scores have been correlated with changes in 6MWD scores and effectiveness, convenience, and satisfaction scores have been significantly associated with improvements in PAH-specific QoL [23]. Likewise, the use of auto-injection devices for administering SC methotrexate in rheumatoid arthritis patients increased treatment adherence due to improved patients’ preference and satisfaction [16]. In this study, high satisfaction with the I-Jet infusion pump coexisted with a high percentage of PAH patients reporting that they were confidently managing SC administration of treprostinil and fully compliant with the treatment after 2 months. Additionally, participants maintained an excellent quality of life throughout the study period. Patients’ adherence to treatment is a key factor for improving chronic disease control (including destabilization of one clinical condition), efficient use of healthcare resources, and for reducing disease costs [24,25]. Patients’ attitudes and adherence towards their medicines are influenced by many factors, including their perceived (or real) benefits and drawbacks, previous experience of use, perceptions of their illness, satisfaction with treatment, and personal preferences [26]. In our study, the experience of PAH patients with the I-Jet infusion pump use was highly satisfactory, implying that a high level of adherence to therapy can be expected. Being able to perform daily activities is of high importance for chronically ill PAH patients and may have a favorable effect on their quality of life and mental health [27]. Stable PAH patients should be encouraged to be active. It has been demonstrated that patients who keep performing their daily activities or increase their level of physical activity improve their distance in 6MWD compared to sedentary patients [28]. The I-Jet infusion pump helped PAH patients to comfortably carry out their daily activities. Compared to other pumps used for the SC administration of treprostinil, common malfunctions were reported with the MiniMed® Model 506 (Medtronic) infusion system (55 patients in the treprostinil group ($24\%$) and 77 patients in the placebo group ($33\%$) [6]. Likewise, Barst et al. [ 2006] described the results of an open label, SC treprostinil long-term extension study over 4 years in 860 patients [29]. Delivery system complications were reported by 255 patients ($30\%$), with the most frequent being pump malfunction (222 patients; $26\%$) and problems with the infusion set (74 patients; $9\%$) [29]. In contrast, patients using I-Jet infusion pump in this study reported no MDRs, ADRs, or malfunctions of the device at two months of prospective observation. During this study, a trainer nurse trained PAH patients to use the pump at the beginning of the study, with no need for further training or monitoring over time. The trainer nurse confirmed the results obtained from patients in terms of satisfaction, compliance, comfort, and confidence. Ease of training and learning to use a device is associated with increased adherence and adequate control of therapy administration [30] and more efficient use of nursing time [19]. This study had limitations and its findings need to be interpreted accordingly. The absence of a comparator prevented us from testing the robustness and true magnitude of the results obtained with the I-Jet infusion pump. Its open, descriptive nature implied low internal validity; however, external validity was high as the findings reflected everyday life. The study was conducted in a small sample of patients in a single center over a short follow-up period due to low prevalence of PAH and infrequent use of SC treprostinil to treat PAH. Additionally, in Poland, all PAH patients have their available pharmacological treatments fully reimbursed and accessible. In consequence, treatment with SC treprostinil depends solely upon medical decision-making and patient agreement in minimizing potential selection bias. Self-reported information on a questionnaire may be biased by patients’ interpretation of questions and answers. The questionnaire was not validated for the assessment of patient satisfaction and content bias may arise in consequence. Despite these limitations, this study presents preliminary findings on the experience and satisfaction of PAH patients treated with SC treprostinil with the I-Jet infusion pump. The study provides evidence of PAH patients’ satisfaction with treatment delivery devices in real life. The adequate, easy, and safe self-management of SC treprostinil with the I-Jet infusion pump may reduce hospital visits and improve patients’ quality of life with no additional physical limitations in daily life. Finally, the study also provides information about patients’ training needs for the design of new infusion pumps. ## 5. Conclusions PAH patients were highly satisfied with the I-Jet infusion pump for the self-administration of SC treprostinil. Convenience, comfort, safety, and simplicity were features of the infusion pump that were highly valued by patient users. 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--- title: Serum Metabolites Associated with Muscle Hypertrophy after 8 Weeks of High- and Low-Load Resistance Training authors: - Denis F. Valério - Alex Castro - Arthur Gáspari - Renato Barroso journal: Metabolites year: 2023 pmcid: PMC10058868 doi: 10.3390/metabo13030335 license: CC BY 4.0 --- # Serum Metabolites Associated with Muscle Hypertrophy after 8 Weeks of High- and Low-Load Resistance Training ## Abstract The mechanisms responsible for the similar muscle growth attained with high- and low-load resistance training (RT) have not yet been fully elucidated. One mechanism is related to the mechanical stimulus and the level of motor unit recruitment; another mechanism is related to the metabolic response. We investigated the electromyographic signal amplitude (sEMG) and the general metabolic response to high-load RT (HL) and low-load resistance training (LL). We measured muscle thickness by ultrasound, sEMG amplitude by electromyography, and analysis of metabolites expressed through metabolomics. No differences were observed between the HL and LL groups for metabolic response and muscle thickness. A greater amplitude of sEMG was observed in the HL group. In addition, a correlation was observed between changes in muscle thickness of the vastus lateralis muscle in the HL group and levels of the metabolites carnitine, creatine, 3-hydroxyisovalerate, phenylalanine, asparagine, creatine phosphate, and methionine. In the LL group, a correlation was observed between changes in muscle thickness of the vastus lateralis muscle and levels of the metabolites acetoacetate, creatine phosphate, and oxypurinol. These correlations seem to be related to the characteristics of activated muscle fibers, the metabolic demand of the training protocols used, and the process of protein synthesis. ## 1. Introduction Resistance training (RT) is recognized as an effective means to promote muscle growth [1]. This morphological adaptation is important to improve athletic performance [2] and provides several health benefits, such as the prevention of metabolic diseases [3,4]. Current guidelines recommend that RT should be performed with loads > $60\%$ of a repetition maximum (1RM) to optimize muscle hypertrophy [5,6]. Accordingly, high loads are preferred by researchers [7,8] and practitioners [9]. Conversely, low-load RT, which uses loads around $30\%$ of 1RM, have also been shown to promote muscle growth similar to that seen with high-load RT [10,11,12]. The mechanisms responsible for the similar muscle growth attained with high- and low-load RT have not yet been fully understood. One suggested mechanism is the mechanical stimulus, which is related to the degree of motor unit recruitment [10,13,14]. Traditionally, high-load RT has been assumed to cause greater muscle activation than low-load RT. However, some authors have challenged this assumption and shown that muscle activation is similar in high- and low-load RT [8,13,14]. When performed up (or close) to the concentric failure, low-load RT may recruit motor units similarly to high-load RT [11,15]. The high level of recruitment means that many motor units are being activated and muscle fibers are under intense mechanical stimulation. Another proposed mechanism relates to the metabolic response. It has been suggested that the accumulation of metabolites during low-load RT compensates for the lower mechanical tension and stimulates intracellular pathways that induce muscle growth, leading to a hypertrophic response similar to that of high-load RT [13,16]. Although several studies have highlighted metabolite accumulation as a potential mechanism to induce muscle hypertrophy [17,18,19], few have investigated which metabolite is a viable candidate for signaling skeletal muscle hypertrophy in humans [20,21]. In addition, we are unaware of any study that has analyzed the metabolome of low-load RT and compared it with that of high-load RT. Although important, the studies that have analyzed the metabolic response to low-load RT were nevertheless performed with the addition of blood flow restriction, and most of them only investigated the acute metabolic response after a single training session [22,23,24]. Investigating acute responses does not allow inferences on the relationship between the metabolic response to a RT session and hypertrophy observed after a training period. Metabolomics represents a promising analysis of the global metabolic response elicited by RT [20,24,25], combining several analytical techniques to identify large amounts of metabolites present in a biological sample [26] and allowing a more comprehensive view of the substrates involved during exercise compared with traditional biochemical techniques focused on isolated compounds. Thus, this study analyzed muscle activation and the overall metabolic response, using metabolomics, in acute sessions of high- and low-load RT before and after the 8-week training period. This study will contribute to the understanding of the relationship between acute metabolic responses and muscle activation produced by high- and low-load RT sessions and changes in muscle hypertrophy. ## 2.1. Participants Thirty healthy young men, who had not participated in RT programs for at least 12 months before the study, were recruited to the experiments. Individuals with metabolic diseases, such as diabetes, who were on a hypocaloric diet, or who had osteomioarticular problems that could interfere with exercise performance were excluded from the study. Participants with a training frequency of less than $90\%$ attendance in training sessions, or who were absent for more than two consecutive sessions, were also excluded from the study. Participants received information about the benefits, risks, and experimental procedures involved in the research and signed an informed consent form. The procedures were approved by the local Ethics Committee. Initially, the 30 participants were selected after screening and interview. Five decided to withdraw for personal reasons, and 25 participants were randomly allocated and stratified into two groups, based on vastus lateralis muscle thickness: high- (HL) and low-load (LL). At the end of the training program, 18 participants (age 23 ± 3 years, body mass 67 ± 2 kg, height 172 ± 6 cm) met the minimum training frequency and were considered for the analysis between the HL ($$n = 9$$) and LL ($$n = 9$$) groups (Figure 1). ## 2.2. Experimental Design On the first visit to the laboratory, participants underwent an anthropometric assessment, and ultrasound images (Nanomaxx, Sonosite, Bothell, WA, USA) of the rectus femoris, vastus intermedius, and vastus lateralis muscles were taken. Participants performed two familiarization sessions with the 1-RM test in the 45° leg press and bilateral leg-extension exercises. After the familiarization sessions, the 1-RM test and re-test were performed for the exercises. There was a minimum of 72 h between laboratory visits. After the 1RM retest, the eight-week training period was started. Participants repeated the 1RM test after the fourth week and 72 h before the last training session to adjust training loads. This procedure was performed to ensure that the participants completed their respective training sessions at the correct intensity, especially during the last training session when the metabolic response was analyzed and muscle activation was assessed. Blood samples were collected for subsequent metabolic analysis at three time points during the first and last training sessions. Muscle activation of the vastus lateralis was assessed during the three sets in the 45° leg-press exercise. Finally, ultrasound images were taken 72 h after the eight-week training period (Figure 2). All experimental protocols took place between 8 and 11 am to avoid possible changes in responses to exercise due to the circadian rhythm. ## 2.3. Nutritional Habits Participants were instructed to maintain the same eating habits in the days before blood sampling. They were familiarized and instructed by experienced researchers to complete the food record of the day before blood collection. Additionally, the total energy intake, amount, and proportions of macronutrients (carbohydrates, lipids, and proteins) filled in the food record were analyzed quantitatively using the NutWin (v. 1.5, Federal University of São Paulo). After a 10 h overnight fast, blood samples were collected from the antecubital vein in serology tubes (Vacuette, 8 mL). Participants also consumed a standardized meal (290 kcal, $60\%$ carbohydrate, $25\%$ lipid, and $15\%$ protein) one hour before baseline blood sampling [24,25]. ## 2.4. Maximum Dynamic Strength Maximum dynamic strength was determined using the one-repetition maximum test (1RM) according to the American Society of Exercise Physiologists (ASEP) guidelines [27] in the leg-press and leg-extension exercises. In this test, the objective was to achieve the maximum weight that could be lifted in one complete movement. Before the test, participants warmed up for 5 min on an ergometric bike. After the general warm-up, participants performed a specific warm-up consisting of two sets of eight and three repetitions with an estimated load of $50\%$ and $70\%$ of the 1RM, respectively. A three-minute interval was observed between the end of the specific warm-up and the beginning of the test. The tests were performed in the same order for all participants. The initial weight for the test was estimated during the familiarization sessions and was increased until the participant was unable to complete a repetition [27]. The total number of attempts to find the 1RM value was no more than five. There was a three-minute rest interval between attempts, and a 10-minute interval between exercises. ## 2.5. Training Protocol Participants completed two weekly training sessions using the 45° leg press and bilateral leg-extension exercises, in this order, for eight weeks. The training sessions consisted of a general (5 min on the bike) and a specific warm-up (one set of 10 repetitions at $50\%$ of 1RM), then three sets at an intensity of $80\%$ 1RM for the HL group and $30\%$ of 1RM for the LL group. Both groups performed repetitions to concentric failure with a 90 s interval between sets and a 120 s pause between exercises. Concentric failure was considered when the participant could no longer perform another repetition with the specified range of motion. ## 2.6. Muscle Activation Muscle activation was assessed by surface electromyography (EMG) obtained only in the 45° leg-press exercise using a 16-channel electromyograph (MP150, Biopac System Inc., Santa Barbara, CA, USA), with the acquisition frequency of the EMG signals set at 1000 Hz and a bandpass filter of 20–500 Hz. Active electrodes (TSD150, Biopac System, Inc., Santa Barbara, USA) with a common mode rejection ratio of >95 dB were used. Before placing the electrodes, the skin was shaved and disinfected with alcohol in the sites designated for application of the electrodes on the vastus lateralis muscle, to reduce the impedance of the skin. The electrodes were placed at the site with the greatest muscle volume identified during an isometric contraction. Positioning was marked with a semi-permanent pen to maintain the positioning. A customized routine (MatLab, The MathWorks, Natick, Middlesex County, MA, USA) was used to digitally filter the raw electromyographic signals (4th order Butterworth, 20–500 Hz bandpass) and convert them to root mean square (RMS). The RMS of each repetition was normalized by the average RMS of the ten concentric phases of the repetitions completed during the warm-up. The amplitude of the EMG was analyzed in a range of motion of 40°, between 120° and 160°, to reduce the influence of changes in muscle length on the signal. To identify eccentric and concentric phases during the exercise, an electrogoniometer (SG150, Biometrics Ltd., Newport, UK) was attached to the side of the right knee, and the electrogoniometer signal was synchronized with that of the EMG. ## 2.7. Muscle Thickness A B-mode ultrasound (Nanomaxx, Sonosite, Bothell, WA, USA), with a linear vector probe and a frequency of 7.5 MHz, was used to capture images of the thickness of the rectus femoris, vastus intermedius, and vastus lateralis muscles. Images were taken on the right leg, with images acquired at $50\%$ of the distance between the anterior superior iliac crest and the superior border of the patella [28]. For all measurements, participants were instructed to relax their muscles as much as possible. To ensure the same positioning, participants had the positioning of their bodies delimited on the evaluation stretcher in a standardized manner. The transducer was aligned in the axial plane, perpendicular to the muscles being examined. Images were recorded for later analysis of muscle thickness, using Image J (NIH, Bethesda, MD, USA). ## 2.8. Blood Sampling Blood collection was performed after participants arrived at the laboratory after fasting for 10 h, consumed the standardized meal, and rested for one hour (collection 0 min). It was repeated at 5 min (+5 min) and at 60 min (+60 min) after the training session [24,25]. Venipuncture was performed via the median cubital vein in the antecubital fossa. After collection, the blood was stored at room temperature for 30 min and then centrifuged at 3000 rpm for 10 min. The serum was stored in a freezer at −80 °C. ## 2.9. Sample Preparation for Metabolomics Analysis Before the analysis, the 3 kDa filter was washed (Amicon Ultra, Sigma-Aldrich, St. Louis, MO, USA). This wash consisted of 500 µL of Milli-Q H2O. After applying Milli-Q H2O to the filter, it was centrifuged at 14,000 rpm for 10 min at 4 °C. This process was repeated five times. After the fifth wash, a further spin was performed (filter inversion and rotation of 8000 rpm for 5 s) to eliminate any trace of Milli-Q H2O. After the spin, 350 µL of the stored serum was added to the filter, which was centrifuged at 14,000 rpm for 45 min at a temperature of 4 °C. After this period, the solution that had passed through the filter (200 µL) was recovered and placed in a 5 mm MNR tube (Wilmad, Sigma-Aldrich, USA). To this solution was added 60 µL of 0.1 mol/L phosphate buffer solution (Sodium Phosphate Monobasic, NaH2PO4 0.028 mol/L and Sodium Phosphate Dibasic, Na2HPO4 0.072 mol/L, pH 7.4), 6.06 µL of TSP-d4 (3-(trimethylsilyl)-2,2′,3,3′tetradeuteropropionic acid—Sigma-Aldrich), 50 mmol/L in D2O (D2O, $99.9\%$; Cambridge Isotope Laboratories Inc., MA, USA) (used as an internal reference), and 340 µl of Milli-Q H2O in a 5-mm NMR tube (Wilmad-LabGlass, Vineland, NJ, USA). ## 2.10. Data Acquisition by NMR and Quantification For the acquisition of spectra, nuclear magnetic resonance spectroscopy (1H-NMR) at 600 MHz (Agilent Technologies Inc., Santa Clara, CA, USA) was used. Data acquisition was performed using VnmrJ software (Varian NMR Systems). The analysis was performed at a constant temperature of 298 K (25 °C). A total of 256 scans were performed, with a delay interval of 1.5 s and an acquisition time of 4 s between each scan. The sample tuning adjustments with the device were performed by a specialized technician, and the other adjustments (lock and shimming) were performed manually for each sample. Spectral processing, characterization, and quantification of metabolites were performed using Suite 7.6 Chenomx NMR software (Chenomx Inc., Edmonton, AB, Canada). Spectral processing consisted of spectral phase adjustment, baseline correction, and signal removal from water (4.6–5.1 ppm). Then, a 0.3 Hz line-broadening apodization function was applied and the spectrum was calibrated by the internal reference signal (TMSP-d4). ## 2.11.1. Muscle Thickness, Muscle Activation, and Total Energy Intake of Macronutrients Data were presented as mean and standard deviation. The normality of data distribution was checked by the Shapiro–Wilk test. For comparisons between and within groups, Mixed Linear Models were used for repeated measures, assuming participants as a random factor, and group (HL and LL) and period (pre- and post-training) as fixed factors for the variables muscle thickness, EMG amplitude, and consumption macronutrients (carbohydrates, lipids, and proteins). Where significant F values occurred, Tukey’s post hoc test was used. The significance level adopted was $5\%$. ## 2.11.2. Metabolic Response To identify the patterns of global metabolic response by the HL and LL groups, a Principal Component Analysis (PCA) was conducted. Before this analysis, to standardize the scale of concentrations between the different metabolites, the autoscaling process was applied [29]. Additionally, a heat map depiction of the metabolite concentrations was generated for the entire metabolomics dataset to display differences between and within groups. For this analysis, MetaboAnalyst 4.0 software was used. Afterwards, to explore the association between the acute metabolic response and muscle hypertrophy, Pearson correlations were calculated between the acute metabolic changes observed for the blood collection times Δ 0–5 and Δ 0–60 min of the first training session (pre-training period) and the increase in the vastus lateralis muscle thickness (Δ muscle thickness). From the metabolites—the changes in which after the acute session were significantly correlated with changes in muscle thickness—Linear Mixed Models for repeated measures were applied for comparisons between and within groups, assuming participants as a random factor, and group (HL and LL), period (pre- and post-training) and time of blood collection (0 min, +5 min, and +60 min) as fixed factors. Main effects and significant interactions were analyzed using Sidak’s post hoc test. This analysis was performed using PASW statistics software version 18.0 (SPSS, Chicago, IL). Significance was at $p \leq 0.05.$ ## 3.1. Nutritional Habits No difference was observed between groups or period (pre, and post-training) for total caloric consumption and amount of macronutrients (carbohydrates, lipids, and proteins) consumed in the days before blood collection. The data are presented in more detail in the Supplementary Material. ## 3.2. Maximal Dynamic Strength A major period (pre vs. post) effect was observed for the 1-RM tests in the 45° leg press and leg-extension exercises ($p \leq 0.0001$ for both). An increase in the load in the 1RM test was observed after eight weeks of training for both the 45° leg press and the leg extension, when compared with pre-training ($p \leq 0.0001$ for both) and week 4 (45° leg press: $p \leq 0.0001$; leg extension: $p \leq 0.003$), as well as at week 4 compared with the pre-training period (45° leg press: $p \leq 0.0001$; leg extension: $p \leq 0.001$). However, there was no between-group difference in the 45° leg press and leg-extension exercises ($p \leq 0.05$) (Figure 3). ## 3.3. Muscle Activation The HL group presented greater electromyographic amplitude compared with the LL group, both in the first ($p \leq 0.0001$) and in the last ($$p \leq 0.01$$) training session (Figure 4). Additionally, for the LL group, greater electromyographic amplitude was observed in the last training session compared with the first session ($$p \leq 0.03$$); while in the HL group, a trend toward greater electromyographic amplitude was observed in the last training session compared with the first session ($$p \leq 0.058$$) (Figure 4). ## 3.4. Muscle Hypertrophy The main period (pre vs. post) effects were observed and showed an increase in muscle thickness, in both the HL and LL groups, after eight weeks, when compared with the pre-training period for the vastus lateralis thickness ($p \leq 0.0001$, Figure 5A), sum of the thickness of the rectus femoris muscles and vastus intermedius ($p \leq 0.0001$, Figure 5B), and sum of the thickness of the vastus lateralis, rectus femoris and vastus intermedius muscles ($p \leq 0.0001$, Figure 5C). There was no difference between the HL and LL groups for the vastus lateralis thickness ($$p \leq 0.8$$), sum of the thickness of the rectus femoris and vastus intermedius ($$p \leq 0.9$$), and sum of the thickness of the vastus muscles lateral, rectus femoris, and vastus intermedius ($$p \leq 0.9$$). Considering the sum of the thickness of the three muscles analyzed, the HL group showed a percentage increase of $12.5\%$ and the LL group of $12.1\%$. ## 3.5. Metabolic Response After the experimental sessions of the HL and LL groups and the performance of 1H-NMR spectroscopy, 50 metabolites were identified and quantified in the blood serum in both groups; a table with further details can be found in the supplementary material and the heat map in Figure 6 provides an overview of the levels of each detected metabolite between and within groups. From the Principal Component Analysis (PCA), it was not possible to show a clear segregation between the HL and LL groups. This finding suggests that there was no global disturbance in the metabolism between and within groups (pre/post-training periods of each group) that could be attributed to a specific group of metabolites (Figure 7). From the correlational analyses, a significant correlation was observed between the observed changes in the thickness of the vastus lateralis muscle and the metabolic response in the first training session of 0–5 min for the HL group (carnitine: $r = 0.678$, $$p \leq 0.045$$; creatine: $r = 0.716$, $$p \leq 0.030$$), the LL group (acetoacetate: $r = 0.715$, $$p \leq 0.046$$; creatine phosphate: r = −0.620, $$p \leq 0.018$$), and the combined groups (carnitine: $r = 0.531$, $$p \leq 0.028$$; creatine: $r = 0.532$, $$p \leq 0.028$$; creatine phosphate: r = −0.517, $$p \leq 0.033$$); and 0–60 min for the HL group (3-Hydroxyisovalerate: r = −0.727, $$p \leq 0.041$$; phenylalanine: r = −0.750, $$p \leq 0.032$$; asparagine: r = −0.721, $$p \leq 0.044$$; creatine phosphate: r = −0.772, $$p \leq 0.025$$; methionine: r = −0.725, $$p \leq 0.042$$), the LL group (oxypurinol: $r = 0.821$, $$p \leq 0.045$$), and the combined groups (carnitine: $r = 0.608$, $$p \leq 0.021$$; creatine phosphate: r = −0.620, $$p \leq 0.018$$). Univariate analyses were then performed for the comparison between and within groups of the metabolites that were correlated with the increase in the thickness of the vastus lateralis muscle. As a result, an increase was observed in the post-training period compared with the pre-training period in the serum levels of 3-hydroxyisovalerate for both groups (HL: $p \leq 0.0001$; LL: $p \leq 0.0001$) with no difference between the groups. Phenylalanine levels increased only in the HL group ($$p \leq 0.00003$$), but there was no between-group difference. On the other hand, decreased serum asparagine levels were observed in the post-training period compared with the pre-training period only in the LL group ($$p \leq 0.003$$), but it was no different from the HL group. No significant changes were observed in the levels of the metabolites acetoacetate, carnitine, creatine, creatine phosphate, methionine, and oxypurinol when comparing groups or in the post- compared with pre-training period. ## 4. Discussion The study aimed to analyze the hypertrophy, muscle activation, and acute global metabolic response of the HL and LL groups. We also sought to correlate the muscle activation and metabolic response data with changes in muscle hypertrophy after eight weeks of training. Our main findings can be summarized as follows: (a) there was greater muscle activation of the vastus lateralis in the HL group compared with the LL group in the first and last training sessions; (b) there were no between-group differences in the metabolic responses; (c) there was correlation between growth of the vastus lateralis in the HL group and levels of the metabolites carnitine and creatine (positive correlations, for delta 0–5 min), 3-hydroxyisovalerate, phenylalanine, asparagine, creatine phosphate and methionine (negative correlations, for delta 0–60 min); (d) there was correlation between growth of the vastus lateralis in the LL group and metabolite levels for delta 0–5 min of acetoacetate metabolites (positive correlation), creatine phosphate (negative correlation) and for delta 0–60 min of oxypurinol (positive correlation); (e) there was correlation between vastus lateralis muscle growth in both groups and metabolite levels for delta 0–5 min of carnitine (positive correlation), creatine (positive correlation), creatine phosphate (negative correlation), and for delta 0–60 min of carnitine (positive correlation) and creatine phosphate (negative correlation). Jenkins, Miramonti, Hill, Smith, Cochrane-Snyman, Housh and Cramer [8] analyzed muscle activation in untrained individuals during high- and low-load RT. In contrast to our results, they observed no differences in muscle activation after 3 or 6 weeks of training between the groups that trained with 80 and $30\%$ of 1RM in the leg-extension exercise. However, the group that trained with $80\%$ of 1RM showed a significant increase from baseline to weeks 3 and 6. We measured EMG only in the vastus lateralis muscle, whereas in Jenkins, Miramonti, Hill, Smith, Cochrane-Snyman, Housh and Cramer [8] the EMG signal was averaged across the vastus lateralis, rectus femoris and vastus medialis muscles. We also used a multi-joint exercise (leg press) while they used a single-joint exercise (leg extension). The recruitment pattern and mechanical differences between the muscles and exercises may have contributed to the discrepancy in results between our study and Jenkins, Miramonti, Hill, Smith, Cochrane-Snyman, Housh and Cramer [8]. Although EMG has traditionally been used to make inferences about muscle activation, some limiting factors of this method have already been discussed [30]. For instance, it is possible that some motor units reduce their firing rates or become momentarily silent to recover from fatigue [30,31,32]. These fatigued motor units would be replaced by more fatigue-resistant motor units, to maintain sufficient force and to continue the exercise [33,34,35]. Therefore, the greater amplitude of EMG, which could be understood as greater muscle activation (i.e., more motor units active), may mean that this analysis is not sensitive enough, as it represents a “snapshot” of the exercise and does not provide information regarding the total number of motor units recruited during the complete set of exercises. Therefore, even with a greater EMG amplitude in the HL group, as observed in our experiment, it is still possible that the same total amount of muscle fibers were recruited during HL and LL exercise performed until concentric failure. It is often thought that metabolite accumulation is a stimulus that can influence muscle hypertrophy [17,18,19], and that low-load RT can cause greater or longer-lasting metabolic stress compared with high-load RT [16,36]. Thus, even if the mechanical stimulus is lower during low-load RT, similar hypertrophy to that of high-load RT could be achieved. In fact, some studies showed lower intramuscular metabolic stress (creatine phosphate, pH, or blood lactate concentration) in high-load compared with low-load RT with [22,23,37] or without blood flow restriction [38]. However, in a study where 1H-NMR analysis of blood plasma was performed to provide a more comprehensive observation of acute responses to high-load and low-load RT with blood flow restriction, there was no difference in the metabolic stress [24]. Although our results showed no difference in the global metabolic response between the HL and LL protocols, it was possible to observe a relationship between metabolic response and muscle hypertrophy in both groups. Some metabolites correlated with the increase in vastus lateralis muscle thickness (i.e., muscle hypertrophy) in the HL and LL groups. Some of these observed correlations may be associated with the characteristics of the activated muscle fibers (type I or type II) and the metabolic demand of the training protocols used in our study. During HL, type II muscle fibers may be predominantly recruited. These muscle fibers have low oxidative but high glycolytic activity [39,40] and may be more responsive to hypertrophy compared with type 1 muscle fibers [39,41]. On the other hand, LL may preferentially activate type I muscle fibers, which have low glycolytic but high oxidative capacity, and are highly fatigue-resistant [39,40]. In our study, we performed metabolomic analysis in two periods (i.e., pre- and post-training) to examine whether the acute global metabolic response changed after a period of HL or LL. As a result, when looking at the PCA plot and heat map, there was no segregation between groups or within groups pre- and post-training. The clusters formed on the heat map present a grouping when observing the period (pre- and post-training) and time of collection (0, 5, and 60 min) between the HL and LL groups, suggesting that there was no difference in the global metabolic response between the HL and LL groups, or between pre- and post-training for any group. Univariate analysis showed differences only in changes in 3-hydroxyisovalerate (both groups), asparagine (LL group) and phenylalanine (HL group) from pre- compared with post-training, with no between-group difference. The study by Gehlert, Weinisch, Romisch-Margl, Jaspers, Artati, Adamski, Dyar, Aussieker, Jacko, Bloch, Wackerhage and Kastenmuller [21] had already analyzed the metabolic response after acute resistance exercise and after an additional period of resistance training. Fourteen young male subjects with moderate resistance training experience participated in this experiment, six of whom provided sufficient muscle samples for metabolomics analysis. The first training session altered 33 metabolites, including increases in 3-methylhistidine, N-lactoylvaline, xanthosine, NAD (N1-methyl-2-pyridone-5-carboxamide), and chenodeoxycholate bile acid. The authors also compared metabolite levels after the last training session (i.e., after the training period) with those of the first training session. The comparison showed that only five of the metabolites that had changed after the acute exercise in the first training session were also changed after the last training session. However, it is important to emphasize that the study by Gehlert, Weinisch, Romisch-Margl, Jaspers, Artati, Adamski, Dyar, Aussieker, Jacko, Bloch, Wackerhage and Kastenmuller [21] did not analyze the metabolic response during low-load training, but only the response in high-load training (8 to 12 maximum repetitions). Thus, it is not possible to compare low- and high-load exercise. We chose to discuss six metabolites, as they may be related to muscle fiber properties and metabolic demand. These metabolites were: asparagine, 3-hydroxyisovalerate, acetoacetate, carnitine, creatine, and creatine-phosphate. Asparagine may have a precursor function as an energy substrate of the Krebs Cycle; it is an amino acid that can be converted into aspartate, then into oxaloacetate for use in the Krebs Cycle [42]. 3-hydroxyisovalerate is a by-product of the leucine degradation pathway, formed from 3-methylcrotonyl-CoA. The leucine degradation pathway leads to the production of acetyl-CoA, another substrate for the Krebs Cycle [43]. Interestingly, these two Krebs cycle energy substrate precursor metabolites showed a negative correlation with the increase in vastus lateralis muscle thickness for the time 0–60 min in the HL group. We hypothesize that the negative correlation was due to stimulation of a greater number of type II fibers, resulting in lower expression of metabolites related to the oxidative system, such as 3-hydroxyisovalerate and asparagine, and concomitantly greater hypertrophy due to the predisposition of type II muscle fibers to hypertrophy [39,41]. Carnitine is also related to oxidative energy production, for which a positive correlation was observed between the changes in time 0–5 min with the increase in vastus lateralis muscle thickness in the HL group. Carnitine has the function of transporting long-chain fatty acids to the mitochondria, which are later oxidized for energy production [44]. Thus, higher availability of carnitine in the circulation could indicate a lower requirement for fatty acid oxidation due to a lower activation of type I fibers, which would explain the positive correlation of this metabolite with the increase in vastus lateralis muscle thickness in the HL group due to a predominant activation of type II fibers. The concentration of acetoacetate may be another indicator of lower activity of the oxidative system and type I fibers. A positive correlation was observed between the increase in muscle thickness of the vastus lateralis in the LL group and acetoacetate in the time 0–5 min. This metabolite is a ketone body formed from some amino acids and free fatty acids and serves as an alternative source of energy substrate for peripheral tissues, such as skeletal muscle, under conditions of reduced carbohydrate availability [45,46]. In muscle, the β-hydroxybutyrate metabolite produced in the liver is re-oxidized to acetoacetate by the action of the enzyme 3-hydroxybutyrate dehydrogenase. Sequential reactions using acetoacetate lead to the formation of two acetyl-CoA molecules, which are incorporated into the Krebs Cycle for terminal oxidation and adenosine triphosphate (ATP) production [45,46]. The activity of the enzyme 3-hydroxybutyrate dehydrogenase is highest in type I fibers and lowest in type II fibers [45,47]. Therefore, higher acetoacetate levels may indicate lower oxidative system activity and of the type I fibers. In addition to the metabolites related to the oxidative system of energy production, some metabolites of the alactic anaerobic system showed a correlation with HL and LL. For creatine, a positive correlation was observed with the increase in the vastus lateralis muscle thickness in the HL group at 0–5 min. For the creatine-phosphate metabolite, a negative correlation was observed with the increase in the muscle thickness of the vastus lateralis in the LL group for the time 0–5 min. Creatine in its phosphorylated form (i.e., creatine-phosphate) provides an energy reserve for rapid ATP regeneration, especially during exercise, with high recruitment of type II fibers [39,48]. In addition to the correlation with HL, there was a period main effect, with an increase in plasma creatine levels at post- compared with pre-training. This increase may be related to muscle growth and, consequently, to the reserve of this intramuscular metabolite, which is later released into the bloodstream after performing RT. The concomitant muscle growth and increased intramuscular creatine levels have been demonstrated in previous studies, especially in experiments analyzing creatine supplementation [49,50,51]. Phenylalanine and methionine showed a negative correlation with the muscle thickness of the vastus lateralis of the HL group for the time 0–60 min. This correlation may be partly explained by the characteristic incorporation of these metabolites into synthesized proteins. Both phenylalanine and methionine are known to be used as tracers to measure the rate of protein synthesis, owing to their incorporation during protein synthesis [52,53,54,55]. In contrast to the above metabolites, which appear to correlate with muscle hypertrophy based on muscle fiber properties and metabolic demand, phenylalanine and methionine may act as regulators of protein synthesis. Increased phenylalanine release from skeletal muscle has been shown to be associated with decreased mTOR activation and a concomitant decrease in cell growth signaling [55]. Methionine is a methyl group donor involved in DNA and protein methylation through the formation of S-adenosylmethionine, which is a known indirect activator of the mTOR pathway [56,57]. Interestingly, the correlation of these metabolites was observed only for HL; we cannot explain this finding. Finally, the metabolite oxypurinol showed a positive correlation with the muscle thickness of the vastus lateralis in the LL group at time 0–60 min. This metabolite is an inhibitor of xanthine oxidase, an enzyme that generates reactive oxygen species (ROS) that converts hypoxanthine to xanthine [58]. During the execution of RT, a greater amount of ATP is consumed than can be resynthesized in the exercising muscles, which may lead to the depletion of adenosine diphosphate to maintain force production, increasing the plasmatic concentrations of hypoxanthine and, consequently, xanthine and ROS [58]. Chronically, the formation of ROS may have negative effects on muscle tissue or even induce sarcopenia [59]. Thus, a possible explanation for the positive correlation of oxypurinol with the muscle thickness of the vastus lateralis of the LL group would be that individuals with higher oxypurinol production had lower formation of ROS throughout the training period and consequently greater muscle growth compared with individuals with lower oxypurinol levels. ## 5. Conclusions Performing high- and low-load RT to concentric failure induced a similar global metabolic response and increased the strength and muscle thickness of the quadriceps muscles analyzed, although the HL showed greater muscle activation. However, correlations were observed between some metabolites from the first training session and the increase in muscle thickness in the HL and LL groups. Some correlations may be related to the characteristics of the activated muscle fibers and the metabolic demands of the training protocols used (3-hydroxyisovalerate, asparagine, acetoacetate, carnitine, creatine, and creatine-phosphate), while the others may be related to the process of protein synthesis (phenylalanine and methionine). The observation of these correlations with the increase in muscle thickness may be of great importance, as these metabolites may be used as biomarkers for muscle hypertrophy in the future. However, these results should still be interpreted with caution, and further studies are necessary to investigate the efficacy of using metabolites correlated with muscle growth as biomarkers. ## 6. Limitations Our study was not without limitations. We collected blood samples in pre- and post-training, at three time points (0 min, 5 min, and 60 min). It is possible that with more data points, we could have described a better time course of metabolic response. 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--- title: Study on the Hepatoprotective Effect Mechanism of Polysaccharides from Charred Angelica sinensis on the Layer Chickens Based on the Detection of the Intestinal Floras and Short-Chain Fatty Acids of Cecal Contents and Association Analysis authors: - Fanlin Wu - Peng Ji - Yonghao Hu - Chenchen Li - Jian He journal: Veterinary Sciences year: 2023 pmcid: PMC10058873 doi: 10.3390/vetsci10030224 license: CC BY 4.0 --- # Study on the Hepatoprotective Effect Mechanism of Polysaccharides from Charred Angelica sinensis on the Layer Chickens Based on the Detection of the Intestinal Floras and Short-Chain Fatty Acids of Cecal Contents and Association Analysis ## Abstract ### Simple Summary This study aimed to analyze the intervention mechanism of polysaccharides from charred Angelica sinensis (CASP) on the liver injury caused by Ceftiofur sodium and lipopolysaccharide from the perspective of the intestine. The detection of the intestinal floras and the short-chain fatty acids (SCFAs) of chicken cecal contents and their association analysis were carried out. The results showed that the structure of chicken liver in the normal control group was normal, while that in the model group was damaged. The structure of chicken liver in the CASP intervention group was similar to the normal control group. The intestinal floras in the model group were maladjusted compared to the normal control group. After the intervention of CASP, the diversity, and richness of chicken intestinal floras changed. The contents of acetic acid, butyric acid, and total SCFAs in the intervention group of CASP were significantly lower than those in the model group, and the contents of propionic acid and valeric acid in the intervention group of CASP were significantly lower than those in the model group and normal control group. The changes in the intestinal floras were correlated with the changes SCFAs in the cecum. It is confirmed that the liver-protecting effect of CASP is indeed related to the changes in intestinal floras and SCFAs content in the cecum. ### Abstract To analyze the intervention mechanism of polysaccharides from charred Angelica sinensis (CASP) on the liver injury caused by Ceftiofur sodium (CS) and lipopolysaccharide (LPS) from the perspective of the intestine. Ninety-four one-day-old laying chickens underwent free feeding and drinking water for three days. Then, fourteen laying chickens were randomly selected as the control group, and sixteen laying chickens were selected as the model group. Sixteen laying chickens in the rest were randomly selected as the intervention group of CASP. Chickens in the intervention group were given CASP by the oral administration (0.25 g/kg/d) for 10 days, the control and model groups were given the same amount of physiological saline. During the 8th and 10th days, laying chickens in the model and CASP intervention group were subcutaneously injected with CS at the neck. In contrast, those in the control group were subcutaneously injected with the same amount of normal saline simultaneously. Except for the control group, the layer chickens in the model and CASP intervention groups were injected with LPS after CS injection on the 10th day of the experiment. In contrast, those in the control group were injected with the same amount of normal saline at the same time. 48 h after the experiment, the liver samples of each group were collected, and the liver injury was analyzed by hematoxylin-eosin (HE) staining and transmission electron microscopy. And the cecum contents of six-layer chickens in each group were collected, and the intervention mechanism of CASP on the liver injury from the perspective of the intestine was analyzed by the 16S rDNA amplicon sequencing technology and the short-chain fatty acids (SCFAs) detection of cecal contents based on Gas Chromatography-Mass Spectrometry (GC-MS), and their association analysis was carried out. The results showed that the structure of chicken liver in the normal control group was normal, while that in the model group was damaged. The structure of chicken liver in the CASP intervention group was similar to the normal control group. The intestinal floras in the model group were maladjusted compared to the normal control group. After the intervention of CASP, the diversity, and richness of chicken intestinal floras changed significantly. It was speculated that the intervention mechanism of CASP on the chicken liver injury might be related to the abundance and proportion of Bacteroidetes and Firmicutes. Compared with the model group, the indexes of ace, chao1, observed species, and PD whole tree of chicken cecum floras in the intervention group of CASP were significantly increased ($p \leq 0.05$). The contents of acetic acid, butyric acid, and total SCFAs in the intervention group of CASP were significantly lower than those in the model group ($p \leq 0.05$), and the contents of propionic acid and valeric acid in the intervention group of CASP were significantly lower than those in the model group ($p \leq 0.05$) and normal control group ($p \leq 0.05$). The correlation analysis showed that the changes in the intestinal floras were correlated with the changes in SCFAs in the cecum. It is confirmed that the liver-protecting effect of CASP is indeed related to the changes in the intestinal floras and SCFAs content in the cecum, which provides a basis for screening liver-protecting alternative antibiotics products for poultry. ## 1. Introduction Chicken Colibacillosis (CC) is a common and important infectious disease that seriously endangers the health of chicks. Previous studies have found that the coexistence of Ceftiofur sodium (CS) and lipopolysaccharide (LPS) can cause liver damage in laying hens after curing CC with CS [1]. It is confirmed that the liver protective effect of polysaccharides from charred Angelica sinensis (CASP) is accurate, and its intervention mechanism is related to arachidonic acid metabolic and mTOR pathway [2], but it is not clear whether it is related to the changes of intestinal floras and the short-chain fatty acids (SCFAs) content in the cecum. The intestinal floras are interdependent and restricted, forming a relatively stable microecology. There is a certain correlation between intestinal floras disorder and the mechanism of liver injury [3]. Some studies have confirmed that intestinal floras could affect the physiological and pathological processes of the liver in many ways [4,5,6]. The interaction between intestinal floras and the host immune system or other types of cells could induce liver inflammation, steatosis, and fibrosis. It is very important to deeply study the mechanism of specific intestinal microorganisms in the process of liver injury and lesion repair [7]. SCFAs are closely related to intestinal floras and can affect intestinal function [8,9]. With the change of floras structure, the species and quantity of short-chain fatty acids will also change. Some scholars have tried to explore the pathogenesis and drug intervention mechanism of liver injury by studying the changes in intestinal floras and short-chain fatty acid content. Wu [10] found mussel polysaccharide “α-D-glucan” could reshape the ecological distribution of intestinal floras in high-fat diet model rats, improve the abundance of some probiotics of intestinal floras, reduce the abundance of some intestinal pathogenic microorganisms, and exert the liver protection effect by regulating SCFAs. Jin [11] found that studying the changes in cecum floras and SCFAs content helped explain the intervention mechanism of probiotics on LPS-induced liver injury. Yu et al. [ 12] found that Chinese herbal compound microecological agents could maintain intestinal health and protect the liver by promoting the reproduction of Lactobacillus in the cecum of broilers. Zhang [13] found that okra powder could alleviate obesity symptoms and liver injury by regulating abnormal blood glucose and the disorder of lipid metabolism in high-fat model mice, and effectively regulating the imbalance of intestinal floras. And the results showed okra seed oil could effectively antagonize the increase of Aspartate Transaminase, Alanine aminotransferase, and Malondialdehyde and increase the activities of Glutathione peroxidase and Total superoxide dismutase in the liver, improve the liver injury induced by alcohol in mice, and effectively intervene in the imbalance of main intestinal microorganisms. Zhu et al. [ 14] found that the liver protection mechanism of Xiaozhi decoction might be related to the increase of Lactobacillus and Bifidobacterium in the intestine. In addition, Xiaozhi decoction could improve the inflammatory reaction of hepatocytes induced by free fatty acids. Therefore, the study on the changes of floras and SCFAs content in the chicken cecum helps explore the liver protective mechanism of CASP. In this study, the liver histological observation was performed, 16S rDNA amplicon sequencing technology was used to screen the differential floras in cecal contents, GC-MS was used to detect the content of SCFAs, and the liver protection mechanism of CASP was analyzed from the perspective of the intestine through correlation analysis. ## 2.1. The Animal Experiment Program, Sampling, and Liver Histological Observation The experimental protocol was approved by the Laboratory Animal Management Committee of Gansu Agricultural University. Ninety-four laying chickens (one-day-old) (Beijing Huadu Yukou Poultry Industry Co., Ltd., Beijing, China) underwent adaptive feeding 3d. Fourteen chickens were randomly selected as the control group, and sixteen from the model group. Sixteen were randomly selected as the intervention group of CASP (self-made, 0.25 g/kg/d). The above doses were based on the pre-experiment results [15]. Chickens in the intervention group were given CASP by the oral administration (0.25 g/kg/d) for 10 days, the next two groups were given the same amount of physiological saline. Chickens in the model and intervention group were subcutaneously injected with Ceftiofur sodium (Qilu Animal Health Products Co., Ltd., Jinan, China, 5 mg/kg) at the neck on the 8th and 10th days. Chickens in the control group were injected with the same amount of normal saline. Except for the control group, the chickens in the other groups were injected with self-made LPS (Escherichia coli O78, 4 mL/kg) after CS injection on the 10th day of the experiment. Chickens in the control group were injected with the same amount of normal saline. 48 h after the experiment, the liver samples of each group were collected, and the liver injury was analyzed by HE staining (Olympus, Tokyo, Japan, DP71) and transmission electron microscopy (JEOL, Tokyo, Japan, JEM1400FLASH). And the cecum contents of six chickens in each group were collected and frozen at −80 °C. ## 2.2.1. DNA Extraction The samples were extracted by the SDS method, and then the purity and concentration of DNA were detected by agarose gel electrophoresis. Finally, the DNA was diluted to 1 ng/μL with aseptic water standby. ## 2.2.2. PCR Amplification Primers were synthesized using diluted DNA as a template (Sangon biotech, Shanghai, China). PCR reaction system and procedure (30 μL): Phusion Master Mix (2×) 15 μL (New England Biolabs, East Hanover, NJ, USA), Primer (New England Biolabs, 2 μM) 3 μL, gDNA (New England Biolabs, 1 ng/μL) 10 μL, H2O (2 μL); Reaction procedure: pre denaturation at 98 °C for 1 min; 30 cycles including (98 °C, 10 s; 50 °C, 30 s; 72 °C, 30 s); 72 °C, 5 min. PCR products were made detection by electrophoresis with agarose gel (Sigma-Aldrich, St. Louis, MO, USA, concentration of $2\%$). Then it was detected with a Gradient PCR instrument (Bio-rad, Berkeley, CA, USA, T100). ## 2.2.3. Mixing and Purification of PCR Products With the Gel DNA recovery kit (Thermo Scientific, Waltham, MA, USA), the equal concentration mixing was carried out according to the final concentration of PCR products, and a 1× TAE (Solarbio, Beijing, China) concentration of $2\%$ agarose gel electrophoresis was used for purification. Finally, the target band was recovered. ## 2.2.4. Library Construction and Computer Sequencing The library construction was completed according to the DNA library construction kit (Illumina, San Diego, CA, USA), and then Illumina Novaseq 6000 detection platform was used to complete the sequencing after Qubit quantification and library detection. ## 2.2.5. Information Analysis Process Firstly, data splicing and quality control analysis was carried out with FLASH software; Uparse was used to cluster the samples with Operational taxonomic units (OTUs), and Greengenes was used for species annotation; Then, abundance, Alpha diversity, Venn diagram, and Principal co-ordinates analysis (PCoA) were carried out for OTUs. Anosim and STAMP were used to analyze the differences in microbial community structure among groups to analyze species composition and diversity. ## 2.3.1. Standards Preparation Accurately weighed the standard of acetic acid (National Medicine ≥ $99.5\%$), propionic acid (TCI > $99.0\%$), butyric acid (TCI > $99.0\%$), isobutyric acid (National Medicine > $99.0\%$), valeric acid (TCI > $98.0\%$), isovaleric acid (TCI > $99.0\%$), and caproic acid (Aladdin ≥ $99.5\%$), and used ethyl acetate (Merck, Kenilworth, NJ, USA, GC-MS grade) to prepare the mixed standard solution with the concentration of 0.1, 0.5, 1, 5, 10, 20, 50 and 100 μg/mL. Take 600 μL standard solution, add 25 μL of 4-methyl valeric acid as internal standard (final concentration was 500 μM), carried out Gas Chromatography-Mass Spectrometry analyzer (GC-MS, Agilent, Santa Clara, CA, USA, 7890A/5975C) detection, and the injection volume was 1 μL, shunt ratio 10:1, shunt injection. ## 2.3.2. Metabolite Extraction 30 mg of samples were taken with Electronic balance (WT3003N), and $0.5\%$ phosphoric acid (National Medicine, Beijing, China, 900 μL) was added and resuspended, shaken, and mixed evenly for 2 min with the Vortex instrument (QL-866), centrifuged 14,000× g for 10 min with the Refrigerated centrifuge (Eppendorf, Hamburg, Germany, 5430R). Then the supernatant of 800 μL was taken, the same amount of ethyl acetate (Merck, GC-MS grade) was added, shaken, and mixed for 2 min with the Vortex instrument (QL-866), and centrifuged 14,000× g for 10 min with the Refrigerated centrifuge (Eppendorf, 5430R); The upper organic phase of 600 μL was taken, and 4-methyl valeric acid was added as the internal standard (the final concentration was 500 μM), at the end 1 μL was taken after mixing and was detected by GC-MS with the shunt ratio of 10:1. ## 2.3.3. QC Samples Preparation QC samples were prepared with all the samples mixed equally, which were used to investigate the stability of the detection process. ## 2.3.4. GC-MS Analysis GC conditions: DB-WAX capillary column (Agilent, 30 m × 0.25 mm ID × 0.25 μm). Programmed temperature rise: initially 90 °C, raise the temperature to 120 °C at 10 °C/min, then rise to 150 °C (5 °C/min), finally increase the temperature to 250 °C at 25 °C/min, and maintain for 2 min. The carrier gas was helium, with a carrier gas flow rate of 1.0 mL/min. MS conditions: the temperature of the injection port was 250 °C; the Ion source temperature was 230 °C; The temperatures of the quadrupole and transmission line were 150 °C and 250 °C respectively, and the electronic energy was 70 eV. ## 2.3.5. Data Processing The retention time and peak area of the chromatogram of different standards were extracted. The standard curve was established according to the concentration and peak area, and then the SCFAs contents in different groups of the cecal content samples were calculated. ## 2.4. Combined Analysis of Intestinal Floras and Short-Chain Fatty Acids For the differential floras and short-chain fatty acids screened in the early stage, the spearman method was used for correlation analysis. R language and Cytoscape software were used to carry out matrix heatmap, hierarchical clustering, and correlation network analysis. The interaction relationship between cecal microbial floras and metabolites was explored from multiple angles. ## 3.1.1. HE Staining The histopathological observation results of HE staining of chicken liver in each group are shown in Figure 1. It could be seen that compared with the normal control group, the chicken liver in the model group had severe liver cell necrosis, difficult identification of liver lobules, structural disorder, nuclear pyknosis, extensive vacuolar degeneration, fatty degeneration, and incomplete cell structure. Compared with the model group, the chicken liver cell structure of the CASP intervention group was more complete, the degeneration and necrosis of liver cells were reduced, and the arrangement was more regular. It can be seen that CASP has a definite effect on the chicken liver damage caused by CS and LPS. ## 3.1.2. Transmission Electron Microscopy The transmission electron microscopic observation results of chicken livers in each group are shown in Figure 2. In the normal control group, the morphology and structure of the hepatocytes in the chicken liver were normal, the structure of the organelles in the cytoplasm was complete and clear, no obvious lesions were found, and a small amount of primary lysosomes were occasionally seen. In the model group, the liver nuclei in the chicken liver were mostly irregular, with chromatin aggregation. Most of the rough endoplasmic reticulum in the cytoplasm had expanded, a large number of mitochondria have obvious swelling (crista dissolution and fracture), and a large number of primary lysosomes and obvious autophagy could also be seen. It could be found that after modeling with CS and LPS, chicken hepatocytes had significant pathological changes, the endoplasmic reticulum and mitochondria have been damaged, and autophagic bodies have appeared, which confirms that autophagy is indeed involved in the pathological process of liver injury caused by CS and LPS. The chicken liver morphology and structure of liver cells in the intervention group of CASP were similar to that in the normal control group, only a small amount of autophagy was found in the cytoplasm. It could be found that CASP had a good intervention effect on the pathological process of chicken liver injury caused by CS and LPS. ## 3.2.1. 16S rDNA Amplicon Sequencing Data Preprocessing and Quality Control Statistics The quality control results of the samples are listed in Table 1, which showed that this method was stable and feasible. ## 3.2.2. Analysis Results of Richness and Uniformity of Samples in Each Group The sample species have good uniformity and richness (Figure 3A). The sequencing data was reasonable, and more data would not produce new species (Figure 3B). ## 3.2.3. Venn Analysis of OTUs Distribution in Cecum Content Floras The results of OTUs clustering of cecal microorganisms with $97\%$ consistency are shown in Figure 4. The middle gray area was the common OTUs between the two groups. ## Relative Abundance of Floras Distribution at the Phylum Level The distribution of intestinal floras at the phylum level of each group is shown in Figure 5. At the phylum level, the richness of Bacteroidetes, Synergistetes, Deferribacteres, Chloroflexi, and WWE1 in the intervention group of CASP was higher, and the richness of Actinobacteria was significantly lower ($p \leq 0.05$). In the model group, Fusobacteria, Lentisphaerae, and Spirochaetes had higher richness. In the normal control group, Cyanobacteria, Tenericutes, Gemmatimonadetes, TM7, and Verrucomicrobia had higher richness (Figure 5A). Firmicutes, Bacteroidetes, and Proteobacteria were the dominant floras in the cecum contents (Figure 5B). ## Relative Abundance of Floras Distribution at the Genus Level The distribution of intestinal floras of each group at the genus level is shown in Figure 6. At the genus level, the richness of Lachnospira, Acinetobacter, Coprococcus, Adlercreutzia, Ruminococcus, Prevotella, Novispirillu, Syntrophomonas, Micrococcus, Cupriavidu, HA73, W22, Succinatimonas, Pelobacter, Sphingobacterium, Syntrophus, T78, Allobaculum, Spirosoma, Herbaspirillum, Asticcacaulis, Mucispirillum, Rubrivivax, Caulobacter, Burkholderia, Sphingomonas, Ralstonia, Sutterella, Paraprevotella, Faecalibacterium, Oscillospira, Gallibacterium, and Novosphingobium in the intervention group of CASP was higher. In the model group, the richness of Sporosarcina, Victivallis, Actinomyces, Haemophilus, Macrococcus, Treponema, Helicobacter, SMB53, Geobacillus, Lactobacillus, Proteus, Anoxybacillus, Bubacterium, Escherichia, Anaerotruncus, Blautia, Streptococcus, Enterococcus, Fusobacterium, Clostridium, Lactococcus, Veillonella, Staphylococcus, AF12, and Corynebacterium were higher. In the normal control group, the richness of Facklamia, Candidatus Arthromitus, Akkermansia, DA101, Brevibacterium, Luteimonas, Dehalobacterium, Bacillus, Jeotgalicoccus, Bifidobacterium, Granulicatella, Rhodococcus, Butyricicoccus, Turicibacter, Pseudoramibacter, Eubacterium, Anaerofustis, and Microbacterium were higher (Figure 6A). At the genus level, Bacteroides, Ruminococcus, and Lactobacillus were the top three dominant floras (Figure 6B). ## 3.2.5. The α Diversity Analysis of Cecum Content Floras in Each Group The α-diversity analysis results of cecum content floras in each group (Figure 7) showed that compared with the normal control group, the ace, chao1, observed species, and PD whole tree indexes of cecum floras in liver injury chicken decreased, and the differences were not significant, prompting that the biodiversity of intestinal floras would be reduced when the antibiotics were used. Compared with the model group, the ace, chao1, observed species, and PD whole tree indexes of chicken cecum floras in the intervention group of CASP were significantly increased ($p \leq 0.05$). ## 3.2.6. PCoA Analysis of Cecum Content Floras in Each Group The community structure differences of different groups were shown in the PCoA analysis chart (Figure 8). ## Anosim Analysis of Cecum Content Floras in Each Group Anosim analysis is a nonparametric test method based on the Bray-Curtis algorithm, which is mainly used to test whether the difference between groups is significantly greater than that within groups. As shown in Figure 9, there was a significant difference between the intervention group of CASP and the model group ($r = 0.28$, $p \leq 0.05$), indicating a significant difference in the structure of chicken cecum floras between the two groups. ## STAMP Difference Analysis of Cecum Content Floras in Each Group The results of the STAMP difference analysis at the genus level are shown in Figure 10. At the genus level, the abundances of Adlercreutzia and Faecalibacterium in the intervention group of CASP were significantly higher than those in the normal control group, and the abundance of HA73 was significantly higher than that in the normal control group and the model group ($p \leq 0.05$). The abundance of SMB53 in the intervention group of CASP was significantly lower than that in the normal control group and model group ($p \leq 0.05$), the abundance of Brevibacterium was significantly lower than that of the normal control group ($p \leq 0.05$), and the abundance of Anaerofustis was significantly lower than that of the model group ($p \leq 0.05$). ## 3.2.8. KEGG Function Prediction The KEGG function prediction results of cecum content floras in each group are shown in Figure 11. In Figure 11, it could be seen that the model group was mainly enriched in metabolic diseases, cell growth, and death, and the intervention group of CASP was mainly enriched in amino acid metabolism, cell growth, and death, and the immune system. ## 3.3.1. The Detection of SCFAs in Cecal Contents of Chickens in Each Group As shown in Figure 12, the contents of acetic acid, butyric acid, and total SCFAs in the intervention group of CASP were significantly lower than those in the model group ($p \leq 0.05$), and the contents of propionic acid and valeric acid were significantly lower than those in model group ($p \leq 0.05$) and normal control group ($p \leq 0.05$). ## 3.3.2. Heatmap Analysis between SCFAs and Different Intestinal Floras of Chicken Cecum Contents The functional abundance value can be directly expressed with colors change in the heatmap. Heatmap analysis was performed on the results of SCFAs and differential intestinal floras in cecum contents. The results are shown in Figure 13. Lactobacillus was closely related to butyric acid, acetic acid, and valeric acid in the normal control and model groups. In the normal control group and the intervention group of CASP, the relationship between Microbacterium and acetic acid, propionic acid, butyric acid, and valeric acid was close. SMB53, Anoxybacillus, Eubacterium, Streptococcus, Granulicatella, and Anaerofustis in the model group and the intervention group of CASP were closely related to propionic acid, valeric acid, butyric acid, and acetic acid, and isobutyric acid. ## 3.4.1. Correlation Analysis of Intestinal Floras and SCFAs in Chicken Cecum Contents between the Normal Control Group and the Model Group As shown in Figure 14, Lactobacillus was positively correlated with the production of valeric acid, acetic acid, and butyric acid in the normal control group and the model group. ## 3.4.2. Correlation Analysis of Intestinal Floras and SCFAs in Chicken Cecum Contents between the Normal Control Group and the Intervention Group of CASP As shown in Figure 15, Microbacterium in the normal control group and the intervention group of CASP was positively correlated with the production of butyric acid, acetic acid, propionic acid, and valeric acid. HA73 was negatively correlated with the production of propionic acid. Ruminococcus was negatively correlated with the production of isobutyric acid and valeric acid. Faecalibacterium was negatively associated with the production of valeric acid. ## 3.4.3. Correlation Analysis of Intestinal Floras and SCFAs in Chicken Cecum Contents between the Model Group and the Intervention Group of CASP As shown in Figure 16, in the model group and the intervention group of CASP, SMB53 in the model group and the intervention group of CASP was positively correlated with the production of valeric acid, acetic acid, butyric acid, and propionic acid; Granulicatella was positively correlated with the production of acetic acid and propionic acid; HA73 was negatively correlated with the production of propionic acid and butyric acid; Streptococcus was positively related to the production of propionic acid and butyric acid; W22 was negatively correlated with the production of propionic acid and butyric acid. In addition, butyric acid production was closely related to Desulfovibrio, Eubacterium, and Anoxybacillus. ## 4. Discussion This study aimed to analyze the intervention mechanism of CASP on the liver injury caused by CS and LPS from the perspective of the intestine, the detection of the intestinal floras of chicken cecal contents by the 16S rDNA amplicon sequencing technology and the SCFAs detection of cecal contents based on GC-MS and their association analysis was carried out. Firstly, the results of liver histological observation with HE staining and transmission electron microscopy showed the liver injury modeling caused by CS and LPS was successful. HE staining and transmission electron microscopy are two kinds of direct and classic methods for judging liver injury. Qiu et al. [ 16] found that HE staining and transmission electron microscopy could be used to observe the occurrence and improvement of liver fibrosis. Feng et al. [ 17] found that HE staining and transmission electron microscopy could be used to observe the occurrence and improvement of liver fibrosis. And the results of liver histological observation also showed the polysaccharides could make resistance to liver injury induced by LPS. Xu et al. [ 18] found that Dicliptera chinensis (L.) Juss (Acanthaceae) polysaccharide could resist the liver injury induced by LPS. Li et al. [ 19] found that the Plantago seed polysaccharide could resist the liver injury induced by LPS. In order to analyze the intervention mechanism of CASP on the liver injury from the perspective of the intestine, the 16S rDNA amplicon sequencing technology was carried out. Intestinal flora is closely related to liver injury [20]. Relative abundance analysis results of cecum content floras showed that at the phylum level, the richness of Bacteroidetes, Synergistetes, Deferribacteres, Chloroflexi, and WWE1 in the intervention group of CASP was higher, and the richness of Actinobacteria was significantly lower ($p \leq 0.05$), which was consistent with the previous research report [21]. Firmicutes were the largest group of bacteria in the intestinal floras, most of which were Gram-positive. Many of its members were beneficial bacteria. For example, Lactobacillus is probiotic, and the produced substances could improve the immunity of chickens [22]. In addition, Firmicutes also included such as Streptococcus and other pathogenic bacteria. In this study, the abundance of Firmicutes in chicken cecum in each group changed significantly. The increase of Bacteroidetes was positively correlated with the immunity of chickens [23]. In this study, the abundance of Bacteroidetes in chicken cecum contents decreased after liver injury. The abundance of Bacteroidetes in chickens increased significantly after being intervened by CASP, suggesting that CASP could improve the immunity of chickens. This study also showed that the abundance of TM7 decreased significantly after liver injury, suggesting that the digestive function of chickens with liver injury was affected. The abundance of TM7 in the intervention group of CASP was corrected. Liu [24] found that Fusobacteria in chicken intestinal were harmful and could inhibit the growth performance of chickens. Xing [25] found that the increase in Spirochaetes would affect chicken intestinal health and reduce intestinal digestion and absorption and mucosal immune function. Li [26] found that LPS stress could reduce the abundance of Tenericutes. Some studies have reported that the changes in the proportion of Bacteroidetes and Firmicutes would cause diseases [27,28,29]. This study found that the proportion of Bacteroidetes and Firmicutes in each group changed. Through comprehensive analysis, it was found that the intervention mechanism of CASP on chicken liver injury induced by CS and LPS may be related to the abundance of some harmful floras and beneficial floras and the proportion of Bacteroidetes and Firmicutes. According to the relative abundance analysis, results of floras distribution at the genus level, Bacteroides, Ruminococcus, and Lactobacillus were the top three dominant floras. Bacteroides’ anaerobic respiration mainly produced acetic acid, isovaleric acid, and succinic acid, which could stimulate the inner wall of the intestine to produce fucosylated glycans. Fucosylation could regulate leukocyte adhesion, regulate the development and differentiation of immune cells such as macrophages, neutrophils, and B cells, and play an essential role in many inflammatory diseases [30]. In addition, Bacteroides could stimulate epithelial angiogenesis, thus enhancing nutrient absorption. However, the nonalcoholic fatty liver could reduce the proportion of Bacteroides in the microbiota composition, indicating that liver injury would affect the abundance of Bacteroides [31]. In this study, the abundance of Bacteroides in the chicken cecum of the model group was significantly lower than that of the normal control group and the CASP intervention group. Ruminococcus, one of the most effective bacteria for decomposing carbohydrates, played an essential role in stabilizing the intestinal barrier and increasing energy. Ruminococcus was also reported as a kind of beneficial bacterium [32]. Oscillospira was an anaerobic bacterium belonging to Ruminococcus in Firmicutes, which could ferment complex plant carbohydrates. This study found that the abundance of Ruminococcus and Oscillospira in the intervention group of CASP was higher. Hepaticus in Helicobacter could cause chronic liver injury in mice [33]. Another study also found that inflammatory bowel disease was closely related to Helicobacter, and showed that T cells played an essential role in this process [34]. The results of this study showed that the abundance of Helicobacter in the chicken cecum of the model group was higher. It was speculated that the liver injury caused by CS and LPS might be related to the high abundance of Helicobacter in the chicken’s cecum. According to the α diversity analysis results of cecum content floras in each group, it may be confirmed that CASP could improve the microecological of chicken cecum content floras. And the PCoA analysis results of cecum content floras in each group also confirmed that there were differences in the coincidence degree of chicken cecum content floras in each group, indicating that after the liver injury induced by CS combined with LPS, the chicken cecum content floras changed, and the floras also changed after the intervention of CASP. The STAMP difference analysis results of cecal content floras in each group confirmed that Faecalibacterium in the intervention group of CASP were significantly higher than those in the normal control group. According to the analysis result, Faecalibacterium may be related to the enhancement of liver metabolism and growth promotion [35]. The KEGG function prediction results showed that the liver injury was mainly enriched in metabolic diseases, cell growth, and death, and the intervention effect on the liver injury of CASP was mainly enriched in amino acid metabolism, cell growth, and death, and the immune system, which was consistent with the previous conclusions [2]. The results in Figure 12 also showed that total SCFAs in the intervention group of CASP were significantly lower than those in the model group ($p \leq 0.05$). The change trend of SCFAs in the cecal contents of chickens in each group was consistent with the change trend of SCFAs in the previous research [36]. It is in accordance with the results in Figure 5A. The results in Figure 5A showed that Bacteroides abundance in the chicken caecum contents of the intervention group of CASP was the highest and that in the model group was the lowest. Bacteroides, as a member of the polysaccharide degradation alliance, were the primary source of propionic acid. It was speculated that they might be consumed by degrading undigested polysaccharides in vivo. Therefore, the propionic acid in the chicken caecum contents of the intervention group of CASP was lower. It was speculated that SCFAs might maintain homeostasis and physiological metabolism through compensatory increase after liver injury. The liver injury of chicken in the intervention group of CASP was significantly repaired. It was speculated that many SCFAs were consumed to repair liver injury. Through enterohepatic circulation, SCFAs may be transferred from the intestine to the liver to play the effect of protecting liver. In addition, SCFAs were produced by the carbohydrates in the undigested and unabsorbed food residues through anaerobic fermentation in the intestine. After the liver injury, carbohydrates in the undigested and unabsorbed food residues in the intestine stagnated. In addition, the change in the floral structures led to the increase of SCFAs produced by fermentation. In the intervention group of CASP, the liver injury of chicken was significantly repaired, and the carbohydrates in the undigested and unabsorbed food residues in the intestine decreased, the content of SCFAs produced was reduced under the change of floras structure [37,38]. In addition, some studies also showed that the Lactobacillus mixture could regulate the intestinal floras, thereby increasing the production of SCFAs and reducing Gram-negative bacteria [39], which were consistent with the results in Figure 6. The level of serum SCFAs increased in rats with nonalcoholic fatty liver disease, suggesting that SCFAs may be related to the pathogenesis of the nonalcoholic fatty liver disease [40]. Li et al. [ 41] also found the concentrations of isobutyric acid and isovaleric acid in the control group were higher than those before and after the treatment ($p \leq 0.05$). These results are consistent with those in this study. Another study found that the content of valeric acid and hexanoic acid in the stool of the non-alcoholic fatty liver fibrosis group was significantly higher than that of the healthy control group [42]. Another study found that the phytosterol ester intervention could reduce the level of short-chain fatty acids in the colon contents of rats with nonalcoholic fatty liver in varying degrees [43]. The correlation analysis results of intestinal floras and SCFAs showed Lactobacillus was positively correlated with the contents of valeric acid, acetic acid, and butyric acid in the normal control group and the model group, which was consistent with the previous literature reports [44]. Peng et al. [ 45] also found that the content of Lactobacillus in the chicken cecum was positively correlated with the content of acetic acid. ## 5. Conclusions This study confirmed that CASP could protect the liver by improving the diversity of chicken intestinal floras, affect the abundance and proportion of Bacteroidetes and Firmicutes, and interfere with the content of SCFAs in chicken cecal by affecting the abundance of Lactobacillus, SMB53, and Microbacillus. It was speculated that CASP might intervene in the chickens’ liver injury induced by CS combined with LPS by restoring intestinal floras balance and affecting the content of SCFAs. 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--- title: Incorporation of Moringa oleifera Leaf Extract in Yoghurts to Mitigate Children’s Malnutrition in Developing Countries authors: - Sandra M. Gomes - Anabela Leitão - Arminda Alves - Lúcia Santos journal: Molecules year: 2023 pmcid: PMC10058877 doi: 10.3390/molecules28062526 license: CC BY 4.0 --- # Incorporation of Moringa oleifera Leaf Extract in Yoghurts to Mitigate Children’s Malnutrition in Developing Countries ## Abstract Moringa oleifera, which is rich in bioactive compounds, has numerous biological activities and is a powerful source of antioxidants and nutrients. Therefore, M. oleifera can be incorporated into food to mitigate children’s malnutrition. In this work, the bioactive compounds were extracted from M. oleifera leaf powder by ultrasound-assisted solid-liquid extraction. The antioxidant and antimicrobial activities and the phenolic composition of the extract were evaluated. The extract presented a total phenolic content of 54.5 ± 16.8 mg gallic acid equivalents/g and IC50 values of 133.4 ± 12.3 mg/L for DPPH and 60.0 ± 9.9 mg/L for ABTS. Catechin, chlorogenic acid, and epicatechin were the main phenolics identified by HPLC-DAD. The obtained extract and M. oleifera leaf powder were incorporated into yoghurts and their physicochemical and biological properties were studied. The incorporation of M. oleifera did not impair the yoghurts’ stability over eight weeks when compared to both negative and positive controls. The extract presented higher stability regarding syneresis but lower stability regarding TPC compared to the powder. Also, the fortified yoghurts presented higher antioxidant properties than the negative control. These findings highlight the potential use of M. oleifera powder and extract as natural additives to produce fortified foods that can be used in the mitigation of malnutrition. ## 1. Introduction Moringa oleifera, a plant from the Moringaceae family, has gained attention all over the world due to its nutritional and bioactive properties. This tree is native to India and grows in tropical and subtropical environments [1]. Most parts of M. oleifera are edible and they provide numerous biological activities, such as antioxidant, antimicrobial, anti-inflammatory, antidiabetic, anticarcinogenic, hepatoprotective, and cardioprotective effects [2,3,4,5,6,7,8]. These therapeutic activities can be attributed to a diverse group of bioactive compounds present in M. oleifera, such as phenolic compounds and carotenoids. The leaves, in particular, are rich in phenolic compounds, which are secondary metabolites of plants known for their antioxidant properties. These properties can be attributed to the phenolic group (Figure 1) [9]. The most common phenolics found in M. oleifera leaves are flavonoids (e.g., epicatechin, catechin, quercetin, kaempferol) and phenolic acids (e.g., gallic acid, chlorogenic acid, caffeic acid) [10,11,12]. Other families of polyphenols, such as lignans, can also be found in M. oleifera leaves [13]. Phenolic compounds can be extracted from M. oleifera using polar solvents, such as water and ethanol, since these compounds are relatively polar. More specifically, $50\%$ and $70\%$ aqueous ethanol have shown to be more efficient in extracting phenolic compounds from different plant parts [14,15,16,17,18,19]. The phenolic content found in M. oleifera leaves’ extracts varies with the origin of the plant, as well as the extraction conditions. Therefore, the values reported in the literature for the total phenolic content (TPC) of these extracts can vary from 4–700 mg of gallic acid equivalents (GAE)/g of dried extract [10,20]. In addition, M. oleifera can serve as a supplement against malnutrition since it is a powerful source of nutritional compounds, such as proteins, fats, carbohydrates, fibre, vitamins, and minerals. The most common vitamins in M. oleifera are B1, B2, B3, C, and E, while minerals include calcium, phosphorous, and potassium. Compared to other commonly consumed food, M. oleifera presents 9 times more protein than yoghurt, 17 times more calcium than milk, 25 times more iron than spinach, and 15 times more potassium than bananas. Also, it contains 10 times more vitamin A and 7 times more vitamin C than carrots and oranges, respectively [21,22]. Several in vitro and in vivo studies were performed to analyse the toxicity of M. oleifera leaf powder and extracts. Experiments with normal human cell lines demonstrated that the extracts from the leaves are generally safe; however, some cytotoxicity can be observed depending on the dose [1]. One study showed that aqueous leaf extract with concentrations superior to 20 mg/mL was cytotoxic to human peripheral blood mononuclear cells [23]. In another study, ethanolic leaf extracts were considered safe for fibroblasts at concentrations ranging from 0.02 μg/mL to 100 μg/mL [24]. In vivo studies using rats demonstrated the safety of M. oleifera leaf powder and extracts [1], which only presented acute toxicity in extremely high dosages (3000 mg/kg) [23]. Finally, no adverse effects were reported in any human studies using M. oleifera leaf powder. There are still no studies on humans regarding leaf extracts [25]. Therefore, toxicity studies are fundamental to ensure that the use of supplements derived from M. oleifera leaves are safe for human health. Due to its broad spectrum of biological activities, M. oleifera can be used in food, pharmaceutical, and cosmetical applications [10,26,27,28,29,30,31,32,33,34,35,36,37,38]. By combining its extraordinary nutritional value with the presence of bioactive compounds, such as phenolic compounds, M. oleifera, more particularly its leaves, is a good candidate to produce fortified food to mitigate children’s malnutrition in developing countries (Figure 2). Dairy products are consumed worldwide. They are mostly ingested in the form of fresh dairy products, including yoghurt, especially in developing countries [39]. However, since these products present considerable amounts of fats, they are prone to lipid oxidation [40]. This process leads to the formation of secondary metabolites that can produce an unpleasant flavour and diminish the nutritional properties of the product, decreasing its shelf-life [41]. Since M. oleifera leaves are rich in phenolic compounds with antioxidant properties, they can be a natural source of antioxidants to be used in the fortification of food products, increasing their shelf-life (Figure 1). Also, antioxidant compounds are particularly valuable to human health since they can protect the cells against free radicals and reduce oxidative stress, which may reduce the risk of developing certain diseases, such as cancer and heart disease [42]. Numerous studies have shown the potential use of M. oleifera as a natural food additive to improve dairy products’ properties and nutritional value (Table 1). Although several studies explored the incorporation of M. oleifera in dairy products’ properties, very few analysed the antioxidant properties of yoghurts fortified with M. oleifera leaves, particularly the leaf powder. Also, the literature review produced no papers that analyse the phenolic composition of the M. oleifera-derived ingredients added to dairy products. Therefore, this study aimed to produce fortified yoghurts that can be used to mitigate malnutrition. The study evaluated the effect of M. oleifera leaf powder and extract on the stability of the yoghurt, as well as its antioxidant and antimicrobial activities. Moreover, the main phenolic compounds present in M. oleifera extract were quantified to match the extract’s biological properties to its phenolic composition. Finally, the potential use of M. oleifera as a natural food ingredient was assessed and compared to a synthetic additive. ## 2.1. Extraction of Bioactive Compounds from M. oleifera Leaves In the present study, the phenolic compounds from M. oleifera leaf powder were extracted using $70\%$ ethanol. The extraction yield can be influenced by numerous aspects, such as the extraction method, solvent, time, temperature, and the sample’s mass-to-solvent volume ratio [15,17,19,53]. In general, higher extraction times generate higher extraction yields. However, when high temperatures are applied to extract phenolic compounds, longer periods of extraction can impair the extraction yield since these compounds can be degraded by high temperatures [54]. Ultrasounds can also influence the extraction yield of the compounds of interest. Ultrasounds generate cavitation bubbles within the solvent; eventually, the bubbles collapse and disrupt the cell walls of the solid matrix, releasing the bioactive compounds into the liquid phase (i.e., the solvent) [20]. In the same way, the agitation also helps to disrupt the cell walls of the plant material. Therefore, both ultrasounds and agitation can help improve the yield of the extraction. In this study, the extraction yield was 34.1 ± $0.9\%$. Other literature reports used similar extraction methods to extract bioactive compounds from M. oleifera. In one study, mechanical agitation was performed for 24 h at 25 °C, using $80\%$ ethanol to extract the compounds of interest from M. oleifera leaf powder. The extraction yield obtained was $45.12\%$, higher than the one presented in this work. This might be explained by the higher extraction time used (24 h vs. 3 h) [55]. In another study, the extracts from M. oleifera were obtained under constant magnetic stirring for 2 h at 25 °C, using $50\%$ ethanol as solvent. Here, the extraction yield obtained was lower than the one of the present work ($26.94\%$), which may indicate that the use of ultrasounds before mechanical agitation may improve the extraction of bioactive compounds [53]. ## 2.2. Characterization of M. oleifera Extract The extract was characterized regarding its total phenolic content (TPC) and antioxidant and antibacterial properties. The obtained results are described in Table 2. The M. oleifera leaf extract presented a TPC of 54.5 ± 16.8 mgGAE/gdried extract. Once again, the extraction method and conditions can influence this parameter, as well as the plant origin. For example, the impact of the drying process used in the pre-treatment of M. oleifera leaves (freeze-dried, air-dried, sun-dried, or oven-dried) on the phenolic content of the extracts was analysed. The bioactive compounds were extracted for 24 h on an orbital shaker using water as the solvent and it was observed that the TPC was influenced by the drying process, with the freeze-dried technique obtaining a higher content of phenolics (68.75 mgGAE/g). The leaves dried in the oven, the same drying process used in our work, presented a TPC of 46.88 mgGAE/g, inferior to the value obtained in this paper [12]. These results may indicate that the ultrasound-assisted solid-liquid extraction method used in the present study may be more suitable for the extraction of phenolic compounds. In another work, the effect of the extraction method on the TPC was also analysed. The investigators showed that mechanical agitation for 24 h was more efficient in the phenolics’ extraction than sonication for 30 min three times. The extracts obtained with the agitation method presented higher TPC (74.87 mgGAE/g) than the one obtained in our work, but the extraction time was also significantly superior [55]. Regarding the antioxidant capacity, the IC50 values obtained represent the extract concentration necessary to inhibit $50\%$ of the free radicals (DPPH or ABTS). It is possible to observe, from Table 2, that M. oleifera extract presents a higher antioxidant capacity towards ABTS, since a smaller amount of extract is needed to inhibit the radicals to the same extent. This higher capacity to inhibit ABTS compared to DPPH was also described by other researchers [11,55]. Similar IC50 values were obtained for DPPH and ABTS in another study (139.60 mg/L and 57.07 mg/L, respectively) where magnetic agitation was performed for 24 h [55]. In our work, M. oleifera leaf powder was placed in an ultrasonic bath for 30 min prior to 2.5 h in agitation. The use of ultrasounds reduced the time of mechanical agitation needed to obtain similar DPPH and ABTS inhibitions. Concerning the antibacterial activity, it was not possible to identify any inhibition halo, which does not mean that the extract cannot inhibit the growth of E. coli and S. aureus since the halo can be present underneath the disk. Although other studies report the antibacterial effect of M. oleifera leaf extract against these microorganisms, the concentrations tested are particularly higher than the ones analysed in this study, which may account for the differences in the results obtained [34,47]. To better understand the biological properties exhibited by the M. oleifera extract, an HPLC-DAD analysis was performed to identify and quantify the phenolic compounds present in the extract obtained. From Table 3, it is possible to observe that catechin was the major phenolic compound found in the leaf extract. Other flavonoids, such as epicatechin, quercetin, and kaempferol were also detected. The main phenolic acid present was chlorogenic acid, followed by caffeic acid and gallic acid. Previous studies have already reported the presence of these compounds in M. oleifera leaf extract [10,12]. The values obtained in the literature present some variability since the origin and cultivar conditions of M. oleifera tree, as well as the extraction method used to extract the phenolics can affect the compounds’ concentration. In one report, quercetin and kaempferol were identified and quantified. The concentrations obtained were 0.07 mg/g for quercetin and 0.03 mg/g for kaempferol, which were very similar to the ones obtained in the present study [20]. However, other studies present higher concentrations of phenolic compounds. In one study, where the seven phenolic compounds were also studied, the concentrations ranged from 19.65 mg/g for kaempferol to 65.83 mg/g for chlorogenic acid [12]. In another study, the concentrations obtained for chlorogenic acid, epicatechin, gallic acid, kaempferol, and quercetin were also superior to the values obtained in our work, but the concentration of catechin was very similar (20.19 mg/g) [56]. The different origins of the plants (Nigeria vs. Angola) may account for the different compositions obtained. Since phenolic compounds are known for their antioxidant properties; the antioxidant capacity of the extract against free radicals, such as DPPH and ABTS, demonstrated in this study is in accordance with the presence of natural antioxidant compounds in the extract’s matrix like the ones identified by HPLC. ## 2.3.1. Physicochemical Properties Five yoghurt formulations were produced in this work: a negative control with no additives (NC), a positive control with sorbic acid (PC; a synthetic preservative), two formulations with M. oleifera leaf extract at different concentrations (1.0 g/L, ME, and 2.0 g/L, ME2) and, finally, a formulation with 2.9 g/L M. oleifera leaf powder (MP). From Figure 3, it is possible to observe that a homogenised product was obtained for all formulations, except for MP yoghurt where it was not possible to completely dissolve the powder. Regarding the colour, fortified yoghurts (ME, ME2, and MP) presented slightly beige colours compared to the controls. The stability of the yoghurts produced was analysed by evaluating their physicochemical properties such as pH, syneresis, water holding capacity, and viscosity throughout eight weeks. pH can play a major role in food quality and safety and in yoghurts is usually below 4.6 [57]. From Figure 4, it is possible to confirm that the pH values obtained for all formulations are below 4.6. After production, all formulations presented similar pH values, except PC yoghurt. which presented a slightly higher value. Moreover, a reduction in the pH was observed over time for all formulations; this may be explained by the increase in lactic acid that occurs during yoghurt fermentation [58]. The decrease in the pH value during the eight weeks of the study was higher for NC yoghurt and lower for the fortified yoghurts, and in particular MP yoghurt, which did not present statistically different pH values in the first four weeks. Also, higher concentrations of M. oleifera extract did not affect the pH of yoghurts since ME and ME2 formulations presented statistically similar pH values throughout the study. Hence, the results reveal that the incorporation of M. oleifera did not compromise the pH of the yoghurts. Furthermore, the fortification of the yoghurts with both extract and powder of the leaves of M. oleifera seems a promising strategy to improve the pH stability of the product. During yoghurt production, whey proteins from milk are denatured and can interact with each other, forming soluble aggregates, or with casein micelles, forming micelles coated with whey protein. The structure of the yoghurt is given by the interactions between k-casein and whey proteins through disulphide and hydrophobic bonds on the surface of casein micelles [59]. Syneresis refers to the release of whey (serum) from the yoghurt matrix, which results in undesirable sensory properties, making the product less appealing to the consumer [60]. Increasing the water holding capacity (WHC) is a possible strategy to decrease the yoghurt’s susceptibility to syneresis [61]. Therefore, the syneresis and WHC of the yoghurts were analysed over time to understand if the fortification impaired their stability. Eight weeks after production (t3) all formulations presented slightly higher syneresis compared to the values obtained after production (t0), except for MP yoghurt which presented a slight decrease; ME formulation was the one that presented syneresis values more stable along the eight weeks. On the other hand, WHC decreased in the same period of time, except for the ME formulation where WHC values were more stable. For both syneresis and WHC, the values obtained for ME2 formulation were less stable than for ME formulation. The higher phenolic composition of ME2 may explain these results since phenolic compounds can interact with both casein and whey proteins [62], which could have implications on the yoghurt’s structure. Although fortified yoghurts did not present an increase in the WHC, it was observed that the addition of M. oleifera to the yoghurts’ matrix was able to diminish the increase of the syneresis over eight weeks. Hence, this preliminary data indicates that the incorporation of the extract and powder obtained from M. oleifera leaves in yoghurts did not impair their physicochemical properties. However, these results must be confirmed in future studies. Lastly, the viscosity of the yoghurts was also analysed. The apparent viscosity of the formulations was determined, with the shear rate varying from 0.01–100 s−1. From Figure 5A, it is possible to notice that the addition of M. oleifera to the yoghurt’s composition did not alter the viscosity behaviour of the yoghurts right after production, with all formulations presenting very similar viscosity values. Only PC yoghurt presented slightly lower values for shear rates inferior to 20 s−1. Eight weeks after the production, it was possible to observe differences in the viscosity values between the formulations and in comparison to the initial results, with MP yoghurt presenting a higher difference over time (Figure 5B). However, for shear rates superior to 20 s−1 this was not observed and the values obtained were very similar to all formulations. Despite the variations in the values obtained, the behaviour of the yoghurts remained the same, with apparent viscosity decreasing until shear rate values of approximately 15 s−1 were reached and then increasing, converging to the same viscosity value (around 5 × 103 mPa·s) in both timepoints. The obtained values for the consistency index, K, and flow consistency index, n, are presented in Table 4. From these results, it is possible to observe that all formulations can be considered non-Newtonian fluids with a pseudoplastic behaviour since the obtained flow behaviour indexes were inferior to 1. This type of fluid presents a shear-thinning behaviour, meaning that the apparent viscosity of the yoghurts decreases with an increase in the shear rate, which is true for shear rates inferior to 15 s−1. Although all formulations presented a similar behaviour after production (t0), it was observed that, after eight weeks (t3), the incorporation of M. oleifera in yoghurts reduced their shear-thinning behaviour (higher flow consistency index values), which can be related to a lower breakage of intramolecular and intermolecular bonds in the yoghurt matrix [63]. The viscosity behaviour of the yoghurts was also analysed as a function of the temperature (Figure 6). When the temperature increased from 2 °C to 25 °C, an increase in the fluidity of the formulations was observed since their viscosity decreased. On the other hand, when the temperature followed the inverse direction (from 25 °C to 2 °C), an increase in viscosity was observed. However, the viscosity values did not return the initial ones, showing that the change in viscosity due to temperature variations is a process that cannot be reversed. Therefore, these changes in the temperature may cause irreversible modifications in the yoghurts’ structure. The results obtained from the physicochemical characterization showed that M. oleifera extract and powder can be used to fortify yoghurt without significantly affecting their properties and stability. ## 2.3.2. Antioxidant and Antibacterial Activities The biological properties of the yoghurts produced were also analysed. For that, the total phenolic content and the antioxidant and antibacterial activities of all formulations were assessed. The results obtained for the TPC of the yoghurts are presented in Table 5. It is possible to observe that the positive control (PC) did not present statistically higher TPC compared to the negative control (NC). On the other hand, the fortification of the yoghurts with M. oleifera significantly increased the phenolic content of the formulations throughout the entire period of the study. This was expected considering the phenolic compounds present in M. oleifera. The results also showed that the TPC of all yoghurts decreased over time, but the values were always higher in the fortified yoghurts. This reduction of phenolics during storage was also described in other studies [30,64]. This may be explained by the biotransformation of phenolic compounds by the probiotics present in the yoghurt [65]. Comparing ME to ME2, besides exhibiting higher phenolic content, ME2 presented a slightly lower reduction of the TPC during the eight weeks. Regarding ME and MP, although they presented similar TPC after production, differences were observed after eight weeks, with MP presenting higher phenolic content than ME. These results demonstrated that although a decrease was observed in the TPC of all yoghurts, the reduction in MP was lower and also slower (significant differences were only observed from four to eight weeks). Regarding the antioxidant properties, it is possible to observe, from Figure 7 that all formulations presented a higher inhibition capacity towards ABTS than DPPH. These results were expected since M. oleifera extract exhibited higher antioxidant capacity in the ABTS assay. Also, another study has shown that plain yoghurt is more efficient at inhibiting ABTS radicals than DPPH radicals [66]. Concerning the DPPH assay (Figure 7A), the fortified yoghurts presented a higher inhibition of DPPH during the first two weeks. However, after two weeks, only ME2 yoghurt displayed higher radical inhibition than the controls. Considering the ABTS assay (Figure 7B), the addition of M. oleifera, either the extract or powder, improved the antioxidant capacity of the yoghurts against this radical throughout the eight weeks of the study. The milk protein hydrolysis that occurs during yoghurt production can contribute to the antioxidant properties presented [67]. Nevertheless, this study demonstrated that the incorporation of M. oleifera improved the antioxidant potential of the yoghurts, mainly due to their phenolic composition. Furthermore, all fortified yoghurts presented better antioxidant properties than PC yoghurt, except in the DPPH assay for t2 and t3 (four and eight weeks after production, respectively), where only ME2 presented better results. These results demonstrated the great potential of the use of M. oleifera powder and extract as natural antioxidants that can be incorporated into food to replace the synthetic compounds typically used. The antibacterial activity of the yoghurts was analysed against Gram-negative bacteria E. coli and Gram-positive bacteria S. aureus, and the results are expressed in Table 6. The incorporation of M. oleifera in the yoghurt did not increase its antibacterial activity, which is in accordance with the characterization of the extract, which did not present antibacterial activity against these bacteria. Also, a decrease was observed in the antibacterial activity against both E. coli and S. aureus over time. Furthermore, yoghurts demonstrated higher antibacterial capacity against S. aureus than E. coli. These results may be explained by the optimum pH conditions at which these bacteria grow: 6.0–7.0 for E. coli and 7.0–7.5 for S. aureus [68]. Since all yoghurt formulations presented a pH inferior to 4.1, these results were expected. Hereupon, these findings suggest that, although in the concentrations tested the addition of M. oleifera leaf extract and powder to the yoghurt did not change their antibacterial activity, the incorporation of these natural phenolic-reach additives improve the antioxidant properties of the product. ## 2.3.3. Microbial Analysis The presence of microorganisms in food can impair its properties and threaten human health. Therefore, the microbial analysis of food products is extremely important as a check for the presence of microorganisms. The European Commission defined 102 CFU/g as the limit of microorganisms that can be found in yoghurts to assure consumer safety [69]. In this work, the presence of coliform microorganisms was accessed using LSA medium while the presence of yeast and moulds was evaluated using RBC medium, four and eight weeks after the production of the yoghurts (t2 and t3, respectively). No microorganisms were detected, in both media, even after eight weeks of storage (0 CFU/mL). These findings may suggest that the formulations’ acidic pH generates an adverse environment for microbial growth. Furthermore, since the results were below the legal limits, the inclusion of M. oleifera had no impact on the safety of the consumers. ## 3.1.1. Samples Small branches with fresh mature leaves were collected from three Moringa oleifera trees in Luanda, Angola (8°57′24.9″ S, 13°13′02.9″ E). Upon arrival at the laboratory, the branches were washed with running tap water and the leaves were removed. The leaves were spread out on trays to dry, beginning at room temperature (about 30 °C) and ending in an oven at 50 °C until they were a constant weight. After this drying process, which lasted about two weeks, the leaves were crispy and ready for grinding. The grinding was done in a coffee grinder, using small amounts of leaves and the same grinding speed to obtain a fine powder with the same granulometry, with a particle size < 250 μm. To produce yoghurt, UHT semi-skimmed milk and yoghurt with probiotics were purchased from a supermarket in Porto, Portugal. ## 3.1.2. Reagents To analyse the total phenolic content, Folin–Ciocalteu reagent (Ref. 47641), from Sigma-Aldrich (St. Louis, MO, USA), and sodium carbonate (Ref. 1.06392, CNa2O3, CAS 497-19-8), from Merck (Darmstadt, Germany), were used. To evaluate the antioxidant capacity, 2,2-diphenyl-1-picrylhydrazyl (Ref. D9132, C18H12N5O6, CAS 1898-66-4) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (Ref. A1888, C18H24N6O6S4, CAS 30931-67-0) were purchased from Sigma-Aldrich (St. Louis, MO, USA). For the antibacterial analysis, agar (Ref. J637, CAS 9002-18-0) and Plate Count Agar (Ref. 84608.0500) were obtained from VWR (Radnor, PA, USA), Rose-Bengal Chloramphenicol Agar (Ref. 1.00467.0500) was acquired from Merck (Darmstadt, Germany) and m-Lauryl Sulfate Broth (Ref. 0734) was purchased from Sigma-Aldrich (St. Louis, MO, USA). Sorbic acid (Ref. S1626, C6H8O2, CAS 110-44-1), used as a control in yoghurt production, was acquired from Sigma-Aldrich (St. Louis, MO, USA). For extraction and analysis, dimethyl sulfoxide (Ref. 41640, C2H6OS, CAS 67-68-5), from Honeywell (Charlotte, NC, USA), and ethanol (Ref. 83813.360, C2H6O, CAS 64-17-5), acetic acid (Ref. 20104.312, C2H4O2, CAS 64-19-7) and acetonitrile (Ref. 83639.320, C2H3N, CAS 75-05-8) obtained from VWR (Radnor, PA, USA) were used. Milli-Q water was purified with a water purification equipment, with 18.2 Ω of electrical resistance (Millipore, Burlington, MA, USA). ## 3.1.3. Analytical Standards for HPLC-DAD Analysis For analytical purposes, 7 flavonoids and phenolic acids were used: caffeic acid (Ref. C0625, C9H8O4, CAS 331-39-5), (+)-catechin hydrate (Ref. C1251, C15H14O6, CAS 225937-10-0), chlorogenic acid (Ref. C3878, C16H18O9, CAS 327-97-9), (−)-epicatechin (Ref. E1753, C15H14O6, CAS 490-46-0), gallic acid (Ref. 91215, C7H6O5, CAS 149-91-7), kaempferol (Ref. 60010, C15H10O6, CAS 520-18-3) and quercetin (Ref. Q4951, C15H10O7, CAS 117-39-5) were purchased from Sigma-Aldrich (St. Louis, MO, USA). All standards used were HPLC grade. ## 3.2. Extraction of Bioactive Compounds from Moring Leaf Powder An ultrasound-assisted solid-liquid extraction method was used to extract the phenolic compounds from M. oleifera leaf powder. The samples were mixed with $70\%$ ethanol in a ratio of 1 g of sample to 40 mL of solvent and placed in a J. P. Selecta 3000617 ultrasonic bath ($\frac{50}{60}$ kHz, 420 W, Barcelona, Spain) for 30 min at room temperature. Afterwards, the mixture was placed in a water bath under agitation (250 rpm) at 50 °C for 2.5 h to complete the extraction. Finally, the samples were filtered using a Whatman No. 1 paper and the solvent was completely evaporated using a rotary evaporator Rotavapor R-200 (BUCHI Laboratories, Switzerland), followed by lyophilisation. The extracts were stored at −4 °C. The extractions were conducted in triplicate to determine the extraction yield using Equation [1]:Extraction Yield (%) = (mextract/msample) × 100[1] where mextract is the mass of the extract obtained and msample is the mass of M. oleifera leaf powder used in the extraction. ## 3.3.1. Total Phenolic Content To quantify the total phenolic content (TPC) of the extracts, the Folin–Ciocalteu method was used. First, 20 μL of the extract (1 g/L in ethanol) was mixed with 1580 μL of water and 100 μL of Folin–Ciocalteu reagent. After 3–6 min, 300 μL of sodium carbonate (333.3 g/L in water) was added and the mixture was incubated for 2 h in the dark at room temperature. Finally, the absorbance was analysed at 750 nm using a Thermo GENESYS™ 10UV UV-Vis spectrophotometer (Thermo Fisher Scientific, Waltham, MA, EUA) [70]. All measurements were performed in triplicate. The results were expressed in mg gallic acid equivalents (GAE)/g dried extract, after preparing a gallic acid calibration curve (0.5–10 mg/L). ## 3.3.2. Antioxidant Capacity The antioxidant capacity of the extract was analysed using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, according to the literature, with some modifications [71]. Briefly, 20 μL of the extract (0.1–2.5 g/L in ethanol) was incubated with 180 μL of a DPPH solution (150 μmol/L in ethanol) for 40 min in the dark, at room temperature. Then, the absorbance was analysed at 515 nm. All measurements were performed in triplicate. The inhibition percentage of DPPH was calculated using Equation [2], where Abssample is the absorbance of the extract, Absblank is the absorbance of 20 μL of water with 180 μL of ethanol and Abscontrol is the absorbance of 20 μL of water with 180 μL of DPPH solution, after incubation. Finally, the IC50 value of the extract was determined using a calibration curve of the percentage of DPPH inhibition versus the extract concentration. DPPH inhibition (%) = (1 − (Abssample − Absblank)/(Abscontrol − Absblank)) × 100[2] The 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assay was also used to analyse the extract’s antioxidant capacity, following the literature protocol [72]. First, 20 μL of the extract (0.1–1.0 g/L in ethanol) was incubated with 180 μL of ABTS reactive solution for 15 min at room temperature, protected from the light. Afterwards, the absorbance was analysed at 734 nm. All measurements were performed in triplicate. The percentage of inhibition of ABTS radical was determined using Equation [3], where Abssample is the absorbance of the extract and Abscontrol is the absorbance of 20 μL of 0.05M acetate buffer (pH 4.6) with 180 μL of ABTS reactive solution, after incubation. Finally, the IC50 value of the extract was determined using a calibration curve of the percentage of ABTS inhibition vs. the extract concentration. ABTS inhibition (%) = (Abscontrol − Abssample)/Abscontrol × 100[3] ## 3.3.3. Antibacterial Activity The antibacterial activity of the extract was analysed by the disk diffusion test. Extract solutions (0.5 g/mL and 1.0 g/mL) were prepared in $2\%$ aqueous dimethyl sulfoxide (DMSO). Bacterial suspensions of Escherichia coli and Staphylococcus aureus were prepared, with an optical density of 0.1 at 610 nm, and plated in Plate Count Agar (PCA) medium. Afterwards, sterile disks were added to the plates and 7 µL of the extract solution was added to the disks in triplicate. Ultrapure water was used as the negative control and sorbic acid as the positive control. The plates were incubated for 24 h at 37 °C and the diameter of the inhibition halos was measured [73]. ## 3.3.4. Analysis of Phenolic Compounds by HPLC-DAD To identify and quantify the phenolic compounds of the extract, high-performance liquid chromatography (HPLC) was performed using an Elite LaChrom HPLC system (Hitachi, Japan), equipped with a Hitachi L-2200 autosampler, L-2130 pump, and L-2455 diode array detector (DAD). A Puroshper® STAR RP-18 endcapped LiChroCART® chromatography column (Merck, Germany) was used. Acetonitrile:water:ethanol (2:1:1 v/v/v) was used as a solvent to prepare standards and samples solutions. The sample solution was prepared by resuspending the extract obtained in 10 mL of the solvent. As eluents, Milli -Q water with $0.5\%$ of orthophosphoric acid was used for the mobile phase A and methanol:acetonitrile (80:20 v/v) was used for the mobile phase B. The gradient was as follows: 0–10 min, $10\%$ B; 10–25 min, $15\%$ B; 25–40 min, $30\%$ B; 40–50 min $50\%$ B; 50–60 min, $70\%$ B. The eluent flow rate and the injection volume were 0.8 mL/min and 40 μL, respectively. Analytes were identified by their retention time (RT) and measured accordingly to their maximum absorption wavelength: catechin and epicatechin—222 nm; gallic acid—275 nm; caffeic acid and chlorogenic acid—322 nm; kaempferol and quercetin—365 nm. Calibration curves were prepared and phenolic compounds were quantified by the external standard method. ## 3.4.1. Yoghurt Production The yoghurt was produced as described in the literature, with slight modifications [66]. Briefly, 1 L of UHT semi-skimmed milk was heated to 40 °C. Then, 125 mg of a commercial yoghurt with probiotics was added and the mixture was homogenised using a glass rod. Finally, the mixture was incubated at 37 °C for 16 h and then stored at 4 °C. Different formulations of yoghurt were produced and the additives used are described in Table 7. Sorbic acid was used as the positive control since it is a commonly used additive in yoghurts. M. oleifera extract and leaf powder were used as natural preservatives. The extract was added at the same level and twice the concentration of sorbic acid (formulations ME and ME2, respectively). The leaf powder added to the yoghurt (formulation MP) was equivalent to the extract added to formulation ME. The physicochemical characteristics, stability, and microbiological safety of the yoghurts were analysed for 8 weeks with four timepoints: t0—after production; t1—two weeks after production; t2—four weeks after production; and t3—eight weeks after production. ## 3.4.2. pH Determination To determine the pH value of the yoghurts produced, they were dissolved in ultrapure water (1:9 m/V). The mixture was homogenised using a T18 Digital Ultra-Turrax (IKA, Staufen, Germany) for 1 min at 300 rpm and the pH of the samples was determined using a digital pH meter [66]. All measurements were performed in triplicate. ## 3.4.3. Syneresis The protocol to determine the syneresis of the samples, which represents the amount of whey expelled from the yoghurt, was adapted from the literature [74]. Briefly, 3 g of yoghurt was centrifuged for 20 min at 700 rpm. Then, the supernatant was discarded and the precipitate was weighed. Equation [4] was used to determine the syneresis of the samples:Syneresis (%) = (msupernantant/myoghurt) × 100[4] where msupernatant is the difference between the initial mass of the yoghurt and the mass of the precipitate and myoghurt is the initial mass of the yoghurt. ## 3.4.4. Water Holding Capacity The water holding capacity (WHC) was determined according to the literature [75]. For that, 7.5 mL of distilled water was added to 0.25 g of each yoghurt. The samples were vortexed for 1 min and then centrifuged for 20 min at 3000 rpm. Afterwards, the supernatant was discarded and the precipitate was collected and weighed. The precipitate was dried for 5 h at 105 °C and the WHC was determined using Equation [5]:WHC = (mfresh precipitate − mdried precipitate)/mdried precipitate[5] where mfresh precipitate is the mass of the precipitate before drying and mdried precipitate is the mass of the precipitate after drying. ## 3.4.5. Viscosity To study the viscosity of the yoghurts, the apparent viscosity (mPa·s) was measured using an MCR 92 rheometer (Anton Paar, Graz, Austria). The apparent viscosity was analysed for different shear rates (0.01–100 s−1) at a constant temperature (25 °C). The effect of the temperature on the apparent viscosity of the samples was also analysed by varying the temperature from 2 °C to 25 °C and then back to 2 °C again, at a constant shear rate (50 s−1). ## 3.4.6. Total Phenolic Content and Antioxidant Capacity To analyse the antioxidant properties of the yoghurts, an extraction of the phenolics was performed. For that, 8 mL of ethanol were added to 2 g of each sample. The mixture was vortexed for 1 min, followed by an ultrasonic bath for 5 min. This process was repeated twice more. Finally, the samples were centrifuged at 3000 rpm for 20 min and the supernatant was collected and stored at 4 °C, in the dark, for further analysis of the TPC and antioxidant capacity (DPPH and ABTS) of the yoghurts, according to the protocols described in Section 3.3.1 and Section 3.3.2, respectively. ## 3.4.7. Antibacterial Activity To analyse the antimicrobial activity of the yoghurts, the well diffusion assay was used, which is similar to the disk diffusion assay described in Section 3.3.3. but with slight modifications. Instead of sterile disks, small wells were made in the PCA plates with a glass Pasteur pipette. Each sample was added to a well in triplicate. The diameter of the inhibition halos was measured after incubating the plates for 24 h at 37 °C. E. coli and S. aureus were again the model bacteria chosen to analyse the antimicrobial activity of the yoghurts and the bacterial suspensions were prepared as explained above. ## 3.4.8. Microbial Safety For this analysis, Lauryl Sulphate Agar (LSA) and Rose Bengal Chloramphenicol Agar (RBC) were used since they are selective to coliform microorganisms, and to yeast and moulds, respectively. The yoghurts were serially diluted in a saline solution (1:10 v/v) two times. Then, 100 μL of each solution was plated in both mediums. The LSA plates were incubated at 37 °C for 24 h, while the RBC plates were incubated for 7 days at 25 °C. Afterwards, the plates were checked for the presence of microorganisms. ## 3.5. Statistical Analysis For the statistical analysis, an analysis of variance (ANOVA) was performed using the Tukey’s multiple comparisons test. GraphPad Prism 8.0.2 was used and values with $p \leq 0.05$ ($95\%$ confidence interval) were considered statistically different. ## 4. Conclusions The purpose of this study was to evaluate the use of natural ingredients obtained from Moringa oleifera leaves in food fortification. A good extraction yield was obtained using ultrasound-assisted solid-liquid extraction, and the obtained extract presented antioxidant properties, with higher activity against ABTS compared to DPPH. However, no antibacterial activity was detected against Escherichia coli and Staphylococcus aureus. Seven main phenolic compounds were identified in the extract, namely caffeic, chlorogenic and gallic acids, catechin, epicatechin, kaempferol and quercetin. These results demonstrated that M. oleifera leaf extract has an interesting phenolic composition and, consequently, antioxidant capacity. This is an important property for its potential incorporation in food products that are susceptible to oxidation, such as the case of yoghurt. The yoghurts fortified with M. oleifera powder or extract presented slightly better stability than the negative control and improved antioxidant properties compared to both negative and positive controls. An increase in the extract concentration increased the total phenolic content of the formulation but reduced its stability regarding syneresis and water holding capacity. Comparing the leaf powder with the extract, the first presented a lower reduction in the TPC after eight weeks but also poorer stability regarding syneresis. All formulations demonstrated higher antibacterial activity against S. aureus than E. coli and no microbial contamination was detected after eight weeks of storage. The obtained results demonstrate that both M. oleifera powder and extract can be incorporated into yoghurt, creating a fortified food product that can be used to combat children’s malnutrition in developing countries. 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--- title: 'Development and Characterization of Hydroxyethyl Cellulose-Based Gels Containing Lactobacilli Strains: Evaluation of Antimicrobial Effects in In Vitro and Ex Vivo Models' authors: - Marcela Almeida dos Santos de Sousa - Alexia Figueiredo Ferreira - Camila Caetano da Silva - Marcos Andrade Silva - Tamyris Alicely Xavier Nogueira Bazan - Cristina de Andrade Monteiro - Andrea de Souza Monteiro - Joicy Cortez de Sá Sousa - Luís Cláudio Nascimento da Silva - Adrielle Zagmignan journal: Pharmaceuticals year: 2023 pmcid: PMC10058878 doi: 10.3390/ph16030468 license: CC BY 4.0 --- # Development and Characterization of Hydroxyethyl Cellulose-Based Gels Containing Lactobacilli Strains: Evaluation of Antimicrobial Effects in In Vitro and Ex Vivo Models ## Abstract This study aimed to develop a hydroxyethyl cellulose-based topical formulation containing probiotics and to evaluate its antimicrobial action using in vivo and ex vivo models. Initially, the antagonistic effects of Lacticaseibacillus rhamnosus ATCC 10863, Limosilactobacillus fermentum ATCC 23271, Lactiplantibacillus plantarum ATCC 8014 and Lactiplantibacillus plantarum LP-G18-A11 were analyzed against Enterococcus faecalis ATCC 29212, Klebsiella pneumoniae ATCC 700603, Staphylococcus aureus ATCC 27853 and Pseudomonas aeruginosa ATCC 2785. The best action was seen for L. plantarum LP-G18-A11, which presented high inhibition against S. aureus and P. aeruginosa. Then, lactobacilli strains were incorporated into hydroxyethyl cellulose-based gels (natrosol); however, only the LP-G18-A11-incorporated gels ($5\%$ and $3\%$) showed antimicrobial effects. The LP-G18-A11 gel ($5\%$) maintained its antimicrobial effects and viability up to 14 and 90 days at 25 °C and 4 °C, respectively. In the ex vivo assay using porcine skin, the LP-G18-A11 gel ($5\%$) significantly reduced the skin loads of S. aureus and P. aeruginosa after 24 h, while only P. aeruginosa was reduced after 72 h. Moreover, the LP-G18-A11 gel ($5\%$) showed stability in the preliminary and accelerated assays. Taken together, the results show the antimicrobial potential of L. plantarum LP-G18-A11, which may be applied in the development of new dressings for the treatment of infected wounds. ## 1. Introduction The skin is the largest organ of the human body; this fact makes it a tissue susceptible to trauma and injury, with a significant impact on the individual and on the health system in the treatment and rehabilitation process [1]. The main skin function is to protect the internal organs, preventing the entry of microorganisms and harmful agents that can be harmful to health, as well as protecting against water loss and ultraviolet radiation [2,3]. The continuous loss of skin can be caused by different situations, such as physical, chemical, mechanical, vascular, infectious, allergic, thermal trauma or even by surgical cutting [4]. As it is an organ highly exposed to various external situations, many cases of skin and soft tissue infections are caused by so-called ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter species) that belong to the bacteria resistant against almost all commonly used antibiotics [5]. Among them, S. aureus and P. aeruginosa are commonly isolated from chronic wounds and cause the increase in resistance to topical antibiotics causing serious damage to health agencies [6]. The indiscriminate use of antibiotics has caused high rates of bacterial resistance, which leads to a risk to the quality of human health, intensifying clinical conditions that are difficult to treat and the risk of hospital infections, both of which are considered public health problems [7]. Moreover, the side effects of conventional therapies and the costs of infected-wound treatment increase the relevance of the development of novel topical agents [8]. Thus, lactobacilli strains have been widely used for wound healing, scar reduction, as well as infections being treating in vitro and in vivo treatments [9,10,11]. In this context, the topical application of lactobacilli has been suggested as a new alternative for wound treatment, due to their immunomodulatory and healing abilities, in addition to exhibiting antagonistic effects against pathogens through competitive exclusion [12,13]. To convey these probiotics, there are several vehicles or pharmaceutical formulations, such as cream, gels, cream-gels, ointments. The vehicle choice is made according to the specifications to guarantee the bacterial viability (as a probiotic product) and product stability, with it being necessary to observe factors such as the chemical and physical stability of the preparation, the proper preservation against microbial contamination and the uniformity of the active ingredient used [14]. Polysaccharides-based gels, such as those from cellulose and its derivatives, have been used for the development of healing formulations due their high biocompatibility and adsorption capacity, promoting a humid environment for the wound [10,15,16]. An example is natrosol, a hydroxyethyl cellulose-based gel with non-ionic characteristics, biodegradability and biocompatibility. This low-cost vehicle can tolerate a wide pH variation, in addition to having already shown healing activity [17,18,19]. Thus, the incorporation of lactobacilli strains with antimicrobial activity in natrosol gel is an interesting alternative for the treatment of infected wounds. Therefore, this study aimed to develop topical formulations with probiotics for application in wound treatment. For this, the antimicrobial actions of four lactobacilli strains (Lacticaseibacillus rhamnosus ATCC 10863, Limosilactobacillus fermentum ATCC 23271, Lactiplantibacillus plantarum ATCC 8014 and Lactiplantibacillus plantarum LP-G18-A11) were screened against E. faecalis ATCC 29212, K. pneumoniae ATCC 700603, S. aureus ATCC 27853 and P. aeruginosa ATCC 2785. The strain with a higher inhibitory potential was selected for the formulation of a gel, which was characterized, and its antimicrobial effects were analyzed using an ex vivo model of an infected wound with porcine skin. ## 2.1. Antagonism Potential of Strains Initially, the antimicrobial action of the four selected lactobacilli were evaluated against E. faecalis ATCC 29212, K. pneumoniae ATCC 700603, S. aureus ATCC 27853 and P. aeruginosa ATCC 2785, as shown in Table 1. All of the lactobacilli strains showed high inhibition capacity against S. aureus [inhibition zone (IZ) > 6 mm], where L. plantarum LP-G18-A11 showed higher action (IZ = 12.5 ± 0.2). Regarding P. aeruginosa, only L. plantarum LP-G18-A11 showed high inhibition capacity (IZ = 8.5 ± 0.1), while none of the tested strains inhibited the growth of K. pneumoniae and E. faecalis. ## 2.2. Antimicrobial Activity of Natrosol Gel with Lactiplantibacillus plantarum LP-G18-A11 Subsequently, two formulations of natrosol gel ($1.5\%$ w/v) were manipulated using L. plantarum LP-G18-A11 at $5\%$ or $3\%$. The other strains were incorporated into the respective gels only at $5\%$ (due the lower antimicrobial action when compared with LP-G18-A11). The antimicrobial actions of these gels were evaluated against P. aeruginosa and S. aureus. Both LP-G18-A11-gels exhibited inhibitory effects (Table 2), with higher action observed for the formulation at $5\%$. The gels formulated with the other lactobacilli strains did not inhibit the growth of P. aeruginosa and S. aureus. ## 2.3. Viability of Lactiplantibacillus plantarum LP-G18-A11 in Natrosol Gel Based on the above results, the LP-G18-A11-incorporated gels were selected for the following assays. The gels were stored at 25 °C and 4 °C and their bacterial viability was analyzed up to 90 days. In the first 14 days, the bacteria remained viable in both formulations and storage conditions (variation of 7.6 to 8.9 Log CFU/mL). After this period, there was a progressive loss of viable cells, where the bacterial incorporated into the gels kept at 25 °C lost their viability after 21 days of storage. The gels that remained refrigerated showed bacterial counts between 5 and 6 Log CFU/mL up to 30 days. In addition, the $5\%$ gel showed bacterial populations of 5 Log CFU/mL after 90 days of storage (Figure 1). ## 2.4. Time-Kill Curve Given the best results obtained with the L. plantarum LP-G18-A11 at $5\%$, a time-kill analysis was performed using S. aureus as the model. Significant reductions ($p \leq 0.05$) were observed after 2 h of contact with the L. plantarum LP-G18-A11-incorporated gel. After 4 h, no growth was detected for S. aureus and this effect remained until 30 h (Figure 2). Furthermore, the L. plantarum LP-G18-A11 remained viable throughout the trial (~10 Log CFU/mL). ## 2.5. Antimicrobial Activity of LP-G18-A11-Incorporated Gel (5%) in Wound Ex Vivo Model The antimicrobial effects of the LP-G18-A11-incorporated gel ($5\%$) were further analyzed in an ex vivo model using porcine skin. In this assay, experimental wounds were performed in the porcine skin and contaminated with S. aureus and P. aeruginosa. After 24 h, the contaminated wounds were treated with the LP-G18-A11-incorporated gel ($5\%$) and exhibited a reduced number of bacteria ($p \leq 0.05$). The reductions in the CFU counts were $31\%$ and $52\%$ for S. aureus and P. aeruginosa, respectively. These results were similar to those obtained with ciprofloxacin ($37\%$ and $62\%$, respectively) (Figure 3A,B). After 72 h of treatment, no reduction was observed for S. aureus in the wounds treated by the gels incorporated with LP-G18-A11 or ciprofloxacin (Figure 3C). On the other hand, in the wounds contaminated with P. aeruginosa, reductions of $25\%$ and $35\%$ were observed for the gels containing LP-G18-A11 or ciprofloxacin, respectively (Figure 3D). ## 2.6. Evaluation of Formulation Stability The gel containing $5\%$ L. plantarum LP-G18-A11 was submitted to the centrifugation test. The gel remained unchanged during all three centrifugation cycles, without presenting phase separation, color change or the same change in color and odor. Therefore, it was suitable to perform the other stability tests. ## 2.6.1. Preliminary Stability Test In the preliminary test, the samples were evaluated for fourteen days, undergoing cycles of heating (on study at 45 ± 2 °C) and cooling (freezer at −7 °C). The gel containing L. plantarum LP-G18-A11 did not show significant changes in its physical-chemical and organoleptic characteristics, although variations were observed in the pH of the formulation on different days (Table 3). ## 2.6.2. Accelerated Stability Test In the accelerated stability test, the gel containing L. plantarum LP-G18-A11 was subjected to different storage temperatures, namely: room temperature (25 ± 2 °C), high temperature (37 °C) and low temperature (2 °C), for a period of 30 days. The organoleptic and physical-chemical characteristics are shown in Table 4. It was seen that, after 15 days, there was a slight change in the appearance of the gel when stored at 25 °C and at 37 °C, a fact that was not observed when it was subjected to the preliminary stability tests. A slight decrease in the pH was also seen over the days in all storage forms (Table 4). ## 3. Discussion Skin infections are among the most common infectious diseases, ranked as the fourth cause of human disease [6,20,21]. The growing resistance presented by skin pathogens is considered to be the main problem in the treatment of skin infections in hospitalized patients. This results in a significant increase in morbidity and mortality as the usual antibiotics are not effective [22,23]. This scenario denotes the urgent need for new alternatives to treat or prevent this condition. In this context, this study aimed to develop a gel with lactobacilli with antimicrobial potential for dermatological use. Firstly, we reported that all of the analyzed strains (L. rhamnosus ATCC 10863, L. fermentum ATCC 23271, L. plantarum ATCC 8014, and L. plantarum LP-G18-A11) inhibited the growth of S. aureus, while only L. plantarum LP-G18-A11 had a good result against P. aeruginosa. The antimicrobial effects of the lactobacilli strains are related to the release of bacteriocins and other bioactive molecules whose properties inhibit the growth of pathogenic microorganisms and/or interfere with the quorum sensing systems [24,25,26]. These bacteriocins and bioactive molecules may vary from one strain to another, which would explain the opposite results [27]. In fact, a wide range of studies have verified the antibacterial properties of lactobacilli strains against P. aeruginosa and S. aureus. For instance, two different studies showed that L. plantarum 34-5 showed antagonistic activity on clinical isolates of P. aeruginosa [28,29]. Other studies reported the antimicrobial and antivirulence properties of L. plantarum F-10 [30] and L. plantarum USM8613 against S. aureus [31]. Therefore, the use of a formulation holding probiotics has been proposed as an alternative to the use of antibiotics [32,33]. The four lactobacilli strains were incorporated into natrosol gels, a hydroxyethyl cellulose-based formulation with a suitable consistency and pH for application on the skin that has been used for the development of healing products [34,35]. In addition, the osmotic properties of a hydroxyethyl cellulose-based formulation allow it to absorb the liquids released from the wounded tissues [36,37]. The antimicrobial effects of the gels containing the lactobacilli were verified against S. aureus and P. aeruginosa. The best inhibitory activity was found for the L. plantarum LP-G18-A11-incorporated gels at $5\%$ and $3\%$. Subsequently, the viability of L. plantarum LP-G18-A11 in the gels was analyzed for three months. This test is of paramount importance, as one of the biggest challenges in using lactobacilli as the active ingredient is its viability in cosmetic formulations. This evaluation is critical to determine the shelf life of the formulation [38]. One strategy to improve the viability is the use of its lyophilized form, and even then, depending on the storage conditions, it may become unfeasible in a few days [39]. This approach was employed in our study and enabled the viability to remain for up to 14 and 90 days at 25 °C and 4 °C, respectively. In addition, the time-to-death curve test was performed with the L. plantarum LP-G18-A11-incorporated gel ($5\%$), which totally inhibited S. aureus growth after 4 h. It was observed that the probiotic associated in the formulation remained viable for a longer time when stored in the refrigerator, which is in agreement with the study that evaluated the viability of lactobacilli strains when stored at a low temperature [40]. Similar results were also observed in a vaginal gel formulation containing Lactobacillus crispatus ATCC 33197 for the prevention of gonorrhea, which confirmed its longer viability when stored at 4 °C, although its viability dropped dramatically after two weeks [41]. The antimicrobial action of the L. plantarum LP-G18-A11-incorporated gel ($5\%$) was further analyzed in an ex vivo of a wound infection using porcine skin. This model is low-cost and represents an interesting alternative as porcine skin offers histological similarity to human skin [42,43], and it mimics how microorganisms can grow and develop in vivo [44,45]. In addition, porcine skin has been already employed to evaluate the antimicrobial activity of L. plantarum USM8613 against S. aureus [31]. Stability evaluations are essential for the development of cosmetic formulations, as the active principles that are incorporated into cosmetic vehicles can change their characteristics, causing instability and altering the quality requirements [13,46]. The gel that served as the cosmetic vehicle for this research is recommended by the National Health Surveillance Agency (ANVISA) of Brazil. This vehicle maintained the antimicrobial action of L. plantarum LP-G18-A11 and allowed its viability. The incorporation of this strain did not significantly change the gel characteristics. It is noteworthy that maintaining the stability of the product is essential to ensure its safety and efficacy, in addition to guaranteeing the content of the active ingredient in the formulation and estimating its useful lifespan [47]. The decrease in the pH of the formulations stored in different environments may be related to the production of some acid metabolite or the decomposition of some raw material during the heating process [48]. The changes that can occur in products, such as changes in the homogeneity and organoleptic characteristics (color and odor) may be indicative of possible physical-chemical changes that may be occurring in the product [46]. ## 4.1. Obtaining and Activating the Microorganism The strains L. rhamnosus ATCC 10863, L. fermentum ATCC 23271, L. plantarum ATCC 8014, S. aureus ATCC 27853, K. pneumoniae ATCC 700603, E. faecalis ATCC 29212 and P. aeruginosa ATCC 27856 were obtained from the Microbial culture collection of CEUMA University, where they are kept at −80 °C. The strain L. plantarum LP-G18-A11 was commercially purchased. The lactobacilli strains were activated in a MRS broth (De Man, Rogosa and Sharpe), while the other strains were activated in a BHI medium (Brain Heart Infusion Broth). ## 4.2. Antagonism Assay-Spot Overlay Assay The antagonistic activities of the lactobacilli strains against the selected isolates (S. aureus ATCC 27853, K. pneumoniae ATCC 700603, E. faecalis ATCC 29212 and P. aeruginosa ATCC 27856) were performed using the spot overlay technique. Five microliters of bacterial suspensions (1 × 108 CFU/mL) of each probiotic were spotted on the surface of the MRS agar plate, followed by incubation at 37 °C and $5\%$ CO2. After 48 h, the lactobacilli colonies were overlayed with 15 mL of BHI agar ($0.8\%$ agar) containing the respective pathogenic strain at a 1 × 108 CFU/mL. After 24 h incubation, the inhibition zones were measured and interpretated, determined by the formula suggested by Halder and Mandal [49]:IZ = (dnib − dspot)/2[1] where “dinib” represents the diameter of the no-growth zone surrounding the “spot” and “dspot” denotes the diameter of the tested probiotic growth zone. For the scores of the growth inhibition results, the following were considered: without inhibition capacity when R < 2 mm; low inhibition capacity with “R” values of 2–5 mm, and high inhibition capacity with “R” values > 6 mm [49]. ## 4.3. Probiotic-Based Gel Formulation For the preparation of the gel, hydroxyethyl cellulose was used as a thickening agent, responsible for the viscosity of the formulation and which has non-ionic characteristics. Glycerin was used as the wetting agent, to prevent the product from losing water to the external environment. The handling was performed according to the Brazilian Pharmacopoeia [47], with adaptations. All components of the formulation were weighed on a precision analytical balance in a container that was sterilized at 121 °C for 15 min. Sterile distilled water was heated to 70 °C for the subsequent melting of the humectant, and the thickening agent was gradually homogenized in water using a vortex until complete dissolution. After cooling, the lyophilized probiotics were homogenized using a vortex at concentrations of $3\%$ (CFU/mL) and $5\%$ (CFU/mL) in individualized formulations. The entire procedure was performed in a laminar flow cabin. The formulations were submitted to stability tests according to the tests proposed by the ANVISA cosmetic stability guide [47]. ## 4.4.1. Agar Diffusion Test Bacterial suspensions (100 μL; 1 × 108 CFU/mL) of S. aureus ATCC 25923 and P. aeruginosa ATCC 27856 were added to 10 mL of Mueller-Hinton medium, stabilized at 45 °C. The culture medium was poured into 90 mm petri dishes (with 20 mL of medium per plate) and left until it solidified [50]. Next, 4 wells, 9 mm in diameter, were made with sterilized straws and filled with hydroxyethyl cellulose-based gels containing $5\%$ or $3\%$ of the respective lactobacilli strain. The plates were subsequently incubated at 37 °C for 24 h. The tests were performed in triplicates. After 24 h, the halos formed around the wells were analyzed. ## 4.4.2. Time-Kill Curve To determine the antimicrobial activity of the L. plantarum-incorporated gel under the influence of time, the methodology described in M26-A of the Clinical and Laboratory Standards Institute [51] was followed, with adaptation. Initially, an inoculum of S. aureus in MRS-MH medium (1:2) was adjusted to 1.5 × 108 CFU/mL. After this adjustment, the inoculum was diluted at a ratio of 1:20 in MRS-MH broth, reducing the concentration to 5 × 106 CFU/mL. Then, 3 mL of this was added to each flask containing 27 mL of MRS-MH broth medium. One of the flasks was supplemented with the L. plantarum-based gel, the other served as a positive control, containing only S. aureus. The flasks were incubated at 37 °C for 30 h, with the aliquots removed, and serially diluted and plated at times of 0, 2, 4, 6, 8, 24 and 48 h after the addition of the bacterial inoculum. The viability of L. plantarum was confirmed by plating (without counting) at all analysis times. The results were expressed in CFU/mL by counting the colonies after 20–24 h of plate incubation [14]. ## 4.5. Viability and Storage Time of the Gel The quantification of the viability of the lactobacillus strains was performed by plating the bacteria after serial dilutions in saline solution and plating in MRS agar medium, incubated for 48 h at 37 °C, and the storage time for 3 months was verified, with the plating every 7 days in the first month and monthly after the first month [52]. ## 4.6. Evaluation of Formulation Stability The preliminary evaluation consisted of two tests: centrifugation and thermal stress. The macroscopic aspects and viscosity were evaluated according to the Cosmetic Products Stability Guide, where: IM: moderate intensity; -M: modified; -LM: slightly modified; -B: normal, no change in appearance [47]. ## 4.6.1. Appearance and Homogeneity of the Formulation Periodically, evaluations were conducted to evaluate changes in the color, odor, viscosity and homogeneity; the reference parameter was the product itself right after handling, in which all these initial parameters were recorded to serve as a guide. The physical characteristics of the sample were analyzed, placing the product in a 25 mL test tube and contrasting it against a dark background, as the gel color is light, according to the Brazilian Pharmacopoeia [47]. ## 4.6.2. Spin Test In a 15 mL tube, 5 g of the sample was weighed and submitted to three cycles at 3000 rpm each for thirty minutes. The test was conducted in triplicate. ## 4.6.3. Preliminary Stability During the 14 days, the samples were submitted to a cycle of freezing and thawing (Table 5). The organoleptic, physical-chemical and chemical alterations were evaluated at time T0, T2, T4, T6, T8, T10, T12 and T14. ## 4.6.4. Accelerated Stability The samples were stored in a plastic container at room temperature, indirect light (25 ± 2 °C), refrigerator (5 ± 2 °C) and oven (37 ± 2 °C), and they were evaluated for three months, verifying the organoleptic, physical-chemical and chemical characteristics, with the analysis being read at time T0, T7, T15, T30 [28]. ## 4.7. Assessment of Physicochemical Stability The samples were stored at room temperature, indirect light (25 ± 2 °C), refrigerator (5 ± 2 °C) and oven (37 ± 2 °C) and were collected at time 0, 07, 15 and 30 days for the physical-chemical evaluation of the appearance, homogeneity, pH, viscosity, density and content of the active substance [47]. ## 4.7.1. Macroscopic Evaluation During the storage, changes in the organoleptic characteristics (color, odor and appearance) and in the formulation state (phase separation, precipitation and turbidity) were analyzed. ## 4.7.2. Determination of the pH Value The pH was determined according to the aqueous dispersion of $10\%$ (1:10) of the sample in distilled water and the measurement was made in a table pH meter, duly calibrated with standardized stock solutions. The aqueous dispersion containing the gel was placed in a 250 mL backer at room temperature (25.0 ± 2 °C) and the electrode was introduced into the solution. ## 4.7.3. Density Density was performed using an already calibrated 50 mL pycnometer. The density was determined by weighing the empty pycnometer, recording its value and subsequently determining the value of the pycnometer containing the test formulation. It is determined using the formula:Density (d) = (m sample − m empty)/(m water − m empty) [2] where: m sample = mass of the pycnometer filled with the sample, m water = mass of pycnometer filled with distilled water, m empty = mass of empty and dry pycnometer. ## 4.8.1. Obtaining, Processing and Disinfecting Porcine Skin The porcine skin was collected in a regulated slaughterhouse in the city of São Luís (Maranhão, São Luís). The skin sample was frozen until the experiment was conducted. The thawed skin was cut into 2 × 2 cm fragments using a scalpel and the disinfection process consisted of placing the skin fragments, with the aid of sterile tweezers, for 30 min in a sterile bottle containing 50 mL of $70\%$ ethyl alcohol. Then, they were transferred to another sterile bottle containing $0.615\%$ sodium hypochlorite for 30 min; finally, the skin fragments were placed in a sterile flask with 50 mL of distilled water for 30 min, then placed in sterile petri dishes for drying [43]. To form the wound, a punch (n° 8) was used to delineate the dimensions [45]. The punch was introduced into the dermis; then, with the aid of a scalpel, the demarcated tissue was removed. ## 4.8.2. Wound Infection and Treatment The skin fragments were individually placed in a Petri dish holding bacteriological agar at 7 g/L for stabilization and hydration. Bacterial inoculums were prepared according to McFarland’s 0.5 scale in falcon tubes containing BHI broth with $1\%$ glucose. Later, 25 μL of bacterial inoculum was added to each wound. Then, the plates were placed at 37 °C. After 24 and 72 h, each wound was treated with the gel containing the probiotic. The skin fragments were used as the growth control, which were filled with gel only. All of the experiments were performed in triplicate [42,45]. ## 4.8.3. Quantification of Colony Forming Units (CFU) For the CFU quantification, 50 µL of PBS was added to the wound bed and then 50 µL was aspirated. Subsequently, a cotton swab was introduced perpendicularly into the wound bed and rotated 360°, twice, and transferred to tubes holding 1 mL of saline + Tween 20 (5 µL/mL) for the detachment of the bacterial cells. [ 35] The tubes were vortexed for 1 min and 100 µL of each suspension was submitted to a serial dilution in sterile saline solution of 1:10; 1:100; 1:1000; 1:10,000 and 1:100,000. Subsequently, 10 µL of the 1:10,000 and 1:100,000 dilutions were seeded in duplicate on the selective medium (mannitol and Macconkey agar) and incubated at 37 °C for 24 h for CFU counting [42]. ## 4.9. Statistical Analysis The results were expressed as the mean ± standard error of the mean. The inhibition percentages were calculated with the mean of the inhibitions obtained for each individual experiment. The statistical evaluation of the results was performed using analysis of variance (ANOVA), followed by the Boferroni or Kruskal—Wallis test, for the parametric and non-parametric data, respectively, and a significance level of 0.05 was adopted. ## 5. Conclusions The present study showed the effectiveness of using strains with probiotic potential in reducing the growth of P. aeruginosa and S. aureus, which are frequently found in wounds. L. plantarum LP-G18-A11, the strain with the highest antimicrobial potential, presented high viability in the formulated natrosol gel during storage and maintained its inhibitory effects. The incorporation of L. plantarum LP-G18-A11 also did not change the organoleptic and physical-chemical characteristics of the gel. Finally, it was proven that the LP-G18-A11-incorporated gel was able to reduce the bacterial load in an ex vivo wound model using porcine skin. 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--- title: 2D/3D Wound Segmentation and Measurement Based on a Robot-Driven Reconstruction System authors: - Damir Filko - Emmanuel Karlo Nyarko journal: Sensors (Basel, Switzerland) year: 2023 pmcid: PMC10058897 doi: 10.3390/s23063298 license: CC BY 4.0 --- # 2D/3D Wound Segmentation and Measurement Based on a Robot-Driven Reconstruction System ## Abstract Chronic wounds, are a worldwide health problem affecting populations and economies as a whole. With the increase in age-related diseases, obesity, and diabetes, the costs of chronic wound healing will further increase. Wound assessment should be fast and accurate in order to reduce possible complications and thus shorten the wound healing process. This paper describes an automatic wound segmentation based on a wound recording system built upon a 7-DoF robot arm with an attached RGB-D camera and high-precision 3D scanner. The developed system represents a novel combination of 2D and 3D segmentation, where the 2D segmentation is based on the MobileNetV2 classifier and the 3D component is based on the active contour model, which works on the 3D mesh to further refine the wound contour. The end output is the 3D model of only the wound surface without the surrounding healthy skin and geometric parameters in the form of perimeter, area, and volume. ## 1. Introduction Chronic wounds are slow to heal, and if ineffective treatment is used, the healing process may be further delayed. Clinicians need an objective method of wound assessment to determine whether current treatment is appropriate or needs to be adjusted. Measuring wounds accurately is an important task in the management of chronic wounds since changes in the physical parameters of the wound are signs of healing progress. The analysis of chronic wounds mainly involves contact and non-contact methods. Contact methods, including alginate molds, transparency tracing, manual planimetry with rulers and injection of color dyes, are considered traditional and were the most commonly used in the past [1,2]. These methods are usually impractical for medical personnel and very painful for patients. Since wounds can be of any shape, these methods are also often inaccurate and imprecise. Increasing computational capabilities of modern hardware has boosted the application of non-contact wound analysis. Additionally, progress in data analysis has led to the accelerated increase in the application of digital imaging in wound assessment. Marijanovic et al. [ 3] provide a recent overview of chronic wound analysis using non-contact methods. Since the wound might theoretically be located on any part of the body and could be of any size or shape, the wound recording process is frequently challenging. The majority of chronic wounds that are discussed in this paper are typically seen on the back or on the legs. Back wounds, e.g., pressure ulcers, typically occur on flatter surfaces, but are often much greater in size than leg wounds (Figure 1a). On the other hand, leg wounds, such as venous and diabetic ulcers, are typically shallow and located on areas of the body that are highly curved (Figure 1b). Chronic wounds can have a dynamic surface geometry because they experience expansion and reduction phases during the course of treatment. As a result, some areas of the wound may occlude other areas when viewed from specific angles. The recording technique can be rather challenging when reconstructing 3D models of such wounds, involving numerous phases and recording poses. This can be quite tiring if done manually with a hand-held 3D camera or sensor, and since human operators lack precision, such reconstructed 3D models may, at best, miss some details or, at worst, have anomalies [4]. Recently, an automated system has been developed that has a much higher precision than human operators and is able to record wounds from different viewpoints. It tracks the state of the recording process and enforces a specified density of surface samples on all parts of the recorded wound surface [5]. The research presented in this paper is based on this developed system and extends the idea of a full automated system that outputs precise geometric measurements of wounds. Physicians can monitor patients’ progress and promptly administer the right therapy with the help of such measurements and the tracking of their development over time. The research presented in this paper is comparable to that in [4], which also focuses on the 3D reconstruction, segmentation, and measurement of chronic wounds, but uses very different technologies. The authors in [4] used handheld RGB-D cameras, which are significantly cheaper, but have significant drawbacks in terms of depth accuracy and the influence of surface features and lighting conditions. Because they were handheld cameras, the accuracy of the reconstruction was also affected by the experience of the operator. In the current research, a sophisticated 7-DoF robotic arm is used with an industrial high-precision 3D scanner attached to the end effector to enable a fully automated and accurate 3D reconstruction process. In order to facilitate the measurement of physical parameters, a precise segmentation of the wound surface from the reconstructed 3D model needs to be performed, which is the main topic of this paper. A segmented wound would enable the measurement of the perimeter of its border, and in the case of surface wounds, its area. For wounds with greater depth, a virtual skin top must be generated, which then enables the calculation of the area of the virtual skin surface and its enclosed volume. The main scientific contribution of this paper is a novel segmentation algorithm using a combination of 2D and 3D procedures to correctly segment a 3D wound model. The segmentation of multiple 2D photographs per wound is driven by a deep neural network in the form of the MobileNetV2 classifier, which is then optimally combined with a single 3D model and initialization of the initial wound contour. This initial wound contour on a reconstructed 3D model is then optimized and adjusted by an active contour model, which then tightly envelops the actual wound surface using surface curvature to achieve its objective. The remainder of the paper is organized as follows. A brief overview of relevant research is provided in Section 2. A hardware and software setup of the created system is described in Section 3. Section 4 describes the implementation of individual components of the segmentation algorithm. Section 5 discusses the performance of the developed algorithm, while Section 6 concludes the paper. ## 2. Related Research The technique of assigning each pixel of an image into one of two categories, wound and non-wound, or separating the wound area from the rest of the image (surrounding healthy tissue or image background), is known as wound segmentation. The accuracy of segmentation is essential for various wound analysis activities such as tissue categorization, 3D reconstruction, wound measuring, and wound healing evaluation. Extracting the visual features of each location is essential for identifying the wound because the wound area typically has different visual features than the healthy skin. Researchers have employed a variety of approaches to perform 2D wound segmentation, including using K-means clustering [6,7], deep neural networks [8,9,10,11,12,13,14,15], support vector machines [16,17], k-nearest neighbors [4], and simple feedforward networks [18]. Other approaches include using superpixel region-growing algorithms, color histograms, or combined geometric and visual information of the wound surface to segment wounds. A systematic review of 115 papers dealing with image-based AI in wound assessment was performed by Anisuzzaman et al. [ 12]. Their final conclusion was that each of the mentioned approaches had some limitations and, hence, no method could be said to be preferable to the others. The most popular methods by far implement deep neural networks. A deep convolutional neural network architecture called MobileNetV2 was proposed by Wang et al. [ 11] for wound segmentation. The network was pre-trained using the Pascal VOC dataset prior to training. The output of the trained neural network model was a segmented grayscale image of the wound, with each pixel indicating the probability of representing a wound pixel. This image then underwent several post-processed steps: thresholding to initial create a binary image, hole filling, and the removal of small regions, thereby resulting in a final binary image or segmentation mask. In the same paper, the authors proved the superiority of their model by comparing with four other deep neural network models (VGG16, SegNet, U-Net, and Mask-RCNN) using the Medetec dataset [19]. A segmentation technique made up of the U-Net and LinkNet deep neural networks was proposed by Mahbod et al. in [13]. These deep neural networks are basically encoder–decoder convolutional networks. These networks were pre-trained using images from the Medetec database [19], and then trained on the MICCAI 2021 Foot Ulcer Segmentation (FUSeg) Challenge dataset [20], thereby resulting in two separate models. Both models evaluate the test image, and the combined output of their evaluations yields the final result. Scebba et al. [ 14] implemented an automated approach to wound detection and segmentation using specialized deep neural networks consisting of three steps: a wound detection neural network that detects the wound(s) on the raw wound image; a processing module that performs cropping, zero padding and image resizing to exclude uninformative background pixels; and the final segmentation model that also includes a deep neural network model. The results showed that the fusion of automatic wound detection and segmentation improved segmentation performance and enabled the segmentation model to generalize well to images of wounds that are not in the distribution. Marijanović et al. [ 18] proposed a method for wound detection with pixel-level instance segmentation, which consists of an ensemble of three simple feedforward networks, each comprising only five fully connected layers. For each of the feedforward neural network classifiers, input data were created using a conventional fixed-size overlapping sliding window method, with the sliding window sizes varying for each classifier. Post-processing involving thresholding, morphological closure, and morphological opening was performed on each of the predicted outcomes or probability maps of the respective neural network classifiers. The logical operation AND was then used to merge these binary post-processed images obtained as the output predictions of the three neural networks. The ensemble classifier suggested by the authors outperformed Wang et al. ’s technique [11] in terms of detection and processing time and proved to be relatively robust to image rotations. Training and testing were conducted using data from the MICCAI 2021 FUSeg Challenge [20]. The segmentation of wounds from 3D surfaces such as meshes is far less popular in the literature since it often requires specialized hardware for acquisition. However, even when regular cameras are used, extension into the third dimension is often cumbersome and requires specific knowledge to analyze and use such data. In medical and other research, lasers are frequently employed for 3D reconstruction, where a laser line projection sensor calibrated with an RGB camera can produce precise and colored 3D reconstructions. One of the earliest studies to implement such a method was Derma [21], where the Minolta VI910 scanner was employed by the authors. Laser and RGB camera technology was also utilized in related studies [22,23]. These systems have been shown to be extremely accurate, but they are also difficult to operate. Furthermore, these investigations had the limitation that the full wound must be seen in one frame. In order to improve image-based techniques and provide more accurate measurement, some wound assessment systems use 3D reconstruction. As a result, multiple view geometry algorithms using conventional cameras are frequently employed. In [24], the authors create a 3D mesh model using two wound images collected at various angles. The final 3D mesh has a low resolution as a result of the technology and techniques used. Some research tries to combine 2D and 3D information to enhance the operation and increase the measurement precision. To find the center of the wound, Filko et al. [ 4] include a 2D detection phase in the 3D reconstruction procedure inspired by Kinectfusion. The kNN method and color histograms are used to implement this. Additionally, they segment the wound from the reconstructed 3D model by first dividing the reconstructed 3D surface into surfels. Then, utilizing geometry and color information to create relationships between neighboring surfels, a region-growing process groups these surfels into larger smooth surfaces. Finally, using spline interpolation, the wound boundary is determined and the wound is then isolated as a distinct 3D model and its perimeter, area, and volume are calculated. Niri et al. [ 25] employed U-Net to roughly segment the wound on 2D images and used structure from motion algorithm to reconstruct the 3D wound surface from a sequence of images. They then used reprojections of the 3D model to enhance the wound segmentation on the 2D input images as well as the 3D model. They managed to measure the wound area, but since the ground truth employed is based on the models acquired by the same technique, the accuracy of the actual area measurements is not fully validated. In a later study, Filko et al. [ 5] developed a robot-driven system for the acquisition and 3D reconstruction of chronic wounds, which also utilized 2D segmentation based on neural networks as its wound detection subsystem. The research presented in this paper is the continuation of that research. The majority of research is focused on segmentation on 2D images, especially employing deep learning that has excellent properties proven over the myriad other applications. In this research, deep learning is also employed in order to generate an initial, rough wound segmentation, which, because of the errors in camera calibration and imprecision of the 2D segmentation, requires further adjustment when projected onto the 3D model. The 3D side of the segmentation is based on the application of a 3D active contour model that further refines the original contour by utilizing surface curvature to find more optimal wound borders on the 3D mesh model of the wound and its local surroundings. This novel combination of deep learning 2D segmentation and 3D refinement using an active contour model is the main contribution of this paper. ## 3. Hardware and Software Configuration The hardware configuration (Figure 2) of the acquisition system consists mainly of a Kinova Gen3 7-DoF robot arm and a Photoneo PhoXi M 3D scanner. The Kinova Gen3 robot arm has an RGB-D camera based on Intel RealSense technology embedded in its tool link in the form of the Kinova vision module. The Photoneo PhoXi 3D scanner is connected to the Kinova Gen3 tool link via a custom 3D printed frame. The Kinova RGB camera was manually calibrated to the PhoXi 3D scanner, while the PhoXi 3D scanner was also manually calibrated to the Kinova Gen3 tool link, which enabled transformations between PhoXi and robot base reference frames. All experiments in this paper were performed on two Vata Inc. medical models (Figure 3):Seymour II wound care model, which includes stage 1, stage 2, stage 3, and deep stage 4 pressure injuries, as well as a dehisced wound. Vinnie venous insufficiency leg model, which includes various injuries as well as venous ulcers and foot ulcers. ## 4. Wound Segmentation Wound segmentation is an important step in obtaining physical measurements of the wound such as area, perimeter, and volume. The estimation of these parameters requires the reconstruction of a 3D model of the actual wound. As mentioned earlier, the segmentation algorithm is built upon a robot-driven wound detection and 3D reconstruction system [5]. Therefore, for the sake of completeness, the description of those prior phases will be included in the next subsection. ## 4.1. Wound Detection and 3D Reconstruction The wound 3D reconstruction system is divided into six main stages (Figure 4):Wound detection;Moving the robot to chosen pose and recording;Point cloud alignment;Point cloud analysis;Hypothesis creation and evaluation;Recording pose estimation. The first step in the system operation is to detect the wound, which must be located in front of the robot. The purpose of detection is to focus the reconstruction process to a relatively small volume instead of reconstructing the entire scene in front of the robot. During the wound detection process, the system acquires an RGB-D pair of images using the Kinova vision module. The RGB image is used for 2D wound detection by a neural network classifier, while the depth image is used for establishing the position of the wound in 3D space. The second stage is to control the robot to the desired recording pose. During this stage, the PhoXi scanner acquires depth images and point clouds, while the RGB image acquired by the Kinova vision module is registered to the PhoXi depth image. In the case that the considered point cloud is the first in a series for the wound reconstruction process, an additional wound detection is executed in order to create a volume-of-interest bounding box, which is then used as the region to concentrate the efforts of the reconstruction process and the segmentation process in the later stages. The alignment of the acquired point clouds with the ones from previous recording cycles is the objective of the third stage. In the case of the initial recording, the alignment is skipped; if it is the second recording, a pairwise alignment between the previous and current point cloud is performed. In the case of the third and every subsequent recording, a full pose graph optimization is performed using all recorded point clouds up until that point in time. The fourth stage focuses on analyzing the reconstructed surface by determining the surface deficiencies such as surface density and surface discontinuities by the classification of points included in the volume-of-interest bounding box in four classes: core, outlier, frontier, and edge. In the fifth stage, a list of hypotheses is generated that are used as the next best view for the surface reconstruction process. A hypothesis list is, in part, populated by hypotheses generated using the surface point density data consisting of clustered poses generated from each frontier point. The other part of the hypothesis list is generated using discontinuity data consisting of structures called DPlanes, which are created by clustered edge points. The sixth and final stage checks whether the evaluated hypotheses in the list are accessible by the robot. If a hypothesis is accessible, it is then chosen as the next best view for acquisition. If it is not accessible, the system tries a number of adjusted views in the vicinity of the considered hypothesis and tests whether they are accessible instead. The wound reconstruction stops if no further hypothesis is created or if none of the hypotheses or their adjacent views are accessible. The final reconstructed point cloud is created by voxel filtering of the complete point cloud created by the alignment of the acquired point clouds. From this final point cloud, the points enveloped by the bounding box volume-of-interest are cropped and sent to the next stage of the wound analysis process, which is the segmentation stage. A complete description of the wound reconstruction system can be found in [5]. ## 4.2. Wound Segmentation Algorithm The input for the wound segmentation algorithm consists of a final 3D reconstructed wound model in the form of a 3D point cloud, RGB-D pairs of images, and final (optimized) poses of the recordings used to create the 3D model. The wound segmentation algorithm includes five stages: Two-dimensional per-pixel wound segmentation of RGB images made by Kinova robot vision system using MobileNetV2 classifier. Registering binary masks created by the previous stage to the depth image created by PhoXi 3D scanner. Optimized labeling of wound 3D model points using registered binary masks. Mesh subdivision to improve mesh density. Active contour model to refine wound segmentation on a 3D model. ## 4.2.1. Per-Pixel 2D Wound Segmentation The 2D wound segmentation procedure used in this paper is based almost entirely on the method proposed by Wang et al. [ 11], with two exceptions. First, our own database of images was used in model training and, secondly, an additional postprocessing procedure, utilizing GrabCut image segmentation [26], was included in the final stages in order to improve the obtained results. The output of the classifier is a binary mask marking the wound area(s). For the purposes of our research, a database of 145 images of two wound models (the Seymour II Wound Care Model and the Vinnie Venous Insufficiency Leg Model by VATA Inc.) was created. Thus, the classifier model obtained in this work is only suitable for images of synthetic wounds. The original images, of dimension 1280 × 780, were taken under uncontrolled illumination conditions, with various backgrounds. Sample images of the dataset are shown in Figure 3. The images were manually annotated per pixel into wound and non-wound. This dataset was further augmented (image flipping and rotation by 180°) and then divided into a training set with 504 images and a test set with 76 images. In order to implement the method proposed by Wang et al. [ 11], the images were resized, i.e., downscaled to the dimensions of 244 × 244. After segmenting using the MobileNetV2 classifier, the segmented image was resized to its original size (upscaled). Since the MobileNetV2 classifier is a per-pixel classifier, the wound segment on the resized or upscaled segmented image is blocky. In order to refine the results, the GrabCut image segmentation method [26] was used to further improve the segmented image whereby the ROIs obtained as outputs of the MobileNetV2 classifier serve as the initial input to the GrabCut segmentation procedure. This is shown with the aid of the images shown in Figure 5 and Figure 6. Figure 5 displays one of the test images (Figure 5a) with a section enlarged (Figure 5b). This enlarged section is further displayed in Figure 6 for different stages of the segmentation procedure. Figure 6a shows the binary image obtained as the output of the trained MobileNetV2 classifier after resizing from the dimension 244 × 244 to the original image dimension (1280 × 780). By superimposing these pixels onto the original image, the wound pixels on the original image are marked (Figure 6b). It can be noticed that the edges of the wound area are blocky or pixelated. By using the original image as well as the corresponding ROIs marked with bounding boxes in Figure 6c as inputs to the GrabCut image segmentation procedure, the obtained wound areas marked in Figure 3d are visibly improved compared to Figure 6b. Comparing the wound areas in Figure 6b,d, it can be noticed that after the additional postprocessing stage, i.e., GrabCut segmentation, the wound areas and the boundaries of the wounds are better defined. ## 4.2.2. Registering Binary Masks Binary images or masks created in the previous stage of 2D segmentation need to be registered with the PhoXi depth images in order to be able to apply them to the reconstructed 3D wound model. Prior to registering the masks, they are first dilated by a 30-pixel dilation filter in order to ensure that the mask covers the whole wound in each of the recordings used. This is carried out due to the imperfect camera calibration procedure which has sub-pixel to sometimes even pixel reprojection error at certain distances, as well as the imperfect segmentation procedure in the 2D segmentation stage. This over-segmentation is optimized by the active contour model in the later stage in order to ensure a tighter fit of the detected wound edge on the actual 3D wound model. In Figure 7, an example of the registration process can be seen, where Figure 7a shows the input RGB image made by the Kinova vision module. Figure 7b shows the output binary mask, while Figure 7c shows the dilated mask. The registered RGB and mask images are showed in Figure 7d and 7e, respectively. ## 4.2.3. Optimized Labeling of 3D Points The final wound point cloud output by the acquisition system [5] is processed by voxel filtering, which averages the point positions, colors, and normals for points contained in a given voxel. The resulting point position on the 3D model is not directly referenced in any of the input point cloud recordings, so each point in the point cloud used as input to the segmentation procedure must be reprojected onto each of the input registered binary masks, and then the reprojection that is best suited for the individual point is selected. Furthermore, the optimized labeling and later stages of the segmentation algorithm are performed only on the local wound area point cloud designated by the bounding box volume-of-interest generated during the detection phase of the reconstruction process [5], thereby removing the remainder of the reconstructed scene that is not needed for the analysis of a particular wound. The algorithm for optimized labeling includes the following steps:Un-project each point in the point cloud on each of the input registered masks, retrieve its mask value and the measured depth value (dm) from the associated depth image. Also keep the observed depth value the reprojected point would have on the input registered mask (do).Calculate the score for each combination of 3D points and input registered masks in the following way: [1]score=1\|\|P−Cp\|\|·1degacos−N·CRZT where P is the point coordinates, N is the normal vector at point P, Cp is the camera position where the image was taken, and CRZ is the Z column of the camera pose rotational matrix. Choose the optimal source of the binary mask label that has the highest score and minimal difference between the measured depth values (dm) of the original recorded depth image and the calculated, observed depth (do) value for each of the point cloud’s points. The difference in the depth values (ddiff), as seen in Figure 8, is used to detect occlusion when a 3D point would choose a particular registered mask due to a better conditioned relation between the surface normal and camera recording orientation; however, the measured depth (dm) at that reprojected pixel shows a different point closer to the camera than the observed depth (do), which is calculated by the reprojection of the 3D point. Figure 8 distinguishes two camera positions designated as 1 and 2, where position 1 has a better conditioned angle between the recording orientation and surface normal, but has a disadvantaged difference between the observable and measured depth. Position 2 is the opposite of position 1 regarding favorability, but since it does not have penalties regarding depth difference, it will be chosen as the optimal position even though its recording is not in a very good position to record that particular point on the surface. Figure 9 shows an example of optimized labeling where four recordings were used to reconstruct a wound. The figure shows a reconstructed 3D model, registered RGB, and mask images, as well as local point cloud wound area textured with color and an optimized mask projection. After the point cloud has been labeled by optimal reprojection, an initial mesh is created using the greedy point triangulation algorithm (GPT) [27] and the initial wound contour is designated by finding mesh vertices that have at least one neighbor labeled as non-wound. That contour is further subsampled by using only half of the points to create an initial contour for the active contour model used in the next phase. Figure 10 shows an example of the initial wound contour on a meshed local wound area. ## 4.2.4. Mesh Subdivision Mesh subdivision, in general, is an algorithm that takes a course mesh as input and produces a more dense mesh by subdividing mesh cells into additional cells. This subdivision typically produces an approximated version of the original surface geometry. There are several popular algorithms such as Loop [28], Butterfly [29], or Midpoint [30] for subdividing triangle meshes. Loop and Butterfly both produce approximate surfaces by interpolating curves, while Midpoint preserves the original mesh geometry. To avoid having to make additional assumptions about the scanned wound surface, the Midpoint algorithm is used in this research. The Midpoint algorithm, in each iteration, basically cuts every mesh edge in half and generates four new triangles out of each original triangle. Figure 11 shows an original mesh and the mesh subdivided by the Midpoint algorithm. Refining the reconstructed wound mesh by increasing the density of triangles and vertices greatly improves the performance of the active contour model (ACM) algorithm, explained in the next subsection, by giving each contour node more freedom to choose a more suitable point that minimizes the energy term [2]. The original wound mesh made by the GPT algorithm can be too restrictive for the ACM algorithm even though the original surface is sampled at the millimeter scale, especially in the case of wounds of small size. Figure 12 shows the change in ACM performance with the same configuration when using original wound mesh or subdivided mesh. In this research, two iterations of the Midpoint algorithm were applied for the input wound meshes. ## 4.2.5. 3D Active Contour Model The active contour model (ACM) [31] is an algorithm that enables users to find the contours of arbitrary objects in primarily 2D images. ACM is basically a deformable spline influenced by some predefined forces. These forces typically include the attraction force between the nodes of the contour, which causes the contour to contract (or repulse in the case of an expanding contour), and a smoothing force, which counteracts the deformation of the contour. Besides these forces, in order for the ACM to work, the nodes of the contour must be attracted toward a boundary that the user is trying to find—in 2D images, this is typically some kind of gradient, for example, finding the edges in an image with the Sobel filter and then blurring it with the Gaussian filter to have a wider attraction range. The basic energy functions for the 3D adaptation of the ACM are similar to the generally known 2D case [31]: [2]Etotal=Emesh+Econtour [3]Emesh=−∑$i = 0$n−iMi, Mp=maxeigCp [4]Econtour=αEelastic+βEsmooth [5]Eelastic=∑$i = 0$n−i∑$j = 0$k−1xki+1−xk2+yki+1−yk2+zki+1−zk2 [6]Esmooth=∑$i = 0$n−1xi+1−2xi+xi−12+yi+1−2yi+yi−12+zi+1−2zi+zi−12 where Etotal is the cumulative contour energy calculated over all contour nodes that needs to be minimized. It comprises mesh energy Emesh and contour energy Econtour. Mesh energy, in this case, is the curvature calculated using principle component analysis (PCA) over a list of normals for points in the vicinity of a particular mesh vertex. Basically, it is the largest eigenvalue of the covariance matrix Cp calculated for the list of normals for a particular point p. Choosing the correct neighborhood size radius for calculating the PCA is crucial for the attraction force and reach of the ACM, as can be seen in Figure 13b,c, where two different neighborhood radii were used for the calculation. In this research, a neighborhood radius of 5 mm was used for calculating the PCA. The contour energy is further composed of the elastic energy Eelastic, which regulates contraction (or expansion), and smoothing energy Esmooth that regulates the deformability of the contour. The symbols α and β control the influence of elastic and smoothing energies in the overall energy term. In this research, α and β were used with the value of 1. The elastic energy is determined by calculating the Euclidean distance between the neighboring nodes of the contour. Since we have a mesh in the 3D case, the distance is composed of the Euclidean distances of all neighboring vertices along the shortest path between contour nodes. Therefore, the elastic energy is basically the geodesic distance along the surface of the triangle mesh between two nodes of the contour. The smoothing energy is calculated as the 3D gradient between the nodes of the contour. As established earlier, the 3D data of the local wound region that enters this stage of the algorithm is a 3D mesh. In order to better adapt the ACM model to the 3D data, the mesh is used to create a weighted graph. The graph comprises nodes as mesh vertices, the graph edges are triangle edges, and the weights are Euclidean distances between vertices. The 3D ACM algorithm works iteratively in five steps:Determine the current neighborhood for each contour node on the graph. Calculate the new position for each node in a greedy manner. Estimate a spline based on the new node positions. Uniformly sample the spline with the same number of nodes as the initial contour. For each spline sample, find the nearest node on the graph (mesh). After the initial contour generation in the previous stage of the segmentation algorithm, each list of contour nodes contains the same number of nodes in the following iterations. At the start of each iteration, each contour node generates a list of neighbors that are located a maximum number of graph nodes from the contour node being considered. For this research a two-node neighborhood was found to be the optimal solution. Figure 13d shows a contour, nodes, and neighbors for each of the displayed contour nodes in a two-node-wide range. The new position for each node in each iteration is considered in a greedy manner, i.e., independently of the new positions for neighboring contour nodes. The new position for each node is selected from a list of neighbors that minimizes the energy term [2]. Following the designation of the new graph position for every node, a spline is estimated through these positions, which is then sampled in the same number of points as the original list of contour nodes. Since these samples may or may not be located on the wound mesh, a nearest mesh vertex is located by using kd-tree. Figure 13e shows the initial contour as well as a 10-iteration ACM optimized one for the synthetic example of the hole (Figure 13a), where the ACM successfully found the requested hole boundary. In this research, 10 iterations of the ACM were utilized to optimize the initial contour in each of the experimental wounds. A more realistic example of the ACM application can be seen in Figure 14. Figure 14a–c shows a very successful application of the ACM where the first image shows the masked mesh and initial contour and the second and third images show the initial and final contour with a curvature texture and RGB texture, respectively. A successful run with some inconsistencies can be seen in Figure 14d–f, where the ACM managed, for the most part, to find the wound border with some small areas in the left and top still being over-segmented. The reason for the error on top of the wound was actually the close proximity of the second wound, not object of this analysis, on the same medical model that has more pronounced edges which then “stole” the contour from the observed wound. An unsuccessful run is shown in Figure 14g–i, where it can be seen that the ACM under-segmented the wound, with the final contour slipping to the bottom border of the wound surface instead of remaining on the top border. The error was caused by a relatively shallow wound with strong top and bottom borders. The ACM could not numerically distinguish between the top and bottom border since the bottom was very close due to the shallowness; it therefore “slipped” to the bottom, causing the wound to be under-segmented. ## 5. Results Generating the final wound boundary using the ACM algorithm is the starting point of calculating the physical properties of the wound, as the boundary directly enables the calculation of the wound perimeter and the area in the case of a shallow wound. For deep wounds, the area is considered to be the skin missing on the top of the wound, therefore a virtual skin top needs to be generated. Similar to our previous research [4], the top of the wound, as well as other holes in the 3D model, are closed using constrained 2D Delaunay triangulation implemented in the VTK library [32]. Even though this Delaunay implementation is for 2D point sets, 3D data can be used by projecting all of the points on a plane chosen as a most likelihood plane by calculating the PCA and choosing the eigenvector corresponding to the largest eigenvalue. Creating a virtual skin top facilitates wound area measurement while creating covers for all holes; it enables the creation of the watertight 3D model and calculating the volume. Figure 15 shows an example of the final wound surface cut from the input mesh by the contour generated from the ACM, along with the generated surfaces used for hole filling. ## 5.1. Case Study The case studies considered here are wounds from two realistic and lifelike medical models by Vata Inc. as described in Section 3. The Seymour II wound care model also has ground truth (GT) measurements available as mentioned in [4], and the GT measurements can be seen in Table 1. In this section, we will consider various wound geometries, namely, Stage 3 and 4 pressure ulcers as well as dehisced surgical wound from the Seymour II wound care model. From the Vinnie venous insufficiency leg model, we will consider two venous ulcers as well as a neuropathic ulcer. ## 5.1.1. Stage 3 Pressure Ulcer This is a stage 3 pressure ulcer with moderate depth and tunneling on two separate sides. While the used robot-driven 3D wound reconstruction system [5] could be very precise, it was struggling to find a reachable pose to scan the tunneling parts of the wound, therefore those parts of the wound remained largely unscanned in both pressure ulcers considered here. The wound reconstruction can be seen in Figure 16a along with the segmentation performance of Figure 16b–d. The wound was reconstructed from four recordings made from separated viewpoints. As can be seen in Figure 16b, the optimized labeling of the reconstructed mesh was quite successful, with very little unwanted labeling in the surrounding mesh around the wound, which resulted in a tight initial contour prior to ACM. The ACM further optimized the contour, as can be seen from Figure 16c as a green contour. This figure also shows the curvature intensities on the surface of the model. The segmented and cut wound mesh can be seen in Figure 16d. All of the covers for this particular wound can be seen in Figure 15, while the covers for other wounds that have them are not shown because they are quite similar. The wound perimeter was measured to be 171.09 mm, the area was 2302.0 mm2, and the volume was 22,532.09 mm3. When comparing the results to GT, they produce a percentage error of $2.62\%$ for perimeter, $2.86\%$ for area, and $4.59\%$ for volume. ## 5.1.2. 5½ Inch Long Dehisced Surgical Wound This wound is a 5 ½ inch long dehisced surgical wound with considerable depth and high-angled sides. Due to its high-angled sides (compared to the camera projection plane), it makes reconstruction of this wound a challenge since the projected laser pattern by the 3D scanner does not reflect enough toward the scanner in order to be visible from many view angles reachable by the robot recording system. Therefore, even though the wound is rather simple and could be reconstructed if placed in an unrealistic position for the patient, since it simulates a patient wound on a model of a part of the human body, it could only be partially reconstructed with one side fully scanned, taking into consideration all of the imposed limitations. The reconstructed 3D model can be seen in Figure 17a: the reconstruction was made from four recordings. Figure 17b shows the optimized mask of the detected wound and initial contour, while Figure 17c shows the initial and ACM contour on the surface textured with curvature. Figure 17d shows the segmented and cut wound. The wound perimeter was measured to be 275.22 mm, the area 2549.63 mm2, and the volume 29,764.54 mm3. The results, when compared to GT, give a percentage error of $0.89\%$ for the perimeter, $6.23\%$ for the area, and $5.95\%$ for the volume. ## 5.1.3. Stage 4 Pressure Ulcer This wound is the second pressure ulcer and the largest and most complex wound on the Seymour II wound care model since it has a very large area, great depth, and tunneling in two different directions. Similarly, as in the previously described pressure ulcer, the tunneling parts of this wound were not able to be reconstructed. Figure 18a shows the reconstructed surface, while Figure 18b shows the optimized mask labeling made from seven recordings from which the wound was originally reconstructed. Figure 18c shows the initial and ACM contour on a model textured with curvature values, while Figure 18d shows the segmented and cut wound. As can be seen in the figures, the ACM failed in 10 iterations to tightly envelop the wound from the bottom and left parts, resulting in a higher area error percentage. Increasing the number of iterations to more than 10 might have helped a little, but reducing the value of β would probably have helped more as it would have made the contour more deformable. The wound perimeter was measured to be 351.53 mm, the area 7689.11 mm2, and the volume 109,839.24 mm3. The results, when compared to GT, give a percentage error of $4.96\%$ for the perimeter, $8.02\%$ for the area, and $8.94\%$ for the volume. ## 5.1.4. Neuropathic Ulcer This wound is a neuropathic ulcer of comparatively smaller size compared with the previously considered wounds, but because of its depth, four recordings were needed to reconstruct it properly. Figure 19a shows the 3D reconstruction model of the local wound, while Figure 19b shows the optimized mask projection. It can be seen that the mask encompasses a large area around the actual wound. Figure 19c shows that despite this larger masked area, the ACM manages to precisely envelop the actual wound. The final segmented and cut wound is shown in Figure 19d. The wound perimeter was measured as 44.07 mm, the area as 150.97 mm2, and the volume as 414.08 mm3. ## 5.1.5. Larger Venous Ulcer This wound is a venous ulcer of substantial size. The wound is rather flat, therefore no volume is measured. Due to some protrusions on the surface, two recordings were needed to reconstruct the surface shown on Figure 20a. Figure 20b shows the optimized mask projection that envelops a much larger area than the actual wound, but the ACM manages to converge on the actual wound outline despite the dynamic nature of that part of the surface, as can be seen in Figure 20c. Figure 20d shows the segmented and cut wound. The wound perimeter was measured as 130.18 mm, while the area was 1324.47 mm2. ## 5.1.6. Smaller Venous Ulcer This is also a venous ulcer of relatively small proportions and, similar to the previously discussed venous ulcer, this one is also very flat and therefore no volume is measured. Only one recording was needed to generate the reconstruction shown in Figure 21a. The initial contouring made by the mask projection is shown in Figure 21b, and as can be seen, the masked area does not correctly overlap the wound area due to inaccuracy in the 2D wound segmentation and errors in camera calibration. Figure 21c shows that the ACM has somewhat correctly contoured the wound, with the only big error being that the top of the contour converged on another wound (a lipodermatosclerosis wound) that is in close proximity to this venous ulcer model. The other wound has a much bigger ridge, which results in a much larger curvature that is therefore “stealing” the contour. If this wound was not located that closely, the ACM would converge on the wound under consideration. The problem might also be fixed by using a larger α value of the ACM energy term, but in this research, we the used same configuration for all experiments. The final segmented and cut wound is shown in Figure 21d. The wound perimeter was measured as 102.44 mm, while the area was 698.56 mm2. ## 6. Conclusions Automated and precise wound measurements will improve the quality of the tools available to physicians to track the healing of individual patients and wounds. This would also facilitate better suited prescription and application of therapies, which would increase the living standards of patients as well as increase the healing rate of wounds, resulting in a reduction of costs in the medical system. The segmentation system presented in this research is built upon on an automated, robot-driven acquisition system that outputs precise 3D reconstructions of chronic wounds. The acquisition system is fully automated and does not require any user input other than turning the robot in the general direction of the patient. The research presented here continues this philosophy of automation such that it does not require any user input in order for it to output accurate wound segmentation and geometric measurements. The data requested by the segmentation algorithm is the reconstructed 3D point cloud model of the wound as well as recordings and camera poses used to create the reconstruction. The recordings are used to create binary masks using the MobileNetV2 classifier and GrabCut, which label a general area of the wound on 2D images. These binary masks are then projected onto the 3D point cloud wound model, and then each point in the point cloud selects which projection to use based on the computed score, as well as the occlusion detection. Such a masked point cloud is used to generate an initial contour of the wound, which is then further refined by ACM on the meshed 3D surface of the reconstructed wound. The wound is then segmented, cut out, and the geometric measures of perimeter, area, and volume are calculated. Comparing the obtained measurement results with the authors’ previous work in [4], the average error rate was $2.82\%$ for circumference, $5.72\%$ for area, and $6.49\%$ for volume measurement, compared to $4.39\%$ for circumference, $6.86\%$ for area, and $23.82\%$ for volume. The results presented clearly show that the segmentation and measurements are accurate, but further improvements must be made, especially regarding the reduction of errors caused by the calibration of cameras as well as 2D segmentation. Moreover, 3D ACM implementation could also be further improved by increasing the robustness to curvature noise as well as increased flexibility to better outline the arbitrary shapes that wounds can have. ## References 1. Gethin G., Cowman S.. Wound measurement comparing the use of acetate tracings and VisitrakTM digital planimetry. J. Clin. Nurs. (2006.0) 15 422-427. 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--- title: The Effects of Glutathione on Clinically Essential Fertility Parameters in a Bleomycin Etoposide Cisplatin Chemotherapy Model authors: - Hale Bayram - Yaprak Donmez Cakil - Mustafa Erinc Sitar - Gamze Demirel - Belgin Selam - Mehmet Cincik journal: Life year: 2023 pmcid: PMC10058932 doi: 10.3390/life13030815 license: CC BY 4.0 --- # The Effects of Glutathione on Clinically Essential Fertility Parameters in a Bleomycin Etoposide Cisplatin Chemotherapy Model ## Abstract Chemotherapeutic agents used in the treatment of testicular cancer cause damage to healthy tissues, including the testis. We investigated the effects of glutathione on sperm DNA integrity and testicular histomorphology in bleomycin etoposide cisplatin (BEP) treated rats. Twelve-week-old male rats of reproductive age ($$n = 24$$) were randomly divided into three groups, the (i) control group, (ii) BEP group, and (iii) BEP+ glutathione group. Weight gain increase and testes indices of the control group were found to be higher than that of the BEP group and BEP+ glutathione group. While the BEP treatment increased sperm DNA fragmentation and morphological abnormalities when compared to the control group, GSH treatment resulted in a marked decrease for both parameters. Moreover, BEP treatment significantly decreased serum testosterone levels and sperm counts in comparison to the control group, yet this reduction was recovered in the BEP+ glutathione treated group. Similarly, seminiferous tubule epithelial thicknesses and Johnsen scores in testicles were higher in the control and BEP+ glutathione groups than in the BEP-treated group. In conclusion, exogenous glutathione might prevent the deterioration of male reproductive functions by alleviating the detrimental effects of BEP treatment on sperm quality and testicular histomorphology. ## 1. Introduction Testicular cancer (TC) is a malignancy frequently seen in men of reproductive age, with approximately 75,000 cases and over 9000 deaths per year worldwide. Though, in general, mortality rates have decreased or become stable due to the improvements in treatment, the incidence of TC has significantly increased in recent years in White males with the highest incidence in the Scandinavian countries, Germany, Switzerland, and New Zealand [1]. Generally, a favorable prognosis with a >$90\%$ cure rate and >$95\%$ five-year survival rate is achieved with effective management [2,3,4]. Cisplatin-based chemotherapy is the routine treatment of choice for patients who are at (i) early stages of nonseminomatous germ cell TC with risk factors, (ii) stage II seminoma, (iii) recurrence and (iv) advanced disease cases [5]. Three to four cycles of bleomycin, etoposide, and cisplatin (BEP) have become the treatment of choice in patients with metastatic germ cell tumors [6]. However, fertility becomes a major concern, as most patients with TC are of reproductive age and the BEP regimen is gonadotoxic [4]. The deleterious effects of BEP on semen parameters and sperm DNA persist even 24 months after the end of the treatment [7,8]. Specifically, cisplatin is associated with a high risk for prolonged or permanent infertility, with 20 to $47\%$ of low versus high dose groups suffering from azoospermia after 5 years [9,10]. Moreover, $89\%$ of patients were recorded to have elevated follicle-stimulating hormone (FSH) levels for 12 months after cisplatin-based chemotherapy including BEP, which was evident for more than 8 years in $64.3\%$ of men, indicating persisting damage to Sertoli cell function [11]. Furthermore, BEP-treated patients with mild Leydig cell dysfunction during the initial standard 5-year follow-up period presented a significant long-term decline in age-adjusted testosterone levels, and hence a risk of testicular failure [12]. In accordance with the aforementioned perturbations, the paternity rate in long-term survivors of TC was found as $71\%$, and 6.6 years was the average duration from diagnosis until the birth of the first child [13]. A recent review, providing comprehensive information on sperm DNA damage in TC patients with clinical implications, reported a more common use of assisted reproductive technologies (ART), especially intracytoplasmic sperm injection (ICSI) by TC survivors, due to poor sperm quality when compared to the general population, with only $50\%$ of couples achieving pregnancy. Maintenance of sperm chromatin integrity becomes specifically important in this issue due to the associated risk of transmitting defective genetic material to the embryo [14]. Sperm DNA fragmentation is the disruption of sperm chromatin integrity due to various intrinsic or extrinsic factors. Together with the abnormal chromatin condensation and dysregulation of normal apoptotic mechanisms, oxidative stress with the generation of reactive oxygen species (ROS) is among the primary causes of alterations in DNA integrity [15]. From a clinical perspective, the high level of sperm DNA damage is associated with a series of adverse reproductive outcomes [16]. Antioxidants possess the ability to reduce the deleterious effects of oxidative stress and protect the body against chemically induced toxicities [17,18]. Oral antioxidant treatments hold promise as adjuvants in chemotherapy [15,16,19]. Antioxidants neutralize ROS, which cause damage to cellular structures including DNA [20]. Several antioxidants such as aescin, coenzyme Q10, glutathione (GSH), L-carnitine, omega-3, selenium, zinc (Zn), and folate were shown to have positive effects on male fertility by mainly maintaining normal sperm motility and/or morphology [21,22]. A Cochrane review compared randomized controlled trials on the effectiveness of oral antioxidant supplementation in subfertile males, and demonstrated improved clinical pregnancy and live birth rates [23]. The 2019 review [24] included four studies evaluating sperm DNA fragmentation, and suggested a higher likelihood of achieving a pregnancy with decreased sperm DNA fragmentation. There is a recent update on the Cochrane review reporting similar reproductive outcomes in subfertile men, though more data is required to clarify the exact effects of the antioxidants [25]. Glutathione (GSH) is a tripeptide composed of glutamic acid, glycine, and cysteine. The latter provides the sulfhydryl group (–SH), which is involved in reduction and conjugation reactions, and makes GSH a major antioxidant synthesized in the cells [26]. Among its diverse functions, GSH is also involved in spermatogenesis and sperm maturation [27], and intracellular sperm GSH system components were reported to be linked to altered sperm morphology in infertile men [28]. Moreover, improvement of sperm quality was evident with exogenous GSH supplementation in infertile men with unilateral varicocele or genital tract inflammation [29], and in diabetic mice [30]. This study was designed to investigate for the first time the effects of GSH on BEP-caused reproductive toxicity by analyzing (i) sperm concentration and morphology; (ii) sperm DNA fragmentation; (iii) serum testosterone levels, and (iv) testicular histomorphology in experimental rat models that mimic the three cycle BEP treatment in humans. ## 2.1. Experimental Animals Twenty-four Sprague-Dawley male rats, 12 weeks old, mature at reproductive age and produced in Maltepe University Experimental Animal Center, were used in the current study. Each cage contained a maximum of four rats, which were maintained at room temperature with a humidity of 50–$60\%$ and automatic 12-h light/dark cycle periods. All animals had free, and easy access to water and pellet food. The experimental protocol was applied in accordance with ethical approval given by Maltepe University Experimental Animal Local Ethics Committee (protocol number 2021.09.01). ## 2.2. BEP and GSH Treatment Protocols Rats were randomly divided into three groups as i-control, ii-BEP and iii-BEP + GSH groups. The BEP protocol was applied for a total of 9 weeks, and the medication doses were determined in a preliminary study based on the study performed by Kilarkaje et al. [ 31]. However, $100\%$ mortality was observed, and the dose of BEP treatment was reduced following subsequent experiments with lower doses. According to the results of the preliminary study, the treatment protocol included 0.17 mg/kg cisplatin (CAS: 15663-27-1; Koçakfarma, Istanbul, Turkey), 0.83 mg/kg etoposide (CAS: 33419-42-0; Koçakfarma), and 0.083 mg/kg bleomycin (CAS: 11056-06-7; Koçakfarma). The rats in the BEP group were treated with a 21-day 3-cycle protocol. Cisplatin and etoposide were administered on days 1–5, while bleomycin was given on days 2, 9 and 16 of each cycle by ip injection with 30-min intervals. The control group was injected with $0.9\%$ NaCl, when bleomycin, etoposide, and cisplatin were applied to the BEP group. The BEP + GSH group was also administered with GSH (CAS: 70-18-8; Laboratorio Farmaceutico, Imperia, Italy) (200 mg/kg) twice a week by ip for 9 weeks in addition to the BEP treatment [32]. ## 2.3. Tissue Removal and Sperm Collection At the end of the experimental period, the rats were anesthetized by intraperitoneal administration of 100 mg/kg ketamine (Ketalar, CAS: 6740-88-1; Pfizer, Turkey) and 10 mg/kg xylazine (Rompun, CAS: 23076-35-9; Bayer, Turkey). All rats were sacrificed by taking intracardiac blood under general anesthesia, and their epididymis were removed and trimmed free of fat. Both testes and epididymis were rapidly excised and placed in a petri dish on ice. Their weights were recorded. Sperm was collected by mincing the epididymis in a global medium (LifeGlobal® Media, Ballerup, Denmark) and incubating at 37 °C for 15 min. ## 2.4. Serum Testosterone Level Measurement Intracardiac blood samples were obtained under full anesthesia and were placed in routine biochemistry tubes. Next, they were centrifuged at 1500× g for 15 min. In this way, serum was obtained and separated into aliquots. Testosterone levels were measured using chemiluminescence method with Siemens Immulite® (Erlangen, Germany) device following the protocol recommended by the manufacturer. ## 2.5. Semen Analysis Sperm samples were diluted 10× with phosphate buffered saline (PBS), and 10 μL of the suspension was placed on a Makler counting chamber. The number of sperm heads was counted using a phase-contrast microscope under magnification of 20×. The sperm count was recorded to calculate the concentration of spermatozoa (106/mL). The Spermac stain method (FertiPRO, Beernem, Belgium) was used for sperm morphology evaluation according to the manufacturer’s guidelines. Semen smears were prepared and air-dried at 25 °C for 15–20 min. Slides were fixed in Spermac fixative solution and washed in distilled water. Subsequently, they were kept in Spermac A for 60 s, in Spermac B for 45 s, and in Spermac C for 45 s. In between, each dye was washed off with distilled water. The stained slides were air-dried and evaluated with a light microscope (Zeiss®, Oberkochen, Germany) under a magnification of 40×. At least 200 sperm were counted repetitively and evaluated for head, and tail abnormalities according to the Rat Sperm Morphological Evaluation Guide [33]. ## 2.6. Sperm DNA Fragmentation Analysis Sperm DNA fragmentation analysis was performed by the TUNEL (terminal deoxynucleotidyl transferase dUTP nick end labeling) method using the Abcam TUNEL assay kit-FITC (CAS: 3326-32-7; ab66108; Cambridge, UK). First, the sperm were fixed in $1\%$ paraformaldehyde for 15 min at −20 °C. The fixed samples were centrifuged at 400× g for 7 min and the supernatants were removed. After washing twice in PBS, pellets were resuspended with 1 mL of ice-cold ethanol ($70\%$ v/v) until staining with the TUNEL assay kit according to the manufacturer’s instructions. The samples were analyzed for DNA fragmentation under a Zeiss LSM 700 confocal scanning microscope. Negative and positive samples of the kit were included as controls and at least 200 cells were counted for each sample. ## 2.7. Testicular Histomorphology Testicular tissues were fixed in $10\%$ formaldehyde, embedded in paraffin blocks, and cut into sections of 2–3 μm thickness. Hematoxylin-eosin (H&E; CAS: 517-28-2, 6359-04-2) staining was performed for general histopathological evaluation at 10× and 40× magnification under a Zeiss light microscope by Johnsen scoring, which gives scores from 1 to 10 based on the stage of spermatogenesis (score of 10 corresponding to a maximum spermatogenesis activity, and score of 1 corresponding to a complete absence of germ cells) [34]. ## 2.8. Statistical Analysis The IBM SPSS Statistics 26 (Statistical Package for the Social Sciences; New York, NY, USA) program was used for statistical analysis. Kolmogorow-Smirnov and Shapiro-Wilk tests were used to determine whether the data conformed to a normal distribution. One-way ANOVA test was employed for three-group comparisons of normally distributed quantitative variables and Tukey post-hoc test was used for pairwise comparisons between the groups. The Kruskal-Wallis test and Tamhane’s post-hoc test were used in the comparison of three groups of quantitative variables that did not show normal distribution. Differences were considered statistically significant when $p \leq 0.05.$ The bar graphs were created using GraphPad Prism V.8.01 (San Diego, CA, USA). ## 3.1. Effects of BEP and BEP + GSH on the Weights of the Rats and the Reproductive Organs The beginning and the final body weights (g), change in body weight (g), right and left testis weights (g), testes index (%), right and left epididymis weights (g), and epididymis index (%) of the control, BEP treated, and BEP + GSH treated rats, are shown in Table 1. BEP treatment significantly reduced the body weight gain ($$p \leq 0.027$$), right testis weight ($$p \leq 0.002$$), left testis weight ($$p \leq 0.027$$), testes index ($$p \leq 0.017$$), right epididymis weight ($$p \leq 0.002$$), and left epididymis weight ($$p \leq 0.010$$), and the epididymis index ($$p \leq 0.000$$) in comparison to the control group. Similar decreases were also obtained in BEP + GSH group when compared to the control group ($$p \leq 0.012$$ for body weight gain, $$p \leq 0.000$$ for right testis weight, $$p \leq 0.000$$ for left testis weight, $$p \leq 0.001$$ for testes index, $$p \leq 0.000$$ for right epididymis weight, $$p \leq 0.004$$ for left epididymis weight, and $$p \leq 0.000$$ for epididymis index). No significant differences were found in the respective parameters when the BEP and BEP + GSH groups were compared ($p \leq 0.05$). ## 3.2. Effects of BEP and BEP + GSH Treatments on Sperm Count and Morphology Sperm count analysis and sperm morphology evaluation were performed to assess the effects of BEP and BEP + GSH treatments on spermatogenesis (Figure 1). As shown in Figure 1A, BEP treatment caused a marked decrease in sperm concentration (106/mL) in comparison to the control group (112.5 ± 4.1 vs. 408.1 ± 29.6, $$p \leq 0.000$$), which was partially recovered in BEP + GSH group (271.2 ± 21.8, $$p \leq 0.001$$ in comparison to BEP group). Similarly, while the percentage of the sperm morphological abnormalities (Figure 1B) increased dramatically in BEP group (25.6 ± 2.27 vs. 12.5 ± 1.3 in the control group, $$p \leq 0.000$$), a drastic decrease was observed when GSH is administered (12.1 ± 0.7, $$p \leq 0.000$$ in comparison to BEP group). Morphological abnormalities were evaluated as abnormal neck/tail, abnormal head and multiple abnormalities, and the former had the highest incidence. Higher percentage of spermatozoa with abnormal head (Figure 1C) or abnormal neck/tail (Figure 1D) were obtained in the BEP group in comparison to the control group ($$p \leq 0.000$$ and $$p \leq 0.000$$, respectively). A significant decrease was observed in both parameters when GSH was administered ($$p \leq 0.000$$ and $$p \leq 0.000$$, respectively, when compared to the BEP group). The sperm counts with multiple abnormalities (Figure 1E) were similar among the study groups ($p \leq 0.05$). Figure 2 shows the images illustrating morphologically normal sperm and various morphological abnormalities. ## 3.3. Effects of BEP and BEP + GSH on Sperm DNA Fragmentation The TUNEL immunofluorescence assay was performed to investigate DNA integrity in control, BEP and BEP + GSH groups (Figure 3). Sperm heads with intact DNA were only stained with propidium iodide (PI) and appear red in the merged images in the right panel. On the other hand, TUNEL positive sperm heads were both stained with TUNEL stain and PI, and displayed yellow to orange fluorescence in the merged images (Figure 3A–C). Sperm DNA fragmentation was dramatically higher in the BEP group compared to the control and BEP + GSH groups (6.8 ± $1.6\%$ vs. 38.4 ± $4.8\%$ for control vs. BEP groups, $$p \leq 0.000$$; 38.4 ± $4.8\%$ vs. 16.9 ± $2.7\%$ for BEP vs. BEP + GSH groups, $$p \leq 0.000$$). There was no statistically significant difference between the control and the BEP + GSH groups (6.8 ± $1.6\%$ vs. 16.9 ± $2.7\%$, $$p \leq 0.105$$) (Figure 3D). ## 3.4. Effects of BEP and BEP + GSH on Serum Testosterone Levels Serum testosterone levels were measured in control, BEP and BEP + GSH groups to examine the effects of BEP and BEP + GSH treatments on Leydig cell function (Figure 4). The results showed a significant decrease in serum testosterone following BEP treatment when compared to the saline treated control group (598.1 ± 30.5 vs. 36.1 ± 4.8; $$p \leq 0.000$$). However, when GSH was also administered, significantly increased testosterone levels were obtained in the BEP + GSH group in comparison to the BEP group (304.6 ± 71.4 vs. 36.1 ± 4.8; $$p \leq 0.001$$). ## 3.5. Effects of BEP and BEP + GSH on Testis Histomorphology Testicular sections of 2–3 µm thickness were stained with H&E to examine if BEP treatment was associated with histopathological changes and, if any, these changes could be recovered by GSH treatment (Figure 5A,B). While spermatogenic cellular masses were observed in the lumen of seminiferous tubules in both control and BEP + GSH groups, the seminiferous tubule lumens were less occupied in the BEP group. To investigate the changes in a qualitative manner, the thickness of the seminiferous tubule epithelium (germinal epithelium height) (Figure 5C), and mean Johnsen testicular biopsy scores (Figure 5D) were calculated for each group. A marked decrease in the thickness of the seminiferous tubule epithelium was evident in BEP group in comparison to the control group (53.2 ± 1.3 vs. 112.2 ± 6.4, $$p \leq 0.000$$), which was reversed with administration of GSH in BEP + GSH group (53.2 ± 1.3 vs. 97.9 ± 3.3, $$p \leq 0.000$$). No significant difference was found when the control and BEP + GSH groups were compared ($p \leq 0.05$) (Figure 5C). A similar trend was observed when Johnsen scores were compared. The Johnsen score of the BEP group was lower than those of the control and BEP + GSH groups (10.00 ± 0.0 vs. 6.9 ± 0.1, $$p \leq 0.000$$, when control and BEP groups were compared; 6.9 ± 0.1 vs. 9.8 ± 0.2, $$p \leq 0.000$$, when BEP and BEP + GSH groups were compared). There was no significant difference between the control and the BEP + GSH groups ($p \leq 0.05$) (Figure 5D). ## 4. Discussion Testicular tumors have great sensitivity to cisplatin-based chemotherapy including BEP, mainly due to insufficient DNA damage repair and hypersensitive apoptotic response to DNA damage [35]. At the same time, oxidative stress induces a reduction in sperm motility and damage to sperm DNA and is considered one of the main pathophysiological mechanisms of male infertility after treatment with these alkylating agents [36]. Physiologically, oxidative stress seems to contribute positively to acrosome reaction, hyperactivation, oocyte interactions, motility and capacitation of spermatozoa in males. This situation is actually like a double-edged sword [37]. Unfortunately, sperm cells are extremely sensitive to high ROS levels due to the oxidative peroxidation of unsaturated fatty acids, which are found in large amounts in their membranes. Additionally, cytoplasmic defense mechanisms are not present, which, together with the former, result in increased oxidative stress leading to the oxidation of sperm cell DNA, proteins, and lipids, subsequently altering sperm vitality, motility, and morphology [38]. Accumulating evidence points to a relationship between male subfertility and oxidative stress in variable cases [39]. Antioxidant supplementation is gaining increasing attention by alleviating chemotherapy-induced reproductive dysfunction in medical communities [16,19]. So far, several studies have demonstrated the protective effects of some antioxidant compounds such as melatonin, zinc, selenium, and α-tocopherol on the reproductive toxicity caused by BEP treatment [31,40,41]. Significant improvements in sperm count, motility, viability, morphology, testosterone levels, histopathology, and stereology of testes were reported in melatonin administered groups receiving BEP treatment [41]. Supplementation of zinc following BEP treatment restored chromatin integrity, testicular organization and spermatogenesis [40]. An antioxidant cocktail including α-tocopherol, L-ascorbic acid, zinc, and selenium was shown to protect testicular and reproductive endocrine functions when administered in conjunction with BEP therapy, and subsequently enhanced the recovery of BEP-induced testicular dysfunction [31]. Royal jelly also had positive effects on sperm count, viability, motility, and DNA integrity, and testosterone concentration in bleomycin-treated rats [42]. Recently, Abdel-Latif et al. reported that antioxidant kinedine used together with cisplatin prevented histopathological lesions in the testis, increased serum testosterone level and improved sperm motility [43]. Cisplatin-based chemotherapies are associated with reduced weights of reproductive organs, lower sperm count and motility, more frequent morphological abnormalities, and impairment in testicular histology [43,44,45]. A possible reason for lower testes weight is that the secretory and synthesis capacities decrease secondary to the decrease in mitotic activity with chemotherapy. In agreement with the findings of the current study, lower sperm counts, decreased testosterone secretion, increased sperm DNA damage, and altered testis histomorphology can be observed following BEP treatment [7,8,41,46]. Decreased testosterone levels can be observed when the equilibrium redox is lost [47]. The increase in DNA fragmentation, which is associated with many reproduction-related disease states, is undoubtedly related to infertility and subfertility. Ghezzi et al. reported significantly higher aneuploidy and DNA fragmentation following BEP treatment [7]. As anticipated, oxidative damage is the primary factor in increased DNA fragmentation in sperm cells [48]. Oxygen-derived free radicals can easily destabilize DNA and lead to fragmentation [49]. Oxidative stress and DNA fragmentation intersect at a clinical point as the high level of sperm DNA damage is associated with a series of adverse reproductive outcomes. Histological alterations following BEP chemotherapy in the testes are thought to be due to oxidant/antioxidant imbalances [41]. BEP treatment was shown to trigger oxidative stress and apoptosis of spermatogonial stem cells and Sertoli cells resulting in impaired spermatogenesis [50]. The testes mainly use enzymatic antioxidants such as copper/zinc superoxide dismutase and selenoenzyme phospholipid hydroperoxide glutathione peroxidase, as well as non-enzymatic antioxidants such as reduced GSH, to avoid the harmful effects of ROS [47,51,52]. GSH, considered one of the most important antioxidants, contributes to antioxidant defense both as a substrate for glutathione peroxidase and by directly sequencing free radicals [53]. Our experimental research aimed to ameliorate the chemotherapy-induced imbalance in redox hemostasis with exogenous systemic GSH supplementation. Systemic GSH application together with the BEP treatment prevented the deterioration of spermatogenesis and preserved the histological structure of the testis, as shown by the improved testes and epididymis indices, testosterone levels, histomorphological examinations, and reduced DNA fragmentation in comparison to BEP treatment alone. In parallel with these findings, sperm count was higher and morphological abnormalities were lesser in the GSH administrated group compared to the BEP-only-treated group. In terms of testicular histology, GSH restored Johnsen scores, and mean seminiferous tubule epithelial thicknesses in rats receiving BEP treatment. The molecular mechanisms of the positive effects of GSH in this study are suggested as (i) quenching of H2O2, (ii) preventing lipid peroxidation, (iii) stopping membrane oxidation, and (iv) contributing to the enzymatic redox cycle [54]. In agreement with our results, in another study, GSH deficiency was reported to lead to the instability of the spermatozoa midpiece, resulting in defective morphology and reduced motility of the spermatozoa [37]. In a study with diabetic mice, sperm motility was found to be higher when the mice were administered GSH [30]. In a recent study evaluating the possible protective effect of earthworm methanolic extract (EE) on impaired reproductive functions caused by acrylamide (ACR) toxicity, ACR application was shown to reduce testicular GSH, and decrease the sperm count, motility, and viability. On the other hand, the application of EE in combination with ACR protected testicular GSH levels [55]. Although there are differences regarding GSH concentration, these studies support evidence on the beneficial effects of GSH on protection from reproductive toxicity. ## 5. Conclusions Exogenous supplementation of glutathione contributes positively to oxidative stress challenges in different biological systems such as cell cultures, plants, and animals at organismal levels [56,57]. This study revealed the beneficial effects of GSH on the restoration of testicular function, spermatogenesis, and sperm DNA integrity in BEP treated rats, possibly by reversing the deleterious effects of oxidative stress. Though our findings might suggest GSH supplementation as an adjuvant in BEP chemotherapy for alleviating reproductive toxicity, further in vivo studies are required to examine tumor response and therapeutic efficiency for potential clinical implications. ## References 1. Michaelson M.D., Shah S., Lerner S.P.. Epidemiology of and Risk Factors for Testicular Germ Cell Tumors. (2022) 2. 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--- title: A Novel Resveratrol-Induced Pathway Increases Neuron-Derived Cell Resilience against Oxidative Stress authors: - Patrizio Cracco - Emiliano Montalesi - Martina Parente - Manuela Cipolletti - Giovanna Iucci - Chiara Battocchio - Iole Venditti - Marco Fiocchetti - Maria Marino journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10058936 doi: 10.3390/ijms24065903 license: CC BY 4.0 --- # A Novel Resveratrol-Induced Pathway Increases Neuron-Derived Cell Resilience against Oxidative Stress ## Abstract A promising therapeutic strategy to delay and/or prevent the onset of neurodegenerative diseases (NDs) could be to restore neuroprotective pathways physiologically triggered by neurons against stress injury. Recently, we identified the accumulation of neuroglobin (NGB) in neuronal cells, induced by the 17β-estradiol (E2)/estrogen receptor β (ERβ) axis, as a protective response that increases mitochondria functionality and prevents the activation of apoptosis, increasing neuron resilience against oxidative stress. Here, we would verify if resveratrol (Res), an ERβ ligand, could reactivate NGB accumulation and its protective effects against oxidative stress in neuronal-derived cells (i.e., SH-SY5Y cells). Our results demonstrate that ERβ/NGB is a novel pathway triggered by low Res concentrations that lead to rapid and persistent NGB accumulation in the cytosol and in mitochondria, where the protein contributes to reducing the apoptotic death induced by hydrogen peroxide (H2O2). Intriguingly, Res conjugation with gold nanoparticles increases the stilbene efficacy in enhancing neuron resilience against oxidative stress. As a whole, ERβ/NGB axis regulation is a novel mechanism triggered by low concentration of Res to regulate, specifically, the neuronal cell resilience against oxidative stress reducing the triggering of the apoptotic cascade. ## 1. Introduction In Western societies, higher life expectancy is correlated with an increased incidence of neurodegenerative diseases (NDs) [1]. Therefore, research is aimed at discovering possible treatments to prevent or delay these pathological conditions [2,3,4,5]. Previously, we identified a novel pathway triggered by the sex hormone 17β-estradiol (E2) via the synergic action of both receptor subtypes (i.e., ERα and ERβ) that leads to the accumulation of neuroglobin (NGB) in the mitochondria of different cell types, including cancer and neuronal cells. In these cellular contexts, the activation of the E2/ERs/NGB pathway results in cell protection against reactive oxygen species (ROS)-induced cell death. In particular, in neuron-derived cells (i.e., SK-NE-BE cells), E2 accumulates NGB into the mitochondria, where, upon oxidative stress injury, it binds to cytochrome c (Cyt c), avoiding its release into the cytosol and preventing the subsequent activation of the apoptotic signaling cascade [6,7]. The contemporary activation of both ER subtypes by E2 (in particular ERα activation) renders E2/ERs/NGB pathway ineffective against oxidative stress-induced apoptosis in cellular models of neurodegeneration [8]. Here we hypothesize that ERβ selective ligands, which overcome ERα activation, could increase NGB levels maintaining their protective effects against oxidative stress-induced apoptosis. Two different molecules have been taken into consideration: the diarylpropionitrile (DPN), a synthetic and specific ERβ ligand, and resveratrol (3,5,4′-trans-trihydroxystilbene) (Res), a stilbene family member further identified as a phytoalexin, present in plants such as grape skin, cocoa, various berries and peanuts [9,10,11]. Res is considered a very hopeful molecule for preserving human health [12]. Indeed, Res ameliorates the nervous system’s inflammatory state through the inhibition of pro-inflammatory pathways (inhibition of NF-kB) and the induction of pathways that promote cell survival by acting on SIRT-1 [13]. Moreover, Res has been reported to reduce the production of reactive oxygen species (ROS) and lipid peroxidation [14]. Experiments conducted in neuronal-derived cell lines have also shown that Res treatment prevents rotenone-induced fragmentation of mitochondria by inducing mitochondrial fission and fusion and promoting ATP synthesis [15]. Unfortunately, Res use in clinics encounters several limitations [16]. In particular, the in vivo effects of Res appear to be affected by its low solubility, high biotransformation, and low bioavailability [17,18,19], which leads to the co-presence of a plethora of metabolites that could also exert effects that differ from the precursor and potentially impair its action, as demonstrated for the daidzein metabolites [20]. To further increase the complexity of this picture, Res action pathways are still not fully identified. Among other mechanisms, Res, as well as other polyphenols, is able to modulate estrogen receptors (ERs), acting as an agonist or antagonist of the sex hormone 17β-estradiol (E2), depending on the receptor subtype: i.e., ERα and ERβ [21,22]. Moreover, Res, like E2, increases NGB in neuron-derived cells that mainly express ERβ [22]. Intriguingly, our previous studies on ERα-positive breast cancer cells demonstrated that, unlike E2, Res reduces NGB levels in this cellular context, making these cells more susceptible to chemotherapy-induced apoptosis, thus antagonizing the effects of E2 on ERα, which is the only ER subtype expressed in these cells [22]. At present, the potential of Res to increase NGB levels in the mitochondria of neuronal cells is unknown, as well as the physiological outcomes of this effect. The aim of this work is to assess in neuroblastoma cells SH-SY5Y the effect and action mechanism of this molecule, evaluating the ERβ involvement and the possible maintenance of the neuroprotective Erβ–NGB axis against oxidative stress-induced apoptosis. ## 2.1. E2-Res Comparison on NGB Levels in SH-SY5Y First, the expression in SH-SY5Y neuroblastoma cells of estrogen receptor subtypes, ERα and ERβ, has been verified. Figure 1a shows that both receptor subtypes are expressed with a clear predominance of ERβ over ERα. The cells were treated with different concentrations of E2 (10−10 to 10−7 M) and Res (10~7 to 10−5 M) to evaluate NGB levels. Both compounds increase NGB levels at all tested concentrations (Figure 1b,c). ## 2.2. ERs Involvement in Res-Induced NGB Accumulation in SH-SY5Y Subsequently, to better define the molecular mechanisms underlying the Res effect on the increase in NGB levels, SH-SY5Y cells were treated either with E2 (as positive control), diarylpropionitrile (DPN, a selective ERβ agonist) and with the selective ERα agonist propylpyrazoletriol (PPT). Figure 2a shows that both DPN and PPT stimulation increases NGB levels at lower concentrations than E2, suggesting that both receptors are involved in the E2 action mechanism. In addition, cells pretreatment with (R,R)-5,11-Diethyl-5,6,11,12-tetrahydro-2,8-chrysenediol ((R,R)-THC), the ERβ selective inhibitor, or with endoxifen, the ERα selective inhibitor, reduces NGB levels impairing E2 effect. Altogether, these data argue that both receptor subtype activities synergize in E2-induced modulation of NGB levels in this cell line. On the other hand, as reported in Figure 1, Res still increases NGB levels (Figure 2b). This effect is blocked only in the presence of (R,R)-THC, but not when SH-SY5Y cells are pretreated with the ERα inhibitor endoxifen, suggesting that ERβ activity is sufficient for Res-induced NGB level increase (Figure 2b). Finally, cell costimulation with E2 and Res further confirms that Res and E2 share similar signal transduction pathways (Figure 2c); indeed, this treatment does not further increase NGB levels. ## 2.3. Signaling Pathways Involved in Res Effects The signaling pathway triggered by the Res/ERβ complex has been investigated. Previous data demonstrated that E2, through ERβ, triggers p38 protein activation, which is crucial for E2-induced NGB accumulation [23]. Therefore, the Res effect on p38 activation has been analyzed in SH-SY5Y cells. Figure 3a shows that there are no variations in p38 total levels, while Res induces p38 phosphorylation that is completely impaired by cell pretreatment with the ERβ inhibitor, (R,R)-THC, or with the p38 inhibitor, SB (Figure 3a). To further confirm the involvement of p38 activation in Res-induced NGB accumulation, SH-SY5Y cells were stimulated with the p38 inhibitor, SB, and NGB levels were determined. Figure 3b shows that the p38 inhibitor significantly reduces the Res effect on NGB levels, further confirming that Res modulatory action on NGB levels requires the activation of the ERβ/p38 pathway in SH-SY5Y cells. E2 is known to rapidly increase NGB levels by blocking its degradation [23,24]. Therefore, SH-SY5Y cells were treated with MG-132 (MG), the proteasome inhibitor, with chloroquine (Clo), a lysosomal degradation inhibitor, and with cycloheximide (CHX), an inhibitor of gene translation, before Res treatment to verify if this polyphenol acts as an estrogen mimetic also on these pathways. Figure 3c shows that either MG-132 or Clo treatment increases NGB levels with respect to the control, and Res stimulation in the presence of these two inhibitors does not lead to a further accumulation of the protein, suggesting that Res-induced NGB augment depends on the block of NGB degradation. Although CHX treatment enhances NGB levels, its costimulation with Res drastically prevented NGB from the stilbene effects, suggesting that the polyphenol also activates NGB mRNA translation. ## 2.4. Res/ERβ Effect on NGB Localization As previously reported, the protective effect of NGB in preventing stress-induced apoptosis strictly depends on the increase in its levels in the mitochondria [6]. Therefore, the effect of Res on NGB mitochondrial localization has been investigated. SH-SY5Y cells were treated with E2 (10−9 M), Res (10−7 M), H2O2 (5 × 10−5 M), and (R,R)-THC (10−6 M). After the treatments, the cells were fractionated to separate cytosol and mitochondria. PP2A and COX4 protein levels were used to confirm the purity of the isolated compartments (cytosol and mitochondria, respectively). Res, like E2 and H2O2, increases NGB levels both in the cytosolic portion (Figure 4a) and in the mitochondria (Figure 4b). Of note, Res pretreatment reduces H2O2-induced NGB accumulation in both cytosolic and mitochondrial fractions (Figure 4), whereas E2 only reduces the H2O2 effect in the mitochondria. Intriguingly, cell pretreatment with the ERβ inhibitor (i.e., (R,R)-THC) compromises the Res effect just in the cytosol but not in the mitochondrial compartment, highlighting that Res-induced NGB accumulation is strictly dependent on ERβ in the cytosol while the Res effect in the mitochondria seems to be ERβ independent (Figure 4b). The NGB level in mitochondria was also confirmed with confocal microscopy, evaluating NGB colocalization (red) with the mitochondrial protein COX4 (green) (Figure 5). Differently from what is reported in Figure 4b, the results indicate that either E2, Res, and H2O2 increase NGB levels in the mitochondria to the same extent (see bottom panel of Figure 5); however, (R,R)-THC pretreatment does not modify the Res effect on NGB mitochondrial accumulation, confirming the ERβ independence of this Res effect. ## 2.5. Res/ERβ Effect on Cell Resilience to Oxidative Stress As previously reported, NGB accumulated in the mitochondria of neuronal cells exerts a key function in increasing cell resilience against ROS by counteracting cell death and assuring cell survival [6]. Therefore, we evaluated whether the Res modulation of NGB levels was paralleled with the increase in SH-SY5Y cell survival in the presence of oxidative stress. First, cell viability was analyzed after SH-SY5Y cell treatment with E2 (10−9 M), Res (10−7 M), H2O2 (5 × 10−5 M), and (R,R)-THC (10−6 M) by using propidium iodide (PI) assay. As shown in Figure 6, E2 or Res stimulation increases the DNA amount proportional to the increase in cell number with respect to the vehicle-treated cells. H2O2, as expected, drastically reduces cell number. Notably, cell pretreatment with E2 or Res provides protection against the reduction of cell number induced by H2O2 treatment; however, the effects of E2 and Res costimulation are not cumulative, suggesting that a similar pathway is triggered by both the hormone and the polyphenol. Pretreatment with (R,R)-THC does not modify H2O2 activity or the proliferative effect of Res, while it completely prevents the Res protective effect against H2O2-induced cell number decrease, supporting the involvement of ERβ in this Res-induced protective pathway. The propidium iodide assay provides a quick answer regarding the effects of different substances on cell viability but does not allow us to understand if an apoptotic cascade has been activated. Therefore, the level of cleaved PARP-1 (Poly ADP-ribose polymerase), a well-known marker of late apoptosis, was examined. After stimulating SH-SY5Y cells with E2, Res, and H2O2, we observed that only H2O2 could induce PARP-1 cleavage (Figure 7a). Moreover, cell pretreatment with E2 or Res before H2O2 stimulation decreases ROS-induced PARP-1 cleavage. Notably, Res takes back the H2O2-induced PARP-1 cleavage at the control levels, while E2 just reduces by 2 times PARP-1 cleavage, sustaining its neuroprotective role against oxidative stress-induced apoptosis. Furthermore, cells pretreatment with (R,R)-THC before H2O2 stimulation strongly reduces the Res antiapoptotic effect (Figure 6b). ## 2.6. Effect of Res Conjugated with Gold Nanoparticles on NGB and on Cell Resilience to Oxidative Stress As already mentioned in the introduction, one of the main problems related to the use of polyphenols in general, and of Res in particular, lies in their poor bioavailability, mainly due to the extensive metabolism those compounds are exposed to in the human body. Nowadays, an important component of drug research efforts is aimed at improving the pharmacokinetic properties and/or enhancing the bio-efficacy of compounds, such as polyphenols. Recently, Res conjugated with gold nanoparticles has been efficiently synthesized and characterized in terms of toxicity and NGB modulation in breast cancer cells expressing only the subtype α of ER [25,26]. According to these previous results, we tested the effect of different concentrations of Res in conjugation with gold nanoparticles (NP-R) in SH-SY5Y. Results indicate that NP-R significantly increases NGB level already at an NP concentration of 1 µg/mL (corresponding to 10−8 M of loaded Res) and 3 and 9 µg/mL NP concentration (corresponding to a load of Res of 3 × 10−8 M and 10−7 M, respectively) (Figure 8a), while unconjugated nanoparticles (NPs) at the same concentrations do not affect NGB levels. In addition, already at the concentration of 10−8 M, Res conjugated with nanoparticles shows the same effect of the higher concentration (10~7 M) of unconjugated Res on cell vitality, whereas NPs do not significantly modify the number of cells, indicating that the nanospheres do not possess any toxic or proliferative effects in these cells (Figure 8b). Finally, the ability of Res conjugated with nanospheres to protect cells against oxidative stress-induced apoptosis was evaluated. The data (Figure 8c) show that, similarly to E2 and unconjugated Res, cell pretreatment with NP-R reduces the H2O2-induced PARP-1 cleavage already at 10−8 M of Res. ## 3. Discussion Over the past two decades, many studies have been conducted regarding the beneficial power of Res on health [27,28,29,30,31,32,33,34,35]. Among others, Res appears to have a role associated with slowing down or preventing cognitive impairment. In this context, the anti-inflammatory and antioxidant effects of Res lead to the hypothesis that this polyphenol may be a useful treatment for neurological disorders such as Alzheimer’s disease (AD) and stroke that occur through inflammatory damage and oxidative stress to the central nervous system [36]. Furthermore, it has also been shown that Res can have a protective effect on the blood-brain barrier in pathological conditions such as multiple sclerosis [37,38]. Since there are many protective effects ascribed to Res, research has focused on identifying the mechanisms of action by which this stilbene acts. Among those, the direct non-enzymatic antioxidant ability of Res has been hailed as responsible for the neuroprotective effects of this stilbene. Moreover, Res has been reported to increase the activity of SIRT1, acting as a protective molecule against mitochondrial dysfunctions [11,39,40,41]. Finally, the interaction of Res with estrogen receptors has also been demonstrated. Indeed, it was seen that mouse ovarian cells transfected with ERα or ERβ and treated with Res (10−4 M) showed reduced cell proliferation compared to non-transfected ones, indicating that the effect was dependent on the expression of the ERs [42]. Furthermore, Res at low concentrations (10~7, 10−6, and 10~5 M) reduced NGB basal levels in ERα-positive breast cancer cells, specifically by antagonizing E2 effects [22]. One of the major criticisms made by the scientific community to the concept of nutraceuticals (i.e., the use of substances of natural origin as possible drugs) lies in the fact that despite the encouraged in vitro and in vivo outcomes when translated to clinical trials, Res did not show the expected significant therapeutic effects [16]. Res is subjected to intense metabolism by the enzymes present in the intestinal microbiota, on the intestinal epithelium, and in the liver, which considerably reduces its bioavailability and increases the concentration of its glucuronidated or sulfated metabolites, whose effects are currently unknown [43,44,45]. Thus, the poor reproducibility of the beneficial effects of Res is mainly associated with the effective concentrations of this compound that have been tested in the literature. It has been estimated that 25 mg of oral dose produces < 5 ng/mL, about 21 nM, of un-metabolized Res in human plasma ([11] and literature cited therein), whereas the majority of studies have been conducted by using a Res concentration ranging from 10−5 to 10−4 M. In the last decade, to improve the poor bioavailability of this stilbene, various methodological approaches have been developed, such as nanoencapsulation in lipid nanocarriers or the synthesis of nanoparticles [25,26,46,47,48]. The identification of NGB as a neuroprotective protein and the discovery of its positive modulation by E2 in neuron-derived cells have paved the way for the study of new possible action mechanisms for Res. Indeed, it is known that the E2/ERβ complex leads to rapid activation of the p38 kinase with subsequent up-regulation of NGB in the mitochondrion, where the protein prevents the activation of the apoptotic cascade and acts as a stress sensor [23]. This work aims to evaluate whether Res, at concentrations compatible with those present in the plasma following its ingestion [11], is able to activate the ERβ/NGB pathway, inducing the accumulation of NGB and increasing the resistance of neuronal-derived cells to oxidative stress. From the reported results, it emerges that, already at the concentration of 10−7 M, Res is more effective than E2, at the same concentration, in increasing NGB levels and that this mechanism is dependent on ERβ. In fact, by pretreating the cells with (R,R)-THC, a selective inhibitor of ERβ, and endoxifen, an inhibitor of ERα, the effect of Res is blocked only in the presence of (R,R)-THC. Interestingly, in ERα-positive breast cancer cells (MCF-7 and T47D), Res acts as an ERα antagonist by reducing the ability of this receptor subtype to activate AKT kinase phosphorylation and reducing NGB levels [49]. In cells of neuronal derivation used in this work, Res acts as an agonist of E2 on ERβ, the most expressed estrogen receptor subtype in neurons, leading to the accumulation of NGB without promoting the activation of ERα. The reported data indicate that DPN, the synthetic selective ERβ agonist, increases NGB levels to a lesser extent than E2. It would have been expected that the Res, by activating only one receptor subtype, should show effects similar to those observed after the stimulation with DPN rather than having significantly greater effects on the accumulation of NGB. These discrepancies can be reconciled by the evidence that both ERα and ERβ activate discordant signaling pathways in all cell lines, including neurons. In fact, the binding of PPT or E2 to ERα triggers the persistent activation of the PI3K/AKT and ERK/MAPK signaling pathways, which inhibit the activation of the p38 pathway that is activated by the binding of E2 or DPN to ERβ [6,23,50,51,52]. While PPT and DPN activate one or the other pathway, E2, by binding both receptor subtypes, leads to a balance between the divergent signal pathways activated by the two receptor subtypes. Finally, Res inhibits the PI3K/AKT and ERK/MAPK pathways activated by ERα [49]. allowing the full activation of the pathway activated by ERβ. In fact, the reported results show that Res activates p38 kinase by increasing the levels of its phosphorylation in an ERβ-dependent manner; in fact, the effect of Res is blocked when cells are pretreated with (R,R)-THC and SB (p38 inhibitor). In addition, the induction of NGB levels by Res also involves the activation of p38. In fact, in the presence of an SB inhibitor, Res’s ability to increase NGB levels is significantly reduced. Finally, the cell co-treatment with E2 and Res does not lead to a further increase in NGB as the activation of ERα induced by E2, which has a major affinity for its receptors than Res, reduces the effects of ERβ-dependent signaling pathways. It is reported in the literature that E2 is able to increase NGB levels mainly by blocking its degradation and partly by increasing its synthesis [23,24]. The data reported in this work show that, likewise, E2 also Res increases NGB levels by blocking its degradation and increasing Ngb gene transduction; in fact, in the presence of either proteasome inhibitor (i.e., MG-132) or the inhibitor of lysosomal degradation (i.e., Clo), Res does not lead to a further accumulation or degradation of NGB to the lysosomal degradation is still working and vice versa. Surprisingly, the protein synthesis inhibitor (i.e., CHX) induces an increase in NGB levels, whereas the CHX costimulation with Res does not increase NGB levels. The Ngb promoter lacks the TATA box; however, many conserved putative transcription factor binding sites have been identified within the human Ngb promoter, including two GC-boxes and two neuron-restrictive silencer element (NRSE) sites that are bound by the neuron-restrictive silencer factor (NRSF), a 210 kDa glycoprotein containing nine zinc finger domains, a silencer of neuron-specific gene expression in undifferentiated neuronal progenitor cells [50]. In addition, the Ngb promoter region is characterized by the presence of binding sites for several transcription factors such as the specificity protein (Sp) family members Sp1 and Sp3, the cAMP response element binding (CREB) protein, the early growth response protein 1, and members of the Nuclear Factor κ-light chain enhancer of activated B cells (NF-κB) family (i.e., p50, p65, cRel) [50]. It could be possible that 24 h of cycloheximide treatment prevents the translation of the silencer protein, enhancing NGB levels. In addition, it has been reported that cycloheximide alters protein degradation through activation of protein kinase B (PKB/AKT) [51], further enhancing NGB levels. On the other hand, resveratrol triggers the p38 activation, a well-known inducer of several transcription factors including CREB activation [52,53,54] that could overcome NRSF inhibition allowing Ngb transcription. Although Res stimulation prevents NGB degradation and enhances Ngb transcription, the contemporary treatment with cycloheximide reduces the NGB translation and the NGB protein overexpression could not occur. Altogether these data indicate that, via ERβ signaling, nM concentrations of Res (10−7 M) activate, like E2, the pathways that culminate with the accumulation of a neuroprotective protein, i.e., NGB. Since the protective effect of NGB in preventing stress-induced apoptosis in neuron-derived cells does not depend only on the increase in its levels but also on its intracellular localization, the subcellular localization of this protein was analyzed. The results show that Res increases NGB levels in the cytosol via an ERβ-dependent mechanism. This event is in agreement with what has been shown in the literature, that NGB accumulated in the cytosol by different inducers (e.g., E2 or H2O2) can be released outside cancer cells [55] or astrocytes [55,56], exerting protective effects on the survival of neighboring cells with autocrine and paracrine mechanisms. In the mitochondria, Res signals are able to carry the globin inside the mitochondria, even if to a lesser extent than E2, and in this latter compartment (R,R)-THC does not seem to influence the activity of Res. Although NGB does not have any mitochondrial localization domains in its sequence, E2 has been shown to induce translocation of NGB into this organelle by increasing huntingtin protein (Htt) intracellular levels through the activation of ERα. Since Res prevents the rapid activities of this receptor subtype, the translocation of NGB to the mitochondrion could rely on other transport proteins whose recruitment could depend on one of the different signaling pathways activated by Res. Once accumulated into the cytosol and in the mitochondrion, NGB can bind the oxidized cytochrome c, released in the cytosol following oxidative stress, avoiding its bond with APAF-1, or it can directly block the cytochrome c inside mitochondria, inhibiting both cases, the activation of caspase 3 and the subsequent apoptotic cascade [6]. The results obtained from the propidium iodide fluorescence assay show the involvement of ERβ in the protective pathway activated by Res against H2O2-induced cell death. This is further supported by the data obtained from the study of PARP-1 protein as a marker of late apoptosis. As shown, when cells are pretreated with (R,R)-THC before stimulation with Res and H2O2, the protective role of Res is lost due to the (R,R)-THC-induced blockade of ERβ. Thus, although Res induces NGB accumulation into the mitochondria through an ERβ-independent pathway, the stilbene protection against oxidative stress-induced apoptosis requires the activation of ERβ signaling. Altogether these data highlight a novel protective pathway triggered by Res against oxidative stress injury that involves both ERβ signaling and NGB accumulation in neuron-derived cells and is not linked just to the antioxidant ability of Res chemical structure. Of note, the different modulation of NGB levels triggered by Res in the presence of the two different ER subtypes ([22,26] and present data) open a novel avenue in the field of pharmacological treatment of degenerative diseases. Although in this work, for the first time, a very low concentration of Res (10−7 M) has been used, we adopted a specific strategy to potentially preserve Res from the extensive metabolism to which polyphenols are exposed and to improve its biological activity [57,58,59] by using Res conjugation with highly hydrophilic gold nanospheres as nanocarriers. The reported data demonstrate that neither naked nor Res-conjugated nanoparticles are toxic in SH-SY5Y cells. Moreover, Res-conjugated nanospheres increase NGB levels and maintain the protective effect against apoptosis induced by oxidative stress, preventing PARP-1 cleavage already at 10−8 M, then surpassing the effect of unconjugated Res (10−7 M), indicating that the conjugation of Res with gold nanospheres not only may enhance Res bioavailability but also strengthens its bioactivity, providing encouraging outcomes for the translation of this different administration routes into clinical application for neuronal protection. Altogether, these data indicate that the Res effect does not depend on generic antioxidant properties ascribed to the structure of this molecule and, more generally, to all polyphenols of plant origin, which require high intracellular levels, but on the specific activation of ERs signaling pathways, which can be obtained at much lower concentrations, compatible with its bioavailability. The obtained results allow us to consider Res, at concentrations compatible with those present in the plasma following a diet rich in this stilbene, as a substance capable of mimicking the neuroprotective actions of estrogens without the secondary effects of the hormone. In conclusion, Res appears to be a promising molecule capable of maintaining high levels of NGB in neuronal-derived cells, leading to protection against oxidative stress and finding a therapeutic application for this molecule against pathological conditions such as neurodegenerative diseases. ## 4.1. Reagents The Bradford protein assay and the chemiluminescence reagent for Western Blot Clarity Western ECL Substrate were obtained from Bio-Rad Laboratories (Hercules, CA, USA). The anti-phospho-p38 (Thr180/Tyr182) (cat. n° 4511), anti-p38 (cat. n° 8690), and anti-poly[ADP-ribose] polymerase 1 (PARP-1) (cat. n° 9542) antibodies were purchased from Cell Signalling Technology Inc. (Beverly, MA, USA). The anti-α-tubulin (cat. n° T6074) and anti-COX-IV (cat. n° ZRB1593) antibodies were purchased from Sigma-Aldrich (St. Louis, MO, USA). Anti-PP2A (cat. n° sc-56954), anti-ERα (cat. n° sc-8005), and anti-ERβ (cat. n° sc-373853) antibodies were obtained from Santa Cruz Biotechnology (Santa Cruz, CA, USA). The anti-NGB antibody (cat. n° MABN369) was purchased from Merck Millipore (Darmstadt, D). The ERα inhibitor endoxifen and the ERβ inhibitor (R,R)-5,11-Diethyl-5,6,11,12-tetrahydro-2,8-chrysenediol ((R,R)-THC) were purchased from Tocris (Ballwin, MO, USA). All the other products were from Sigma-Aldrich. Analytical and reagent-grade products were used without further purification. ## 4.2. Cell Culture Human neuroblastoma cells SH-SY5Y (American Type Culture Collection, LGC Standards S.r.l., Milan, Italy) were grown at 37 °C in air containing $5\%$ CO2 in either modified, phenol red-free, Dulbecco’s Modified Eagle’s Medium (DMEM) medium. Ten percent (vol/vol) of charcoal-stripped fetal calf serum, L-glutamine (2 mM), non-essential amino acid (2×), sodium pyruvate (1 mM), HEPES (10 mM), and penicillin (100 U/mL) were added to the media before use. Cells were used in passages 4–8, as previously described [7]. The cell line authentication was periodically performed by amplification of multiple short tandem repeat loci by BMR genomics S.r.l (Padova, Italy). Cells were treated for 24 h with either vehicle (DMSO or phosphate-buffered saline [PBS], 1:1000; vol/vol) or E2 (10−9 M) or Res (10−7, 10−6, and 10−5 M) or H2O2 (5 × 10−5 M). When indicated, endoxifen (10−6 M) or (R,R)-THC (10−6 M), as indicated by the manufacturer, were added 1 h before Res (10−7 M) or E2 administration, Res (10−7 M) or E2 were added 4 h before H2O2 addition for 24 h, while the p38 inhibitor SB203580 (5 × 10−6 M) was added 1 h before Res (10−7 M). For blocking NGB degradation, the cells were treated for 4 h with the proteasomal inhibitor MG-132 (10−6 M), chloroquine (10−5 M), and the protein synthesis inhibitor cycloheximide (10−5 M), and when in costimulation, Res was administrated at the same time of the inhibitors. ## 4.3. Western Blot Assay After the treatments, cells were lysed, and proteins were solubilized in the YY buffer (50 mM HEPES at pH 7.5, $10\%$ glycerol, 150 mM NaCl, $1\%$ Triton X-100, 1 mM EDTA, and 1 mM EGTA) containing $0.70\%$ (wt/vol) sodium dodecyl sulfate (SDS). Total proteins were quantified using the Bradford protein assay. Solubilized proteins (40 μg) were resolved by $7\%$, $10\%$, or $13\%$ SDS-polyacrylamide gel electrophoresis at 100 V for 1 h at 24.0 °C and then transferred to nitrocellulose with the Trans-Blot Turbo Transfer System (Bio-Rad) for 7 min. The nitrocellulose was treated with $5\%$ (wt/vol) bovine serum albumin or non-fat dry milk in 138 mM NaCl, 25 mM Tris, pH 8.0, at 24.0 °C for 1 h and then probed overnight at 4.0 °C with either anti-NGB (final dilution, 1:1000), anti-phospho-p38 (final dilution, 1:1000), anti-PP2A (final dilution, 1:1000), anti-ERα (1:1000), anti-ERβ (1:1000), or anti-PARP-1 (final dilution, 1:1000) antibodies. The nitrocellulose was stripped by the Restore Western Blot Stripping Buffer (Pierce Chemical, Rockford, IL, USA) for 10 min at room temperature and then probed with either anti-p38 (final dilution, 1:1000), anti-COXIV (final dilution 1:1000), or anti-α-tubulin (final dilution, 1:40,000) antibodies to normalize the protein loaded. The antibody reactivity was detected with ECL chemiluminescence Western blotting detection reagent using a ChemiDoc XRS+ Imaging System (Bio-Rad Laboratories, Hercules, CA, USA). The densitometric analyses were performed by the ImageJ software for Microsoft Windows (National Institute of Health, Bethesda, MD, USA). ## 4.4. Mitochondria/Cytosol Fractionation Cell fractionation was performed using the Mitochondria/Cytosol Fractionation Kit (ABCAM, Cambridge, U.K.). After seeding 10 million cells and treating them as reported above, the medium was removed, and the cells were collected in 15 mL tubes and centrifuged at 600× g for 5 min at 4 °C. Subsequently, the supernatant was removed, and the pellet was resuspended in 5 mL of cold PBS. It was centrifuged at 600× g for 5 min at 4 °C. The supernatant was removed, and the pellet was resuspended with 1 mL of Cytosol Extraction Buffer Mix 1×. It was incubated on ice for 10 min, and then the cells were homogenized with the Potter. The homogenate was transferred to 1.5 mL tubes and centrifuged at 700× g for 10 min at 4 °C. The supernatant was collected in other 1.5 mL tubes and centrifuged at 10,000× g for 30 min at 4 °C. The supernatant, i.e., the cytosolic fraction, was taken and placed in other tubes, while the pellet, i.e., the mitochondrial fraction, was resuspended with YY lysis buffer, and the samples were prepared for the electrophoretic run. In the case of cell fractionation, COX4, a mitochondrial protein, and PP2A, a protein localized in the cytosol, were used as control proteins. The detection of these proteins in the cytosolic and mitochondrial fractions provides control of the purity of the obtained fractions. ## 4.5. NGB Mitochondrial Localization with Confocal Microscopy After having seeded the cells on slides and stimulated with the treatments, the cells were fixed with $4\%$ paraformaldehyde for 10 min and subsequently permeabilized with $0.1\%$ Triton for 5 min. Then the slides with the cells were incubated with $2\%$ bovine serum albumin (BSA) solution in PBS for 30 min. Thus, the slides were incubated overnight at 4°C in the dark with anti-NGB, and anti-COX-IV prepared 1:200 in $0.2\%$ BSA in PBS. The next day, the slides were incubated with Alexa Fluor 488 (anti-rabbit) and 578 (anti-mouse) secondary fluorescent antibodies (Invitrogen, Carlsbad, CA, USA) (red for NGB and green for COX4) prepared 1:400 in $0.2\%$ BSA in PBS for 30 min in the dark at RT. Finally, the slides with the cells were mounted on specimen slides, and the images were captured under the confocal microscope. Images were analyzed with ImageJ software (NIH, Bethesda, MD, USA) and JaCoP plugin (Just another Colocalization Plugin) to determine Pearson’s correlation coefficient. ## 4.6. Cellular DNA Content—Propidium Iodide (PI) Assay SH-SY5Y cells were grown up to $80\%$ confluence in a 96-well plate and treated with the selected compounds. The cells were fixed and permeabilized with cold EtOH $70\%$ for 15 min at −20 °C. EtOH solution was removed, and the cells were incubated with PI buffer for 30 min in the dark. The solution was removed, and the cells were rinsed with PBS solution. The fluorescence was revealed (excitation wavelength: 537 nm; emission wavelength: 621 nm) with TECAN Spark 20 M multimode microplate reader (Life Science, Italy). ## 4.7. Synthesis and Purification of Gold NP and NP-R The gold NPs stabilized with citrate and L-cystein (L-cys) were prepared and characterized in analogy to literature reports [25,26,57]. Briefly: 25 mL of L-cys solution (0.002 M), 10 mL of citrate solution (0.01 M), and 2.5 mL of tetrachloroauric acid solutions (0.05 M) were mixed sequentially in a 100 mL flask, provided with a magnetic stir. After degassing with Argon for 10 min, 4 mL of sodium borohydride solution (0.00008 M) was added, and the reaction continued for 2 h at room temperature. 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--- title: 'Health and Sedentary Behaviors within Polish Nurses: A Cross-Sectional Study' authors: - Anna Bartosiewicz - Edyta Łuszczki journal: Nutrients year: 2023 pmcid: PMC10058938 doi: 10.3390/nu15061312 license: CC BY 4.0 --- # Health and Sedentary Behaviors within Polish Nurses: A Cross-Sectional Study ## Abstract Health behaviors play a pivotal role in improving and strengthening health. Nurses, who constitute the vast majority of employees in the health sector, play a crucial role not only in treating disease but also in promoting and maintaining optimal health for themselves and society. The purpose of the study was to assess the level of health and sedentary behavior and the factors influencing them among nurses. A survey, cross-sectional study was conducted among 587 nurses. Standardized questionnaires evaluating health and sedentary behavior were used. The study utilized both single-factor and multifactor analyses, employing the linear regression method and Spearman correlation coefficient. The results showed that the health behaviors of the survey nurses were at an average level. Sedentary time (in hours) was an average of 5.62 h (SD = 1.77) and correlates significantly ($p \leq 0.05$) and negatively (r < 0) with health behaviors in terms of the positive mental attitude subscale; the longer the sitting time, the lower the intensity of this type of health behaviors. The efficient functioning of the healthcare system is greatly dependent on nursing staff. To improve health behaviors among nurses, systemic solutions such as workplace wellness programs, incentives for healthy behaviors, and education on the benefits of a healthy lifestyle are needed. ## 1. Introduction In recent years, there has been growing public awareness of the importance of health behaviors in sustaining and improving overall health [1,2,3,4,5]. Health behaviors include a variety of habits, attitudes, and intentional behaviors that can be pro- and anti-health and relate to the bio, psycho, and social aspects of human functioning [6,7,8]. Studies indicate the important role of proper nutrition, physical activity, participation in preventive examinations, maintaining safety, adequate sleep, and avoiding addictions (tobacco, alcohol, medications) [8,9,10]. Furthermore, an increasing amount of research indicates that a sedentary lifestyle not only significantly reduces quality of life but also leads to the development of many diseases, such as overweight and obesity, diabetes, hypertension, and spinal degeneration. Ultimately, it can even lead to significant disability and even death [11,12,13]. Sociodemographic factors, family circumstances, or type of work can influence health behavior [8,9]. Nurses, who constitute the vast majority of employees in the health sector, participate not only in combating the effects of the disease but also in every action leading to maintaining an optimal state of their own and society’s health [14,15,16]. Moreover, as healthcare professionals, nurses can serve as positive role models for their patients, families, and friends [16,17]. Unfortunately, numerous studies have indicated that employees in the healthcare sector, including nurses, often fail to practice behaviors that promote and sustain good health, despite their knowledge and high awareness of health [18]. It is difficult to pinpoint a clear cause. The issue is multifaceted and influenced by various factors. The unique nature of nursing work must be considered, including the shift system and the disruption of natural sleep, rest, and nutrition cycles, as well as overwork, stress, and time pressure [19,20]. These factors can make it challenging for nurses to maintain healthy habits [21]. Therefore, it is important for nursing leaders, in collaboration with healthcare organizations, to prioritize promoting and strengthening health behaviors among nurses [22]. This is not only a workplace health problem but also a potential financial and patient safety issue. Creating policies and jobs that take into account holistic support for this professional group is a guarantee of stress reduction, professional burnout, better health condition, and thus patient safety and high-quality healthcare [18,23,24]. The efficient functioning of the healthcare system is greatly dependent on nursing staff [14]. Staff shortages and the age of over 50 of the majority of nurses currently working in the system require special attention when discussing the importance of good health conditions of this professional group for public health. In addition, the fact that among the leading causes of death, most are related to behavioral factors increases the need for research in this field [25,26]. The purpose of the study was to assess the level of health and sedentary behavior and the factors influencing them among nurses. ## 2. Materials and Methods This is a cross-sectional descriptive study, carried out from April to June 2021 in the Subcarpathian region in Poland. The study involved 587 nurses working in the following medical entities: primary health care, hospitals, outpatient specialist care, hospices, independent health care institutions, health care centers and social welfare homes, private sector, nursing homes, and resorts. Medical entities have been randomly selected through a randomized algorithm program. The sample size was determined using EPI INFO (StatCalc) software. A multistage random cluster sampling method was used. Convenient sampling was used, and the inclusion criterion for the participants was professionally active nurses with a license to practice, at least 2 years of work experience, and consent to participate in the study. The questionnaire was distributed to participants in sealed envelopes to ensure confidentiality. In total, 1150 questionnaires were distributed, 614 were collected. All questionnaires were checked, and due to the incompleteness of the answers, 27 questionnaires were excluded from the study. Data from 587 questionnaires were entered into an Excel spreadsheet, coded, and subjected to statistical analysis. To explain the purpose and conditions of the study, a meeting was organized in the medical entities before the survey. Participation in the study was voluntary, with the possibility of withdrawing from the study at any stage and without consequences. The nurses were assured of the anonymity of the study. The nurses included in the study were a representative group of all nurses working in the southeastern region of Poland (the error threshold was $4\%$, that is, the test power was 0.96). The survey technique used a standardized questionnaire, including the Health Behaviors Inventory (HBI), a modified Polish version of the International Physical Activity Questionnaire (IPAQ), and questions regarding the sociodemographic data of the respondents. ## 2.1. Health Behaviour Inventory The HBI questionnaire is used to monitor pro-health behaviors; it contains 24 statements describing health-related behaviors. Analysis of the frequency of individual behaviors indicates the overall result of individual health behaviors. The questionnaire is divided into four subscales:-Proper Eating Habits (PEH), which primarily take into account the type of food eaten (type of bread, fruit, and vegetables);-Preventive Behaviours (PB), related to compliance with health recommendations and how to obtain information in the field of health and disease;-Health Practices (HP), related to daily habits related to sleep, physical activity, and recreation;-Positive Mental Attitude (PMA), related to psychological factors such as avoiding stress, strong emotions, or other depressing situations. Respondents specifying the frequency of specific health behaviors answer questions on a five-point scale, where 1 means almost never, 2 means rarely, 3 means occasionally, 4 means often, and 5 means almost always. The questionnaire evaluates the frequency of behaviors over the last year, and the average examination time does not exceed 5 min. To obtain a general indicator of the intensity of health behaviors, all values marked by the respondent are summarized. The number of points varies from 24–120. Higher scores correspond to a higher level of declared health behaviors. The results are interpreted according to the sten scale: according to the norms (separate for women and men) given in the key to this questionnaire, sten scores 1–4 mean low, sten scores 5–6 average, and sten scores 7–10 high regarding increased health behaviors. The results of each of the four subscales of the HBI questionnaire are the averages of the responses given to the questions included in them. The results obtained were interpreted as low, high, or medium according to the following criteria: an average of 1 means “almost never”; an average of 2 means “rarely”; an average of 3 means “from time to time”; an average of 4 means “often”; and an average of 5 means “almost always” [27]. ## 2.2. Sedentary Behaviors (SB)—Single Item of the IPAQ Respondents retrospectively reported their sedentary behaviours (SB). To obtain the most accurate results, before the survey, nurses were asked to pay attention to and/or record how much time they spend sitting during the day before respondents retrospectively reported their sedentary behavior in the survey. A single item questionnaire (the short version of the IPAQ questionnaire) was used. The question asked: “How long have you been sitting in the last 7 days? When answering, nurses indicated how much time (in hours per day) they spent sitting [28]. ## 2.3. Statistical Methods Used The analysis of quantitative, which represent numerical, data was performed by calculating the mean, standard deviation, median, and quartiles. The analysis of qualitative variables (i.e., not expressed in numbers) was performed by tabulating the frequency and percentage of each value. Single- and multi-factor analysis of the influence of many variables on the quantitative variable was performed using the linear regression method. The results are presented as values of the parameters of the regression model with a $95\%$ confidence interval. The correlations between the quantitative variables were analysed using the Spearman correlation coefficient. The analysis adopted a significance level of 0.05. Therefore, all p-values less than 0.05 were interpreted as correlations that are unlikely to have occurred by chance. The analysis was performed in the R program, version 4.1.3 [29]. ## Characteristics of Study Group The study involved 587 nurses, mostly women ($80.75\%$ vs. $19.25\%$), aged 38–52. Details are presented in Table 1. ## 4. Findings The results showed that almost half ($41.74\%$) of the participants declared an average level of health behaviors, $33.39\%$ were high and $24.87\%$ were low (Table 2 and Table 3). The average results of the subscales “Proper eating habits”, “Preventive behaviors” and “Positive mental attitude” were within the range of 4 in a scale of 1–5, where 4 indicates a high frequency of behaviors in these areas. The average result of the “Health practices” subscale was 3.39 points (rounded to 3). Thus, the average frequency of undertaking behaviors in this area is “from time to time” (Table 4). Univariate and multivariate analyses in the linear regression model for the entire HBI scale (separate for each of the analyzed features) showed that none of the variables analyzed in the study are a significant predictor of the score on this scale ($p \leq 0.05$), (Table 5). The single-factor linear regression model in the scope of the PEH subscale (separate for each of the features analyzed) showed that an important ($p \leq 0.05$) predictor of health behavior among nurses was the level of education, specifically bachelor’s title (regression parameter is 0.249, so increases the result on this scale by an average of 0.249 points in relation to secondary education). The multivariate linear regression model within the scope of the PEH subscale showed that important ($p \leq 0.05$) independent predictors of the result of health behavior among nurses were the level of education, specifically the bachelor’s title (the regression parameter is 0.314, and therefore increases the result on this scale, on average, by 0.314 points in relation to secondary education), and the workplace—that is, work in IHI (the regression parameter is 0.239, and thus increases the result on this scale by an average of 0.239 points in relation to the lack of employment in IHI), (details available in Supplementary Materials—Table S1). The single and multivariate linear regression model (separate for each of the analyzed features) in the scope of the PB subscale showed that none of the variables analyzed in the study features is an important predictor of the result on this scale ($p \leq 0.05$), (details available in the Supplementary Materials—Table S2). The single-factor linear regression model (separate for each of the analyzed features) in the scope of the PMA subscale showed that none of the analyzed features are an important predictor of the result on this scale ($p \leq 0.05$). The multivariate linear regression model in the scope of the PMA subscale showed that important ($p \leq 0.05$) independent predictors on this scale are age (the regression parameter is 0.026, so each subsequent year raises the result on this scale by 0.026 points) and nurses’ work experience (the regression parameter is −0.025, so each subsequent year of work reduces the result on this scale by an average of 0.025 points), (details available in the Supplementary Materials—Table S3). The single and multivariate linear regression model (separate for each of the analyzed features) in the HP scope showed that none of the variables analyzed is an important predictor of the result on this scale ($p \leq 0.05$), details available in Supplementary Materials—Table S4). The results showed that sedentary time (in terms of hours) had an average of 5.62 h (SD = 1.77) and ranged from 1.71 to 11.29 h/day (Table 6). The single-factor linear regression model (separate for each of the features analyzed) showed that the gender of the male is a significant ($p \leq 0.05$) predictor of sitting time among the nurses surveyed (the regression parameter is −0.573, indicating that it reduces sitting time, on average, by 0.573 h per day in relation to the female sex. Additionally, the number of full-time jobs is also a significant predictor ($p \leq 0.05$), with a regression parameter of −0.38. This indicates that each additional job reduces sitting time by an average of 0.38 h per day. The multivariate linear regression model showed that the gender of men is still a significant (p ˂ 0.05) independent predictor of sitting time, with a regression parameter of −0.489. This means that it reduces sitting time by an average of 0.489 h per day with respect to the female sex (Table 7). Correlation results showed that sitting time correlates significantly ($p \leq 0.05$) and negatively (r < 0) with health behaviors, specifically with the positive mental attitude subscale. This means that the longer the sitting time, the lower the intensity of this type of health behavior (Table 8). ## 5. Discussion It was noted that the health behaviours of nurses were at an average level. This is consistent with findings by Ross et al., who found that despite health knowledge and awareness, nurses do not always maintain healthy behaviors [18]. Nurses’ working conditions have been shown to affect their health, with numerous authors identifying this professional group as being burdened by health problems, such as obesity, insufficient or lack of physical activity, inappropriate eating behaviours, smoking, excessive alcohol consumption, and inadequate rest [21,30,31,32]. According to the 2022 Report of the Supreme Chamber of Nurses and Midwives, the numerically largest age range among nurses is 51–60 years, which includes 84,444 nurses, which represents $36.0\%$ of the number of nurses employed in Poland. Despite having acquired pension rights, up to 68,955 nurses still work in the profession in the 61–70 age bracket and the over 70 age bracket. These groups represent $29.36\%$ of the total workforce. By 2030, up to $65\%$ of nurses currently employed are projected to be of pensionable age [33]. In our study, the mean age of the nurses in our study was 44.63 ± 9.24 years and their work experience was 19.95 ± 9.53 years. The issues of health behaviors among nurses have been widely addressed in both Polish and foreign research [21,34]. In our study, we sought to analyze the amount of time nurses spend on sedentary behavior and how these behaviors affect their overall health, which we evaluated using the HBI questionnaire. The results showed that almost half ($41.74\%$) of the participants declared a moderate level of health behaviors, while $33.39\%$ reported a high level, and $24.87\%$ reported a low level. This indicates that only about one third of the respondents have high health behaviors that may be related to their health status and the quality of their profession. On the contrary, the majority have moderate or low health behaviors. This is consistent with a study by Orszulak et al. who surveyed a group of nurses and also found that only $19.87\%$ of the study group exhibited a high prevalence of health behaviors [34]. Moreover, the results of our studies are consistent with those of other authors. Książek et al. [ 35], the research by Różewicz et al. [ 36], and the study of Jankowska-Polańska et al. [ 37] all found that most examined nurses had a moderate level of health behaviors. Nurses face potential barriers to maintaining a healthy lifestyle both on and off the job. These include lack of breaks, shift work, and a fast pace of work. There is evidence that the incidence of excessive body mass among nurses is increasing [38]. In our study, the mean BMI was 25.28 ± 9.24, indicating overweight. The multivariate linear regression model within the scope of the “positive mental attitude” subscale of HBI showed that the significant independent predictors on this scale are age and nursing job experience. Specifically, with age, the “positive mental attitude” has increased, and the work experience has decreased. Similar results were obtained in a study by Waksmaska et al., where statistically significant differences were shown in participants under 40 and over 50 years of age with respect to the level of health behaviors [39]. In the study by Orszulak et al., it was observed that there was an equally significant correlation between age and total HBI score, revealing a higher prevalence of each type of health behavior among older nursing staff [34]. The average work experience in our study was 19.95 ± 9.53 years. In an article by Jankowska-Polanska et al., a strong relationship was found between years of age and total HBI score. The group of respondents with more than 25 years of experience in the nursing profession had a higher health-behavior index than the nursing staff who worked for only 5 years [37]. However, in our study, we showed an inverse relationship, as the HBI subscale decreased with work experience. This may be related to job burnout, which researchers have frequently noted. However, the study by Górniak reported a significant decrease in positive psychological attitudes in respondents with more years of seniority [40]. The single factor and multivariate linear regression models within the scope of the “Proper eating habits” subscale showed that the significant predictor of health behavior among nurses was the level of education—specifically, having a bachelor’s degree. Our results showed that the higher the education level, the higher the level of health-promoting behaviors related to “Proper eating habits”. This finding is consistent with a study by Górniak et al., which found a statistically significant relationship between the level of education and the overall health behavior index [40]. Nursing staff with master’s and bachelor’s degrees reported a higher level of health-promoting behaviors than those with a secondary school or medical school degree. Similarly, Różewicz et al. [ 36] found that proper eating habits scored the highest in the group of nurses with a bachelor’s degree. Sedentary behaviors are defined as any wakeful behaviors that spend less than 1.5 metabolic equivalents while in a reclining, sitting, or lying position [41]. Several studies have measured nurses’ sedentary behavior and shown low levels of physical activity and high levels of sedentary behavior, with nurses spending up to $60\%$ of their day in a sedentary state. Most of the nurses examined did not meet the physical activity guidelines. Nurses who work rotating shifts, 12-h shifts, and/or work full-time or part-time are at increased risk of physical inactivity [42]. Our study found that nurses spent an average of 5.62 h (SD = 1.77) per day being sedentary, with a range from 1.71 to 11.29 h. These results are consistent with those of Benzo et al. who reported that nurses spent 4.56 h of each 12-h shift sitting and 5.64 h of each 12-h shift standing [43]. The correlation analysis showed a significant negative association between sedentary time and positive mental attitude, indicating that higher levels of sedentary time were associated with lower intensity of positive mental attitude health behaviors. These findings are not surprising given that prolonged sitting can have negative effects on health [44,45]. While some studies have suggested that nurses lack motivation to adopt healthier lifestyles [46], others have highlighted environmental and occupational barriers [47]. Nevertheless, promoting lifestyle changes is crucial, particularly considering the aging nursing workforce, as well as the health issues associated with shift work, long working hours, and stressful work environments. ## Limitations There are several potential limitations of this study that should be considered when interpreting the results. Firstly, the study had a limited geographic scope and there may be differences between departments of healthcare institutions. Secondly, the study was carried out during the COVID-19 pandemic, making it difficult to reach a larger group of respondents. It was also a very difficult time for nurses because they worked under difficult conditions. Thirdly, despite the assurance of anonymity, it was a self-assessment of specific health and sedentary behaviors, which may be partly subjective. Fourthly, the cross-sectional design of the study prevents us from establishing causality and temporality problems. Finally, sedentary behaviors were assessed based on the retrospective declaration of the nurses. Studies using more advanced and objective measuring devices, e.g., accelerometers, are needed. To increase the generality of the study, it should be extended and include more medical facilities in other regions. ## 6. Conclusions and Recommendations The nurses in our study presented a moderate level of health behaviors, with the highest results in terms of preventive behaviors on the HBI scale and the lowest scores in terms of health practices. Age and work experience were found to affect nurses’ positive mental attitude, while level of education influenced proper eating habits. Additionally, the study found that the average sedentary behavior was 5.62 per day. To improve health behaviors among nurses, systemic solutions such as workplace wellness programs, incentives for healthy behaviors, and education on the benefits of a healthy lifestyle are needed. Nursing leaders and employers play a pivotal role and can become advocates for system changes and be aware of the impact of social support and the hospital or unit culture on the ability of a nurse to practice health-promoting behaviors. They should create open work environments where nurses feel comfortable talking about workplace stressors and barriers to healthy behaviors, and thus support and promote nurses’ efforts to eat a healthy diet or exercise. When making staffing decisions, they should ensure that there is adequate support to provide meal and relaxation breaks for nurses. It should be noted whether canteens, coffee shops, and vending machines in medical facilities offer healthy food. Because nurses themselves are best able to identify the needed programs and barriers in the workplace to healthy living, it is a good initiative to assess needs or hold focus groups to determine how best to encourage and support a healthy lifestyle. Holistic activities that promote health permanently, not only periodically, focusing on physical activity, healthy eating, and stress reduction, must be included in the nursing workplace. Both mindfulness-based stress reduction interventions and weekly yoga classes can be helpful in improving self-care and reducing nurse burnout. They are essential and should be activities that staff members can perform during the workday or immediately before or after their shifts. A very positive example of initiatives taken in this area is the Healthy Nurses’ Nation Health campaign created by the American Nurses Association, which created an information website especially for nurses and thus supports and promotes pro-health behaviors among nurses [48]. Incorporating healthy behaviors into the nursing workplace is an investment that can not only provide immediate dividends for the nurses and staff, but long-term benefits for the organization and patients as well. In an age when it is imperative that all possible avenues for improving quality of care and decreasing healthcare costs be explored, interventions aimed at promoting the health, well-being, and performance of Polish nurses should be implemented to support nurses in making lifestyle changes and improving their health. Given the current shortage of nurses in Poland, this is of paramount importance. We hope that the findings of this study prompt further investigation in this area. ## References 1. Łukasik I.M.. Budowanie świadomości zdrowotnej w orientacji na przyszłość wyzwaniem edukacji zdrowotnej. Lub. Rocz. Pedagog. (2019.0) 37 93-106. DOI: 10.17951/lrp.2018.37.4.93-106 2. Huang H.C., Lin K.C., Wu C.S., Miao N.F., Chen M.Y.. Health-promoting behaviors benefit the mental health of cirrhotic outpatients. Qual. Life Res. (2018.0) 27 1521-1532. DOI: 10.1007/s11136-018-1818-3 3. Comprehensive Mental Health Action Plan 2013–2020–2030. (2019.0) 4. 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--- title: Chitooligosaccharides Derivatives Protect ARPE-19 Cells against Acrolein-Induced Oxidative Injury authors: - Cheng Yang - Rongrong Yang - Ming Gu - Jiejie Hao - Shixin Wang - Chunxia Li journal: Marine Drugs year: 2023 pmcid: PMC10058944 doi: 10.3390/md21030137 license: CC BY 4.0 --- # Chitooligosaccharides Derivatives Protect ARPE-19 Cells against Acrolein-Induced Oxidative Injury ## Abstract Age-related macular degeneration (AMD) is the leading cause of vision loss among the elderly. The progression of AMD is closely related to oxidative stress in the retinal pigment epithelium (RPE). Here, a series of chitosan oligosaccharides (COSs) and N-acetylated derivatives (NACOSs) were prepared, and their protective effects on an acrolein-induced oxidative stress model of ARPE-19 were explored using the MTT assay. The results showed that COSs and NACOs alleviated APRE-19 cell damage induced by acrolein in a concentration-dependent manner. Among these, chitopentaose (COS–5) and its N-acetylated derivative (N–5) showed the best protective activity. Pretreatment with COS–5 or N–5 could reduce intracellular and mitochondrial reactive oxygen species (ROS) production induced by acrolein, increase mitochondrial membrane potential, GSH level, and the enzymatic activity of SOD and GSH-Px. Further study indicated that N–5 increased the level of nuclear Nrf2 and the expression of downstream antioxidant enzymes. This study revealed that COSs and NACOSs reduced the degeneration and apoptosis of retinal pigment epithelial cells by enhancing antioxidant capacity, suggesting that they have the potential to be developed into novel protective agents for AMD treatment and prevention. ## 1. Introduction Age-related macular degeneration (AMD) is one of the main causes of irreversible central visual loss in the elderly worldwide [1,2]. In 2020, the number of AMD patients worldwide was 19.6 million, and this number was predicted to be 288 million in 2040 [1,3,4]. According to the symptoms, AMD can be divided into dry and wet forms with $80\%$ and $20\%$ prevalence, respectively [5]. Current treatments for wet AMD include laser therapy and VEGF antibody injection (such as Eylea) [6], while there is no preventive therapy for dry AMD [7]. Therefore, it is necessary to develop effective agents to prevent or cure dry AMD. Numerous studies have indicated that AMD pathogenesis was related with chronic oxidative stress and the inflammation of retinal pigment epithelial (RPE) cells, which could lead to the eventual degeneration of the RPE [8,9,10,11]. Jin et al. [ 12] suggested that retinal pigment epithelium cell apoptosis was induced by ultraviolet and hydrogen peroxide via AMPK signaling. Melissa officinalis L. extracts and resveratrol were reported to improve cell viability and decrease reactive oxygen species (ROS) generation in RPE cells to prevent AMD [10,13]. These results demonstrated that the inhibition of RPE cell damage induced by ROS could prevent the process of AMD [14]. Therefore, antioxidation could be an effective strategy to protect RPE cells for the amelioration of early AMD. Chitin is extracted mainly from the shells of crabs, shrimps and insects and is one of the most abundant natural biopolymers [15,16,17]. Chitosan oligosaccharides (COSs) are the degraded product of chitin or chitosan and consist of glucosamine linked by β-1,4-glycosidic bonds, possess various biological effects, including anti-inflammatory, antimicrobial, immunomodulatory, antioxidant, and anticancer activities [18,19,20,21]. Fang demonstrated that COS attenuated oxidative-stress related retinal degeneration in a dose-dependent manner in a rat model [22]. Xu found that COSs protected against Cu(II)-induced neurotoxicity in primary cortical neurons by interfering with an increase in intracellular reactive oxygen species (ROS) [23]. Our previous study indicated that peracetylated chitosan oligosaccharide (PACOs) pretreatment significantly reduced lactate dehydrogenase release and reactive oxygen species production in PC12 cells [24]. In addition, Guo’s group indicated that the antioxidant properties of chitosan were inversely related to its molecular weight (Mw) [25]. We performed a preliminary screening of structurally related compounds, and COSs and NACOs showed excellent antioxidant activity with the potential to prevent AMD. In the present study, we investigated the effect of a series of chitosan oligosaccharides and their N-acetylated derivatives on RPE cell damage and explored the possible mechanisms of action. The results showed that chitosan oligosaccharides had an excellent capacity for protecting RPE cells from acrolein-induced oxidative stress. ## 2.1. Characterization of Chitooligosaccharides and N-Acetylated Chitooligosaccharides According to the previous method, chitooligosaccharides (COSs) and N-acetylated chitooligosaccharides (NACOs) were prepared via enzymatic hydrolysis [24] and acetylated modification [26]. The crude products were isolated and purified to provide monomers with different degree of polymerization (Figure 1A). NACOs were purified by column chromatography using graphitized carbon black as the stationary phase and ethanol–water as the mobile phases. This purification method was simple and efficient with the elimination of the tedious operation process of desalting, compared with gel exclusion and ion exchange purification methods [27]. The purity of these compounds was analyzed via HPLC (LC-10AD, Shimadzu, Kyoto, Japan) [28,29]. As shown in Figure 1B, the purity of COS (COS–2~6) and NACO (N–2~6) monomers was above $95\%$. The structures of COSs and NACOSs were characterized using a quadrupole time of flight (Q-TOF) mass spectrometer, and nuclear magnetic resonance (NMR) and Fourier-transform infrared spectroscopy (FT-IR) analysis (Figure 1C–E). The Q-TOF MS analysis (positive ion mode) of COSs and NACOs samples are shown in Figure 1C and Table 1. For the FT-IR spectra (Figure 1D), the bands at 3370 cm−1, 2876 cm−1, and 1073 cm−1 were corresponded to stretching vibrations of O-H, C-H and C-O, respectively. The spectra of N-acetyl chitosan oligosaccharides showed the characteristic absorptions of 1649 cm−1, 1549 cm−1 and 1314 cm−1, which were attributed to amide I, II and III bands of amide, respectively [30]. Moreover, there was no 1735 cm−1 band (-C(=O)O-) in the N-acetylated chitosan oligosaccharide, indicating no acetylation on the OH groups of COSs. The structures of COSs and NACOSs were also characterized via NMR. Taking COS–3 and N–3 as examples, the 13C NMR signals in spectra (Figure 1E) were assigned in Table 2. Compared to COS–3, acetyl signal peaks appeared in the 13C NMR spectrum of N–3, with 174.8 ppm attributed to C=O, and peaks at 22.6~22.3 ppm attributed to CH3 of acetyls. ## 2.2. Protective Effect of COSs and NACOs against Acrolein-Induced Cell Death The cytotoxicity of COS and NACO monomers (DP 2, 3, 4, 5, 6) was tested via MTT assay in ARPE-19 cells. After 24 h of incubation with 1 mM COSs or NACOs, the MTT test showed that both COSs and NACOs exhibited no significant cytotoxicity (Figure S1A). In addition, the effect of COSs and NACOs on the viability of ARPE-19 cells was tested with different concentrations (200, 400, 800 μM). It showed that COSs and NACOs did not affect cell proliferation. ( Figure S2). Acrolein, a major component of the gas phase of cigarette smoke and also a product of lipid peroxidation in vivo, has been shown to be a mitochondrial toxicant related to mitochondrial dysfunction [31]. Therefore, acrolein-induced cellular oxidative mitochondrial dysfunction in retinal pigment epithelial (RPE) cells had been used as a cellular model to evaluate antioxidants and mitochondrial protecting agents [32,33,34]. Here, AREP-19 cells were pretreated with different concentrations of COSs or NACOs (200, 400 and 800 μM) for 48 h, and then treated with 75 μM acrolein for 24 h, and cell viability was measured using the MTT test. As shown in Figure 2, the cells exposed to 75 µM acrolein showed a significant decrease in cell viability (about $50\%$) compared to the untreated control group. However, after pretreatment with COSs or NACOs at 200, 400, and 800 μM for 48 h before acrolein exposure, the cell viability increased significantly. Furthermore, COSs and NACOs exhibited similar protective activity which was dose-dependent. In addition, we also prepared peracetylated chitosan oligosaccharides (PACOs) [24], but PACOs had a certain cytotoxicity to ARPE-19 (Figure S1B). Glucosamine pentamer (COS–5) and N-acetylated chitopentaose (N–5) showed the highest protective activity, which indicated that the pentaose skeleton may be the suitable structure for binding to the receptors or targets, such as heparin core pentasaccharide, for anticoagulant activity [35]. ## 2.3. Protective Effect of COS–5 and N–5 against Acrolein-Induced Oxidative Stress The involvement of oxidative-stress-triggered apoptosis in retinal endothelial cells was considered as the leading cause of AMD [2,36,37]. In this study, RPE cells were stimulated by acrolein to induce oxidative stress. It was evaluated for the capacity of COS–5 and N–5 to prevent oxidative-stress-induced cell death and the imbalance of the antioxidant system. Initially, the effects of COS–5 and N–5 on acrolein-induced ROS generation (Figure S3) and MMP decline (Figure S4) in ARPE-19 cells were evaluated at different concentrations (200, 400, 800 μM). The results showed that there were no significant differences between 400 and 800 μM. Thus, all subsequent experiments were performed with the 400 μM dose. Then, intracellular and mitochondria ROS accumulation, GSH level, and GPx and SOD activities were measured (Figure 3). ROS are natural by-products of aerobic respiration. ROS can be controlled by various cellular antioxidant compounds and enzymes, and their overproduction would lead to cell death [38]. Compared with the control, intracellular and mitochondria ROS levels were significantly increased to about $270\%$ and $276\%$ after acrolein exposure, respectively (Figure 3A,B). However, pretreatment with COS–5 or N–5 at the concentration of 400 μM reduced acrolein-induced ROS production significantly. GSH is one of the most important endogenous small molecule antioxidants. As shown in Figure 3C, the intracellular GSH level was decreased significantly after acrolein exposure (about $49\%$). Pretreatment with COS–5 or N–5 could successfully inhibit the decrease in GSH content induced by acrolein, which increased by $39\%$ and $41\%$ ($p \leq 0.01$), respectively. GSH peroxidase (GPx) and SOD activity was decreased to $30\%$ and $55\%$ after acrolein treatment (Figure 3D,E), respectively. The activities of antioxidant enzymes (GPx and SOD) significantly enhanced after COS–5 or N–5 treatments. These results indicated that the excellent antioxidant activity of COSs and NACOs played a critical role in protecting cells against acrolein-induced oxidative damage. In this study, we found that chitooligosaccharides and their derivatives could protect APRE-19 cells from acrolein oxidative damage by improving their antioxidant capacities. However, without acrolein exposure, COS–5 or N–5 pretreatment did not affect these antioxidant biomarkers when compared to control cells (Figure 3). This is an interesting phenomenon. ROS at a low level play important roles as signaling molecules in normal physiology. Navdeep et al. [ 39] found that the mitochondrial complex III ROS was essential for T cell activation both in vitro and in vivo. It is a huge advantage that the antioxidant activities of N–5 and COS–5 were selective, and they did not affect ROS balance and ROS-mediated signaling pathways in normal cells. The data above showed that COS–5 or N–5 has the potential to be studied further and developed into a novel therapeutic agent for the treatment of AMD. ## 2.4. COS–5 and N–5 Improved Mitochondrial Function in Acrolein-Treated ARPE-19 Cells Mitochondria are the main sites of oxidant generation, and are easily affected by oxidants, resulting in mitochondrial dysfunction and apoptosis. We examined mitochondrial function by assaying cellular and mitochondrial ROS production, and mitochondrial membrane potential MMP. The results of cellular (Figure 3A) and mitochondrial ROS production is shown in Figure 3B. MMP is an important index of mitochondrial function, which could be evaluated using a JC-1 fluorescent probe. As shown in Figure 4, MMP was decreased to about $45\%$ by acrolein (75 μM, 24 h), which was consistent with previous reported results [32]. MMP was significantly increased after pretreatment with COS–5 or N–5. Similarly, COS–5 or N–5 did not affect mitochondrial function of normal ARPE-19 cells. Zhou [40] found that COS could entered into cells in a dose-dependent and time-dependent manner, and COS was localized preferentially in the mitochondria. However, it was not reported whether NACOSs could enter into cells. Here, the localization of N–5 in ARPE-19 cells was detected by confocal microscopy using the FITC-labeled N–5 (N5-FITC). After treatment with N5-FITC (100 μM) for 3 h, a green fluorescence was observed around the mitochondria, while nearly no fluorescence was found in control cells (Figure 5), suggesting that N–5 could enter into ARPE-19 cells and localize in the mitochondria. These data indicated that the intracellular localization of chitooligosaccharides was not affected by the introduction of acetyl group into amino. Taken together, the results demonstrated that N–5 could localize in the mitochondria and protect ARPE-19 cells against mitochondrial dysfunction and apoptosis induced by oxidative stress. ## 2.5. N–5 Promoted Nrf2 Nuclear Translocation and Increased Antioxidant Enzyme Expression Nuclear transcription factor Nrf2 plays a key role in regulating the expression of phase II detoxification enzymes and antioxidant enzymes. Under normal physiological conditions, Nrf2 was present in the cytoplasm coupled with the negative regulatory protein Kelch Ech-associated protein 1 (Keap1), which interacted with Nrf2 and acted as an adaptor protein, maintaining Nrf2 at a low level and allowing it to be continuously degraded by the proteasome in a ubiquitin-mediated process [41]. When cells were exposed to oxidative stress, Nrf2 in the cytoplasm was released from the negative regulatory protein Keap-1 and translocated to the nucleus, then bonded to an antioxidant response element (ARE). Then, a variety of genes, including glutathione reductase (GR), heme oxygenase-1 (HO-1), catalase (CAT), NAD(P)H Quinone oxidoreductase-1 (NQO-1), and γ-glutamyl cysteine ligase (GCL) were regulated to resist the cell damage caused by oxidative stress [42]. We determined the effect of oxidative stress induced by acrolein on Nrf2 nuclear translocation in the ARPE-19 cell. Due to the similar activity of N–5 and COS–5, as well as the easy preparation of N–5, we focused on N–5 in subsequent experiments. As Figure 6A,B shows, the level of Nrf2 protein in the nucleus significantly decreased after acrolein damage, similar to a published report [43], while pretreatment with N–5 significantly increased the level of nuclear Nrf2, indicating that N–5 could promote Nrf2 nuclear translocation. Meanwhile, we detected the effect of N–5 on the transcription of genes downstream of Nrf2. The mRNA expression of HO-1 and NQO-1 were performed via qRT-PCR. As shown in Figure 6C,D, the mRNA levels of HO-1 and NQO-1 were significantly reduced in ARPE-19 cells treated with acrolein, and upregulated significantly when pretreated with N–5. These results suggested that N–5 could activate the Nrf2-ARE pathway in ARPE-19 cells, enhance Nrf2 protein nuclear translocation and upregulate the expression of phase II metabolizing enzymes (such as HO-1 and NQO1) to alleviate acrolein-induced oxidative injury. Oxidative damage of RPE cells was a major factor in the pathogenesis of AMD, and protecting RPE from oxidative damage and death has become a trend in the treatment and prevention of AMD disease. COS and their derivatives were well-known for their free radical scavenging potential by interrupting radical chain reactions to inhibit oxidative damage [44]. The antioxidant activity of chitosan increased with decreasing Mw [45]. Li et al. [ 46] reported that COS had strong antioxidant activities such as hydroxyl and superoxide radical scavenging activity and reducing power. Qu [47] found that chitooligosaccharides had a certain radical scavenging activity in vitro, and they protected mice from oxidative stress, increased the activity of SOD, catalase, and GPx significantly in mice on a high-fat diet. However, there are fewer reports on N-acetylated oligochitosan with the same repeated unit as chitin. Several high-purity chitosan oligosaccharides and their N-acetylated derivatives were prepared in this study, and their protective effect on retinal pigment epithelial cells was studied. Similar to other antioxidants such as curcumin analogs [32], luteolin [48], naringenin [49], or tocopherol [31], chitooligosaccharide monomers also had good protective activity, and COS–5 and N–5 showed the best activities. Further studies found that acetyl group introduction did not affect the protective effect of chitooligosaccharides. Subsequent study found that N–5 could enhance the antioxidant capacity of ARPE-19 cells, via reducing ROS production, increasing the GSH level, and enhancing SOD/GPx enzyme activity. In addition, N–5 could localize in mitochondria, increase MMP, reduce mitochondrial dysfunction and cellular damage, and enhance Nrf2 nuclear translocation and the transcription of downstream antioxidant enzyme (HO-1 and NQO1). Interestingly, N–5-mediated antioxidant properties were selective and associated with the oxidative stress state. N–5 does not inhibit ROS production and ROS-mediated signaling pathways in the normal cells. The above results indicated that N-acetylated chitooligosaccharides may have a potential application in anti-AMD degenerative diseases. ## 3.1. Materials Chitosan (deacetylation > $95\%$) was purchased from Jinhu Crust Product Corp (zi bo, Shandong, China). Chitosanase fermented by Renibacter ium sp. QD1 was obtained from the Ocean University of China. Acrolein was purchased from Xiya Reagent (Chengdu, China). MitoTracker Red CM-H2Xros and Trizol Reagent were purchased from Invitrogen (Foster City, CA, USA). PrimeScript RT-PCR Kit was purchased from TaKaRa (Dalian, China). The reduced glutathione (GSH) assay kit was purchased from the Nanjing Jiancheng Bioengineering Institute (Nanjing, China). The MTT cell proliferation and cytotoxicity detection kits, phenyl methane sulfonyl fluoride (PMSF), reactive oxygen species (ROS) detection kit, mitochondrial membrane potential (MMP) detection kit, BCA protein assay kit, CuZn/Mn-SOD assay kit (WST-8), cellular glutathione peroxidase (GPx) assay kit, Nuclear and Cytoplasmic Protein Extraction kit, PVDF membranes, and BCIP/NBT Alkaline Phosphatase Color Development kit were purchased from the Beyotime Institute of Biotechnology (Shanghai, China). Nrf2 XP Rabbit mAb and Histone H3 XP Rabbit mAb were purchased from Cell signaling technology (Boston, MA, USA). All other reagents were obtained from Sigma-Aldrich (Saint Louis, MO, USA), unless otherwise stated. ## 3.2. Chitosan Oligosaccharide (COSs) Preparation and Purification The COSs were prepared via the enzymatic hydrolysis of chitosan and purified with gel filtration chromatography according to a previously reported method [24]. In brief, chitosan (10 g) was added to 80 mL of distilled water, then 1.5 mL of chitosanase solution (10 U/mL) was added. The mixture was stirred at 50 °C for 24 h, and the pH of the reaction mixture was adjusted to 5~6 with HCl solution (4 mol/L) during the hydrolysis process. The hydrolysate was adjusted to pH 8~9 with NaOH solution (1 mol/L) and filtered to remove insoluble parts. The filtrate was concentrated and precipitated by adding a four-fold volume of ethanol at 4 °C overnight. The precipitate was collected via centrifugation for 15 min at 8000 rpm, and then lyophilized to yield powdered products, and identified as a COS mixture. The COS mixture (200 mg) was dissolved in 2 mL of 0.1 M NH4HCO3, and then filtered with a microporous membrane (0.22 μm) to obtain a clear solution. The filtrate was loaded on a Bio Gel P6 column (2.6 × 110 cm) that was connected to an AKTA UPC100 purification system (GE Healthcare, Fairfield, CT, USA) equipped with an online refractive index detector. The column was eluted with 0.1 M NH4HCO3 solution at a flow rate 0.5 mL/min. Eluents (8 mL/tube) were collected using a fraction collector to afford the pure dimers, trimers, tetramers, pentamers, and hexamers of the COSs. The COSs were analyzed using the high-performance liquid chromatography (HPLC), mass spectra, nuclear magnetic resonance (NMR) and Fourier-transform infrared spectroscopy (FT-IR) methods [24]. ## 3.3. N-Acetylated Chitooligosaccharide (NACOs) Preparation and Purification The NACOs were prepared via the acetylation of COSs according to a previously reported method [26]. Briefly, the dried COS mixture (1 g) and NaHCO3 (756 mg) were added to methanol–water solution (8:1; v/v, 35 mL) with stirring, and 5 mL of acetic anhydride was added dropwise at 0 °C with stirring. After stirring for 4 h at room temperature, the NACO mixture solution was filtered to remove insoluble parts and the reaction completion was monitored using TLC (n-propanol:water, 2:1, v/v). The filtrate was concentrated and lyophilized to obtain the NACO mixture powder. Then, the NACO mixture (500 mg) was dissolved in 2 mL of water, and filtered with a microporous membrane (0.22 μm). The filtrate was loaded on a graphitization of carbon black column (2.6 × 20 cm) that was connected to an AKTA UPC100 purification system (GE Healthcare, Fairfield, CT, USA). After loading the sample, the column was eluted with the following gradient of water and ethanol with a gradient of solvent B (ethanol) as follows: $0\%$ B for 3 CV (column volume), then up to $60\%$ B over 5 CV. Eluents (10 mL/tube) were collected using a fraction collector and monitored using TLC (n-propanol:water, 2:1, v/v). Pure dimers, trimers, tetramers, pentamers, and hexamers of the NACOs were pooled and lyophilized. The NACO samples were identified via HPLC chromatogram, mass spectra, nuclear magnetic resonance (NMR) and Fourier-transform infrared spectroscopy (FT-IR) analysis. ## 3.4. MTT Assay for Cell Viability The ARPE-19 (human retinal pigment epithelial) cell line was purchased from ATCC (CRL2302) and cultured in a DMEM-F12 medium supplemented with $10\%$ fetal bovine serum, $0.348\%$ sodium bicarbonate, 2 mM L-glutamine, 100 μg/mL of streptomycin, and 100 U/mL of penicillin. The cell culture was maintained at 37 °C in a humidified atmosphere of $95\%$ air and $5\%$ CO2 [50]. ARPE-19 cells were used within 10 generations, and the medium was changed every two days. COSs and NCOSs were dissolved with PBS buffer, filtered through a sterile 0.22 μm filter, and diluted with complete culture medium to different concentrations for the cell experiments. The ARPE-19 cells were seeded in 96-well plates at 5 × 104 cells per well and incubated overnight. After incubation with different concentrations of COSs or NCOSs for 48 h, the cells were treated with 75 μM acrolein for 24 h. Cell viability was measured via MTT cell proliferation and a cytotoxicity detection kit (Beyotime). After 4 h of incubation with MTT, the solubilization buffer was added to each well and incubated at 37 °C overnight. The optical densities were read at 555 nm using a SpectraMax M5 plate reader (Molecular Devices, Sunnyvale, CA, USA). ## 3.5. Antioxidant Enzyme Activities, ROS Generation, and Intracellular GSH Levels Assay The GSH level, superoxide dismutase (SOD) activity, and GPx activity were determined using commercial assay kits [51]. Briefly, cells were placed in 6-well plates at a density of 5 × 105 cells per well. After 12 h, the cells were treated for 48 h with 400 μM of COS–5 or N–5 and then for 24 h with or without 75 μM acrolein. After treatment, the cells were washed twice with PBS, and then the antioxidant enzyme activities and GSH level in the cells were detected. Moreover, the ROS levels in PRE cells and mitochondria exposed to acrolein were determined using fluorescent probe. In brief, cells were plated in 96-well plates at a density of 2.5 × 104 cells per well for 12 h. ARPE-19 cells were treated with 400 μM of COS–5 or N–5 for 48 h, and then incubated with or without 75 μM acrolein for another 24 h. The ROS level in PRE cells was determined by the 2′, 7′-dichlorofluorescein diacetate (DCFH-DA) method using a SpectraMax M5 plate reader (Molecular Devices, San Jose, CA, USA) at a 488 nm excitation wavelength and a 525 nm emission wavelength [52]. The ROS generation in mitochondria was detected using MitoTracker Red CM-H2Xros at a 579 nm excitation wavelength and a 599 nm emission wavelength. ## 3.6. Confocal Imaging ARPE-19 cells were cultured on glass-bottom cell culture dishes at a density of 2 × 104 cells per well for 12 h. The cells were incubated with 25 nM MitoTracker Red CMXROS at 37 °C for 30 min. Thereafter, the cells washed three times with PBS to remove unbound probes. Then, the cells were incubated with FITC (100 μM) or FITC-labeled N–5 (100 μM) for 3 h at 37 °C. Cellular uptake was terminated by washing the cells three times with PBS. Finally, the cells were observed under a Nikon A1 confocal microscope (Nikon Corporation, Tokyo, Japan). The green fluorescence of FITC was measured at Ex495/Em525, and the red fluorescence of MitoTracker Red CMXRos was measured at Ex578/Em599 [53]. ## 3.7. Mitochondrial Dysfunction Evaluation Mitochondrial membrane potential (MMP) was detected in live ARPE-19 cells using a cationic fluorescent indicator JC-1, according to the manufacturer’s instructions. Briefly, APRE-19 cells were seeded at a density of 2.5 × 104 cells per well in a 96-well plate. After 12 h, the cells were exposed to 400 μmol/mL of N–5 for 48 h. After treatment with 75 μmol/mL of acrolein for 24 h, the cells were treated with JC-1 for 30 min at 37 °C, washed with PBS, and observed under the fluorescence microscope. The Δψm of ARPE-19 cells in each treatment group was calculated as the fluorescence ratio (590 to 530 nm) [54]. ## 3.8. Western Blot Western blot was performed as in previously described methods [55] and each Western blot was repeated at least three times. Nuclear proteins were prepared using a Nuclear and Cytoplasmic Protein Extraction Kit, and nuclear Nrf2 was analyzed using Western blot. Briefly, the lysates were homogenized and centrifuged at 13,000 ×g for 15 min at 4 °C. The supernatants were collected, and the protein concentrations were determined using the BCA Protein Assay kit. Equal amounts (20 μg) of each protein sample were loaded on $10\%$ SDS-PAGE gels, electrophoresed, transferred to PVDF membranes, and blocked with $5\%$ non-fat milk. The membranes were incubated with anti-Nrf2 (1:1000) and anti-histone H3 (1:1000) at 4 °C overnight, and then incubated with anti-mouse secondary antibodies at room temperature for 1 h. Protein bands were visualized using a BCIP/NBT Alkaline Phosphatase Color Development Kit. Signals were quantified using ImageJ software (Version 1.52b, NIH, Baltimore, MD, USA), and defined as the ratio of target protein to histone H3. ## 3.9. Real-Time PCR Real-time PCR was performed using a previously described method [56]. Total RNA was extracted from the cells using Trizol reagent according to the manufacturer’s protocol. Reverse transcription was performed using the PrimeScript RT-PCR Kit followed by semiquantitative real-time PCR using specific primers. The primer sequences are listed in Table 3. ## 3.10. Statistical Analysis All quantitative experiments were repeated at least 3 times independently. Data are presented as mean ± SD. Data were analyzed by one-way analysis of variance (ANOVA) with Tukey’s multiple comparison post hoc test using GraphPad Prism 8.0 Statistics Software (Graphpad Software, Inc., La Jolla, CA, USA). A p value of < 0.05 was considered statistically significant. ## 4. Conclusions In conclusion, our study demonstrated that chitosan oligosaccharides (COSs) and their N-acetylated chitooligosaccharides (NACOs) exhibited excellent protection effects on acrolein-induced ARPE-19 cell damage. 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--- title: Phytochemical Profile, Antioxidant, Antimicrobial and Cytoprotective Effects of Cornelian Cherry (Cornus mas L.) Fruit Extracts authors: - Mara Aurori - Mihaela Niculae - Daniela Hanganu - Emoke Pall - Mihai Cenariu - Dan Cristian Vodnar - Andrea Bunea - Nicodim Fiţ - Sanda Andrei journal: Pharmaceuticals year: 2023 pmcid: PMC10058959 doi: 10.3390/ph16030420 license: CC BY 4.0 --- # Phytochemical Profile, Antioxidant, Antimicrobial and Cytoprotective Effects of Cornelian Cherry (Cornus mas L.) Fruit Extracts ## Abstract Cornus mas L. is characterized by an increased quantity of bioactive compounds, namely polyphenols, monoterpenes, organic acids, vitamin C and lipophilic compounds such as carotenoids, being anciently used in the treatment of various diseases. This paper’s objectives were to characterize the phytochemical profile of Cornus mas L. fruits and to evaluate the in vitro antioxidant, antimicrobial and cytoprotective effects on renal cells exposed to gentamicin. As such, two ethanolic extracts were obtained. The resulting extracts were used to assess the total polyphenols, flavonoids and carotenoids through spectral and chromatographic methods. The antioxidant capacity was assessed using DPPH and FRAP assays. Due to the high content of phenolic compounds analyzed in fruits and the results obtained regarding antioxidant capacity, we decided to further use the ethanolic extract to investigate the in vitro antimicrobial and cytoprotective effects on renal cells stressed with gentamicin. The antimicrobial activity was assessed using agar well diffusion and broth microdilution methods, with great results regarding Pseudomonas aeruginosa. The cytotoxic activity was assessed using MTT and Annexin-V assays. According to the findings, extract-treated cells had a higher cell viability. However, at high concentrations, viability was shown to decline, most likely due to the extract and gentamicin’s additive effects. ## 1. Introduction Recently, it has been considered that nutrition plays a crucial role in human health. Therefore, interest in living a healthy way of life exists, by having a healthy diet and consuming food supplements [1,2]. Most people use plant-derived drugs as the first line in the treatment of various diseases [3]. There are studies that have proven the effectiveness of plant-derived drugs against certain illnesses, namely degenerative diseases, atherosclerosis, diabetes, gastrointestinal disorders and cancer, outlining the importance of alternative medicine compared to synthetic drugs [4,5,6,7,8,9,10,11,12]. Thus, the search for biologically active compounds from plants implies a new challenge, with the aim of obtaining new commercial products. It might be considered such plants to be berries, known for their increased quantity of sugars and phytochemical compounds [13]. Specifically, cranberries, blueberries, strawberries or cherries, with a particular interest in cornelian cherry, where recent studies suggest that it has great potential for alternative medicine applicabilities [14,15]. European cornelian cherry (Cornus mas L.), widely known as dogwood, is a flowering medicinal plant that belongs to the Cornaceae family. It arises from the foothills of the Caucasus Mountains and spreads over southeastern Europe, more specifically over Turkey, Bulgaria, Romania and Italy [16,17,18]. Cornelian cherry is a deciduous shrub with a height ranging from 5 to 12 m. It has dark brown branches, greenish twigs and early-blooming yellow flowers. The fruits have an oval form that resembles an olive, are firm to the touch, and only have one stone within. They bloom from September to October [16,18]. Their color is initially yellow, but as the fruits ripen, they turn crimson. Ripen fruits are edible, having an acidic and sweet flavor. Depending on the plant genotype and culture conditions, the fruit of Cornus mas L. weighs between 1 and 10 g and 5.7–$11\%$ of the weight is made up of the stone [17,19]. Cornus mas L. thrives in unaltered natural circumstances without pesticides, being therefore appropriate for cultivation in accordance with the principles of organic agriculture [20]. It was established by previous investigations that Cornus mas L. is a rich source of biologically active organic compounds. Therefore, from a phytochemical perspective, cornelian cherry holds an increased quantity of polyphenols, monoterpenes, organic acids and vitamin C. Anthocyanins, cinnamic acids, flavonoids, benzoic acids, catechins and tannins are the primary polyphenols, having the highest preponderance of $37.76\%$. Organic acids and monoterpenes, particularly iridoids, are present in roughly equal amounts ($25.9\%$ and $26.3\%$, respectively). The main organic acids identified in Cornus mas L. fruits include tartaric acid, malic acid, citric acid, gallic acid, loganin and chlorogenic acid. Moreover, these fruits contain $10.7\%$ vitamin C. However, the amount of nutrients might differ based on a number of variables, including the geographical region, the cultivar and the level of ripeness of the fruit [17,19,21,22]. Cornelian cherry has traditionally been used both for food consumption and as an ornamental plant. It is cultivated in some countries for the production of marmalade, compote, syrup, juice, yogurt, liqueur and wine [16,23,24]. In addition, Cornus mas L. fruits are also utilized in the cosmetic industry [21]. For ornamental purposes, cornelian cherry trees are planted and grown in households, public gardens and parks due to its lovely yellow blooms [25]. In folk medicine, cornelian cherry fruits have historically been used to cure a variety of illnesses. The Caucasus, Central Asia, Turkey, Azerbaijan, Iran, Greece and Slovakia were the main regions where they were employed. Thus, the ripe fruits were used to treat sore throats, gastrointestinal disorders, measles, chicken pox, anemia, rickets, fever, inflammation, skin disorders, tuberculosis, malaria, cancer, thermic fever, wounds, liver diseases such as hepatitis A and kidney diseases such as pyelonephritis and renal calculi [16,21]. In recent years, the effects of Cornus mas L. fruits have been the subject of numerous studies, which have revealed that they have anti-inflammatory, antibacterial, antioxidant, antidiabetic, antiatherosclerotic, antiproliferative, antiparasitic, antihyperlipidemic, nephroprotective, hepatoprotective and neuroprotective effects [18,26,27,28,29,30,31,32,33,34,35,36]. Due to the fact that Cornus mas L. fruits contain a number of significant active components and due to recent epidemiological studies that have suggested that some plant extracts may be advantageous for their capacity to prevent the onset or slow the evolution of a number of illnesses, we believe it is vital to thoroughly investigate the profile of biologically active organic compounds and their effects at a cellular level. Therefore, the current study intends to identify and quantify the biologically active chemical compounds from cornelian cherry fruits as well as investigate the in vitro antioxidant, antimicrobial and cytoprotective effects on primary renal cells stressed with gentamicin, the latter of which has received very little research and may help in the development of new therapeutic agents to prevent kidney damage. ## 2.1. Total Content of Polyphenols, Flavonoids and Carotenoids of Cornus mas L. Fruit extracts Initially, one of our objectives was to detect and evaluate the bioactive constituents of cornelian cherry cultivars from Cluj county, Romania, which may have antioxidant, antimicrobial and cytoprotective properties. The results regarding total phenolic content, total flavonoids and total carotenoid pigments are provided in Table 1. As such, the analysis of the ethanolic extracts of Cornus mas L. fruits revealed that the total polyphenolic content was 0.872 ± 0.0035 mg GAE/mL and the total flavonoid content was 139.14 ± 2.10 µg/mL. Total carotenoids were found to be 3.8 ± 0.0002 µg/g, resulting from the second type of extracts (ethyl ether re-extraction of the ethanolic extracts of Cornus mas L. fruits). ## 2.2. Identification of Phenolic Compounds by HPLC-DAD-ESI-MS The results regarding HPLC-DAD-ESI+ profile of phenolic composition are shown in Figure 1 and Table 2. The retention time, UV-Vis spectrum and each individual peak’s spectral mass were compared to published data in order to identify the phenolic compounds. As a result, 13 compounds belonging to four different classes were identified. Thus, phenolic acids were represented by gallic acid glucoside, chlorogenic acid and caffeic acid. The class of anthocyanins was represented by coumaroyl-glucoside, Cy 3-O-galactoside, Cy 3-O-robinobioside, Pg 3-O-galactoside and Pg 3-O-robinobioside, being the most numerous class. Loganin and sweroside were also discovered, being part of the iridoid class, while rutin, K 3-O-galactoside and a procyanidin dimer were associated with the flavonol class. Using the calculation method mentioned in the Materials and Methods section, the highest concentration of GAE was found in gallic acid glucoside (248.51 μg/mL), a hydroxybenzoic acid, followed by a procyanidin dimer (195.82 μg/mL) and loganin (111.47 μg/mL), with Cy3-O-(coumaroyl-glucoside) having the lowest concentration (6.43 μg/mL). In addition, the total phenolic content was 0.847 mg GAE/mL of extract. This result was comparable to the spectrophotometric assay of these compounds by the Folin–Ciocalteu method (0.847 mg GAE/mL vs. 0.872 mg GAE/mL). ## 2.3. Antioxidant Capacity Using the Radical Scavenging Activity (DPPH) assay to measure the antioxidant capacity, a final IC50 value of 0.466 mg/mL was obtained. Simultaneously, by employing the Ferric Reducing Antioxidant Power (FRAP) method, a value of 23.09 was yielded, which was expressed as µmol Trolox/mL extract. ## 2.4. Antimicrobial Activity The results of Cornus mas L. extract in vitro antimicrobial properties assessment are presented in Table 3 (zone of inhibition) and Table 4 (MIC index). Cornus mas L. extract displayed in vitro antimicrobial potential against all tested bacterial strains (Table 3). The highest effect was recorded towards Enterococcus faecalis and Pseudomonas aeruginosa with diameters of the inhibition zone of 22.33 ± 0.47 mm. These results are particularly of interest since both bacteria are well known for their elevated level of antimicrobial resistance. In fact, compared to positive controls (amoxicillin–clavulanic acid for Enterococcus faecalis and gentamicin for Pseudomonas aeruginosa), the inhibition zone diameters were found significantly higher ($p \leq 0.05$). Further evaluation towards clinical strains isolated from human and animal cases is intended. The extract presented inhibitory activity also against Staphylococcus aureus reference strains; as expected, the values were significantly higher ($p \leq 0.05$) in the case of MSSA compared to MRSA. The diameters of the inhibition zones were comparable to those obtained for gentamicin ($p \leq 0.05$) but significantly lower ($p \leq 0.05$) than those of amoxicillin–clavulanic acid. The lowest inhibitory effect was recorded towards Bacillus cereus (inhibition zone of 17 ± 0.00 mm). The MIC and MBC values obtained using a broth microdilution method are presented in Table 4. Based on the resulting MIC index, the extract was found to exhibit bactericidal activity against all tested bacterial strains (MBC/MIC ≤ 4). ## 2.5.1. Evaluation of Cell Viability by MTT Assay MTT was used to assess the cytoprotective activity of the Cornus mas L. extract. The culture cells were initially divided into the following four groups: Control (C) group, which contained untreated cells; Gentamicin (G) group, which received antibiotic treatment in three different concentrations (G1 = 100 μg/μL, G2 = 150 μg/μL and G3 = 200 μg/μL); Cornus mas (CM) group, which received extract treatment in three distinct amounts (CM1 = 130 μg/μL, CM2 = 195 μg/μL and CM3 = 260 μg/μL) and Cornus mas + Gentamicin (GCM) group, which received treatment with a combination of both. According to the results of the MTT assay, the G group’s cell viability was significantly lower than the C group’s at all concentrations ($p \leq 0.05$). The first concentration of gentamicin, which had the lowest viability, was found to be the most nephrotoxic, registering a percentage of $63.03\%$. Thus, this concentration was considered for future evaluations. Additionally, the CM group showed a statistically significant decline in cell viability in comparison to the C group, at all concentrations ($p \leq 0.05$). It was noticeable that the highest concentration (260 μg/μL) had the lowest viability ($71.36\%$). Nevertheless, compared to the gentamicin-treated cells, a greater viability was observed at all concentrations. Lastly, in the GCM group, it was possible to observe a decrease in cell viability as the extract’s concentration increased. This was likely caused by the extract and gentamicin’s combined cytotoxic effects at high doses. Moreover, the cell viability in this group was higher in comparison to the cells treated with gentamicin alone ($p \leq 0.05$). However, the cell viability was similar to that obtained in cells treated just with Cornus mas L. extract, there being no statistical difference between the two groups at all concentrations ($p \leq 0.05$). Figure 2 displays these findings graphically. ## 2.5.2. Evaluation of Cell Apoptotic Rate by Annexin-V FITC Assay Annexin-V FITC was the following test used in measuring the cytoprotective effect of Cornus mas L. extract in gentamicin kidney injury. Apoptotic measurements were performed on identical cell groups as presented in the MTT assay (C, G, CM1-CM3, GCM1-GCM3). Following fluorochrome staining and the cells’ affinity for PI and Annexin-V, flow-cytometry results were revealed. As such, in comparison to the C group, a statistically significant decrease in cell viability was observed in the G group ($63.83\%$ vs. $99.9\%$; $p \leq 0.0001$) and CM group ($77.4\%$, $80.9\%$, $70.1\%$ vs. $99.9\%$; $p \leq 0.0001$). It was noticeable that the second concentration of the CM group registered the highest viability, whereas the last concentration recorded the lowest level of viable cells. These results can be connected with those obtained in the MTT assay because the percentage of viable cells was shown to decline at high concentrations. Furthermore, by comparing the GCM group to the CM group, there was no statistical difference in cell viability at 130 µg/µL and 195 µg/µL concentrations ($77.1\%$, $80.5\%$ vs. $77.4\%$, $80.9\%$; $p \leq 0.05$), manifesting a protective effect in a manner similar to the MTT assay. Importantly, these two concentrations had a significantly higher percentage of viable cells when compared to the G group ($77.1\%$, $80.5\%$ vs. $63.83\%$; $p \leq 0.01$), outlining the protective effect of Cornus mas L. extract. In contrast, a significant decline in cell viability was observed at the highest concentration (260 µg/µL), compared to the CM group ($62.1\%$ vs. $70.1\%$; $p \leq 0.05$). Moreover, the percentage of viable cells of this concentration was significantly lower compared to the percentage of gentamicin-treated cells ($62.1\%$ vs. $63.83\%$; $p \leq 0.05$), probably due to the cumulative cytotoxic effect of the extract at high concentrations with that of gentamicin. When analyzing early apoptosis, an increase in the percentage of early apoptotic cells was observed in the G group ($1.8\%$ vs. control; $p \leq 0.0001$) and CM group ($0.4\%$, $1.1\%$, $0.9\%$ vs. control; $p \leq 0.0001$). In comparison to the CM group, the GCM group registered a similar increase in early apoptosis at the first two concentrations, namely 130 µg/µL and 195 µg/µL ($1.3\%$, $1.1\%$ vs. $0.4\%$, $1.1\%$; $p \leq 0.05$). Moreover, no significant difference was observed when compared to the G group (vs. $1.8\%$; $p \leq 0.05$). However, there was a drastic increase in the amount of early apoptotic cells at the highest concentration (260 µg/µL) of this group in comparison to the CM group ($11.6\%$ vs. $0.9\%$; $p \leq 0.05$) and the G group (vs. $1.8\%$; $p \leq 0.01$). As such, this concentration registered the highest percentage of apoptotic cells. Regarding tardive apoptosis, the G group registered a greater percentage of late apoptotic cells when compared to the C group ($3.5\%$ vs. $0\%$; $p \leq 0.01$). In addition, the CM group recorded a significantly higher number of tardive apoptotic cells in comparison to control ($1.8\%$, $2.4\%$, $3.7\%$ vs. $0\%$; $p \leq 0.05$). Furthermore, by analyzing the GCM group, a significantly greater decrease in these cells was observed at 130 µg/µL and 195 µg/µL concentrations, in comparison to the G group ($0.2\%$, $1\%$ vs. $3.5\%$; $p \leq 0.0001$). The first concentration (130 µg/µL) also recorded a significantly lower percentage of tardive apoptosis compared to the CM group ($0.2\%$ vs. $1.8\%$; $p \leq 0.0001$), whereas there was no significant difference between the GCM and CM groups at the second concentration, namely 195 µg/µL ($1\%$ vs. $2.4\%$; $p \leq 0.05$). However, the highest concentration of the GCM group recorded the greatest level of late apoptotic cells, namely $7.4\%$. This was significantly increased when compared to the CM group ($p \leq 0.01$) and G group ($p \leq 0.0001$). Overall, necrotic cells registered a higher number in all groups when compared to early and late apoptosis. Thus, in comparison to control, there was a drastic increase in the percentage of necrotic cells in the G group ($30.87\%$ vs. $0.1\%$; $p \leq 0.0001$) and CM group ($20.4\%$, $15.6\%$, $25.3\%$ vs. $0.1\%$; $p \leq 0.0001$). The second concentration of the CM group recorded the lowest amount of necrotic cells, while the last concentration registered the highest percentage of necrosis, following the G group. Importantly, it was noticeable that the GCM group had a significantly lower percentage of necrosis in comparison to the G group ($21.4\%$, $17.4\%$, $18.9\%$ vs. $30.87\%$; $p \leq 0.001$), outlining again the importance of Cornus mas L. extract against gentamicin stress. Figure 3, Figure 4 and Figure 5 show a detailed replication of these outcomes. ## 3. Discussions Phytochemical profile of Cornus mas L. is presented in this paper by assessing the total phenolic, flavonoid, and carotene content of the extracts. As a result, values of 0.872 ± 0.0035 mg GAE/mL for total polyphenols, 139.14 ± 2.100 μg/mL for flavonoids and 3.8 ± 0.0002 μg/g for total carotenoids were obtained. According to the literature, the results regarding total polyphenols and total flavonoids are similar or slightly lower than those previously reported [37,38]. Similar to these findings, the total carotenoid content was comparable to or rather decreased than earlier published data [39,40]. However, it is generally accepted that cornelian cherry fruits contain a reduced quantity of carotenoid pigments. On the other hand, when compared to other plant components, the leaves of cornelian cherry were discovered to be incredibly rich in carotenoids, especially β-carotene [41]. In addition, a more detailed characterization of the Cornus mas L. extract was assessed by HPLC-DAD-ESI-MS analysis. This resulted in the identification of 13 compounds belonging to four phenolic classes. Gallic acid glucoside had the highest concentration (248.51 μg GAE/mL), while Cy3-O-(coumaroyl-glucoside) had the lowest concentration (6.43 μg GAE/mL). According to Klymenko et al. [ 26], loganic acid had the highest concentration, ranging from 772 to 2390 μg GAE/g, while gallic acid was not identified in this study. Another research investigated the phytochemical profile of cornelian cherry fruit extract, revealing that the same compound had the greatest concentration, namely loganic acid (12913.51 μg/g). Gallic acid was identified only in yellow Cornus mas L. fruits, in a quantity of 263.59 μg/g, being similar to the quantity obtained in our study [42]. The composition of these compounds varies based on a wide range of parameters, including geographical region, genotype, cultivar and the degree of fruit ripening. Thus, it should be emphasized that these differences can be attributed to these factors. Regarding the antioxidant activity, we obtained a DPPH value of 0.466 mg/mL. In accordance with earlier studies, the result is slightly lower than those previously reported. Thus, Esroy et al. [ 43] reported DPPH ranging from 1.06 to 1.83 mg/mL and Celep et al. [ 44] registered a value of 0.72 mg/mL. In terms of the FRAP test results, we reported a value of 23.09 μmol Trolox/mL extract. This result is more elevated than those previously published in the literature. Klymenko et al. [ 26] registered FRAP ranging from 8.45 to 19.34 μmol Trolox/g, while Moldovan et al. [ 45] yielded a value of 0.628 μmol Trolox/g. Therefore, based on the previously mentioned factors, these variations can be linked to the different concentrations of phenolic compounds identified in cornelian cherry fruits. In conclusion, it should be noted that Cornus mas L. fruit extract exhibits in vitro antioxidant activity. By evaluating the antimicrobial activity, Cornus mas L. extract exerted antimicrobial activity against all tested strains, Pseudomonas aeruginosa and Enterococcus faecalis being the targets of the strongest effect. Moreover, the Cornus mas L. extract showed a significantly stronger antimicrobial potential towards these two bacterial strains when compared to amoxicillin–clavulanic acid and gentamicin. These results were compared to previously reported studies. Thus, Kyriakopoulos and Dinda [46] demonstrated the inhibitory effect of Cornus mas L. fresh fruits against the strains of Staphylococcus aureus and Pseudomonas aeruginosa. Another previous study investigated the antimicrobial potential of cornelian cherry fruits against four reference strains. Compared to our study, the diameters of the inhibition zone were significantly reduced for MSSA, Pseudomonas aeruginosa and Escherichia coli, being 8 mm for all strains [47]. Therefore, to the best of our knowledge, this is the first study examining the antimicrobial activity of Cornus mas L. fruit extract against MRSA, which may be especially intriguing for upcoming research on antibiotic resistance. Additionally, the Cornus mas L. fruit extract’s inhibition zone against Pseudomonas aeruginosa in this study had the largest diameter of any published data, strengthening the fruits’ antimicrobial characteristics. Nephrotoxicity is one of the well-known adverse effects of gentamicin. The tubular impact of this antibiotic, which can range from a simple loss of the brush boundary in epithelial cells to a clear tubular necrosis, is a key component of its nephrotoxicity. One important factor in gentamicin’s tubular damage is oxidative stress. Thus, it has been demonstrated that diverse antioxidants counteract the harmful effects of oxidative stress. A variety of plants contain antioxidant properties due to their increased quantity in bioactive constituents, such as phenolic compounds [48]. Water spinach, red grape, garlic and green tea are a few examples of such antioxidant-enriched plants that have been shown to have an antioxidant effect in gentamicin-induced kidney damage [49,50,51]. As previously mentioned, Cornus mas L. is also a plant with a high concentration of phenolic compounds that have antioxidant properties. The constituents from Cornus mas L. fruits may have a protective impact on gentamicin-induced nephrotoxicity, a potential use for this plant for which there has been minimal previous research. As such, we believed it was vital to perform a more thorough investigation of the cytoprotective effect of these fruits on renal epithelial cells exposed to gentamicin. This effect was analyzed through cell viability assays, namely MTT and Annexin-V FITC. By applying the MTT assay, it was revealed that the extract-treated cells and gentamicin-treated cells both had a decrease in cell viability when compared to control ($p \leq 0.0001$). Nevertheless, the extract-treated cells had a higher cell viability than gentamicin-treated cells. Interestingly, it was observed that the cell viability was shown to decline as the extract’s concentration increased, with the greatest concentration registering the lowest viability. This outcome might be explained by the pro-oxidant properties of polyphenols in high quantities. Importantly, when compared to gentamicin-treated cells, there was a significant increase in cell viability in the group of cells treated with gentamicin and Cornus mas L. extract ($p \leq 0.0001$). In addition, a similar increase in viability to the extract-treated cells was observed in the group of cells that received both an antibiotic and an extract treatment ($p \leq 0.05$). However, at high concentrations, a reduction in viability was shown, most likely as a result of the extract and gentamicin’s additive effects. These findings were then contrasted with the literature’s data. Thus, to the best of our knowledge, there has been only one previously published study regarding the cytoprotective effect of Cornus mas L. fruit extract in renal cell injury in vitro. Thus, Yarim et al. [ 34] demonstrated the cytoprotective effect of these fruits against cisplatin-induced nephrotoxicity by MTT assay. Cell viability in the cisplatin-treated group was $42\%$, while cisplatin and Cornus mas L. extract treated cells registered a significantly higher percentage of cell viability, i.e., $59\%$. The results of our investigation are generally consistent with this previous publication. The findings of the Annexin-V FITC test were comparable to those of the MTT assay. Thus, the gentamicin-treated cells showed a significantly lower percentage of viability when compared to control ($p \leq 0.0001$). This group additionally contained the highest proportion of cells in the necrotic phase, emphasizing the adverse effects of gentamicin on renal epithelial cells. Likewise, extract-treated cells had a significantly decreased percentage of vitality in comparison to control ($p \leq 0.0001$). On the contrary, when compared to cells that had just suffered gentamicin treatment, a higher percentage of cells were still viable. The greatest concentration from the extract-treated cells obtained the highest number of necrotic cells, outlining the information mentioned above regarding the pro-oxidant properties of polyphenols at high levels. Furthermore, there was no discernible loss in cell vitality at the first two concentrations in the group that received gentamicin and Cornus mas L. extract together, when compared to cells treated with extract only ($p \leq 0.05$). The last concentration, however, was found to be the most cytotoxic, reporting a lower percentage of viability than cells that were treated with the extract ($p \leq 0.05$) or even gentamicin ($p \leq 0.05$). This discovery might have relied on the extract and gentamicin’s additive pro-oxidant effects. The present study offers originality and, to the best of our knowledge, the first data regarding the apoptotic measurements of the tested ethanolic extract from Cornus mas L. Consequently, our study was contrasted to the protective effects of other natural substances in gentamicin-induced nephrotoxicity. As such, epigallocatechin gallate (EG), an active constituent of green tea, was studied by Yue et al. [ 52] for its effects on renal cells during gentamicin stress. The assessment of the cellular apoptotic rate by flow cytometry was performed. This indicated that the gentamicin-treated cell group had a substantially increased number of apoptotic cells. The use of EG as a therapeutic agent prevented these outcomes, with the rate of cell apoptosis reducing in the group receiving treatment with both gentamicin and the natural substance. These results are mostly comparable to those of our investigation, with the exception of the last concentration, which recorded noticeably higher values than the gentamicin group in both early and tardive apoptosis. In another study, sulforaphane (SFN), a naturally occurring isothiocyanate present in crucifers, was examined in order to determine whether it could protect LLC-PK1 cells from acute renal injury induced by gentamicin. In comparison to untreated cells, gentamicin treatment resulted in a 1.5-fold increase in necrotic cells and a 4.8-fold increase in apoptotic cells, aspects revealed by the flow-cytometry analysis. After receiving SFN therapy, the rise in apoptosis was greatly reduced. The rate of cell necrosis, however, did not significantly decrease after this natural compound was applied [53]. In our current study, a significant increase in cell necrosis compared to cell apoptosis was noted, probably due to the instability of the primary renal cell culture. Moreover, the cell groups treated with extract + antibiotic had a lower percentage of necrotic cells compared to the cells treated only with antibiotic. Shin et al. [ 54] investigated the nephroprotective effects of red ginseng extract (RGE) in acute renal injury induced by gentamicin on NRK-52E cells. The flow-cytometric analysis revealed that the nephrotoxic induced a significant increase in early apoptosis ($47.6\%$) when compared to the control group ($2.7\%$), with RGE improving these aspects. The increase in early apoptosis was even higher than the increase in cell necrosis in our study ($47.6\%$ vs. $30.87\%$). This finding may be the result of the different gentamicin concentrations and cell lines employed in each study. Therefore, it could be emphasized that, by displaying a more thorough cytotoxic activity utilizing the MTT test and Annexin V-FITC assay as well, this is the first article revealing that Cornus mas L. extract exhibits cytoprotective effects on primary renal cells stressed with gentamicin. Future interest in minimizing kidney injury may result from this study. ## 4.1. Chemicals and Reagents Sigma-Aldrich provided phenolic compounds and carotenoid pigments standards (Darmstadt, Germany). All tested samples were purified via a 0.45 µm MF-Millipore™ Membrane Filter from Merck prior to HPLC Analysis (Darmstadt, Germany). Plant Flavonoids Colorimetric Assay Kit and Annexin V-FITC with propidium iodide (PI) flow-cytometry Kit were both acquired from Elabscience Biotechnology Inc. (Houston, TX, USA) and Thermo Fisher Scientific Inc. (Waltham, MA, USA), respectively. Bacterial reference strains were obtained from Oxoid Ltd. (Hampshire, UK) and culture mediums, such as Mueller Hinton Broth and Mueller Hinton agar, were purchased from Merck (Darmstadt, Germany). Enzymatic mixing solutions for cell cultures were acquired from Sigma-Aldrich (St. Louis, MO, USA), while the substances for the culture medium were purchased from Gibco Life Technologies, Paisley, UK. ## 4.2.1. Harvesting Fruit Samples Cornelian cherry twigs, containing leaves and flowers, and fruits were collected from shrubs growing in natural habitats in the steep hills of Mărişel commune, Cluj county, Romania (46°40’03.7″ N 23°06’35.6″ E). The fruits were harvested between August and September 2020. All the plant’s components were identified and verified by Dr. Andrei Stoie (Professor of Botany, Faculty of Agriculture, University of Agricultural Sciences and Veterinary Medicine, Cluj-Napoca, Romania). A voucher specimen was deposited in the Botanical Department’s herbarium, Faculty of Agriculture, University of Agricultural Sciences and Veterinary Medicine, Cluj-Napoca, Romania. After the fruits were harvested and identified, the twigs, leaves and stones were manually removed. The entire quantity of fruit pulp was then portioned into 100 g sample pouches and preserved at −18 °C in a refrigerator until further proceedings. ## 4.2.2. Preparation of Extracts The fruits had been thawed and dehydrated using a TEESA TSA3031 dehydrator at a temperature of 45 °C for 7 days. After dehydration, they were pulverized into powder. The extraction was performed on 10 g of fruit powder using 100 mL of $96\%$ ethanol. The resulting mixture had been subjected to homogenization for 2 h, with the help of a magnetic stirrer, at 1000 rpm. The mixture was then filtered, using a funnel and cotton wool, and the residue was re-extracted using the same procedures. The resulting extracts were pooled and concentrated by evaporation, using an Eppendorf Concentrator Plus evaporator at 45 °C. Lastly, the volume obtained was measured and utilized for direct determinations, namely total phenolic content, total flavonoids, LC-MS analysis, antioxidant capacity, antimicrobial activity and cytotoxic assays. All phases of extraction were performed in triplicate. In parallel, an ethyl ether re-extraction was performed in order to determine the fat-soluble compounds, particularly total carotenoids. As such, water, ethyl ether and the ethanolic extract were poured into a separatory funnel. Two phases were observed: the upper organic phase and the lower aqueous phase. The organic phase was separated and passed through anhydrous Na2SO4 to remove traces of water and was later subjected to rotary evaporation at 40 °C. As a final extraction phase, the oleoresin residuum was resuspended in a known volume of ethyl ether for subsequent assessments. ## 4.2.3. Total Phenolic Content Assay The Folin–Ciocalteu method was employed to assess total polyphenolic concentration. This method was performed according to Moldovan et al. [ 45] with slight modifications. A calibration curve of gallic acid was obtained, with eight different concentrations, ranging from 50 to 450 µg/mL. At 765 nm, the absorbance was measured using a microplate spectrophotometer (SPECTROstar® Nano—BMG Labtech, Ortenberg, Baden-Württemberg, Germany). The values were presented in mg of GAE (gallic acid equivalent) per mL of extract. The measurements were conducted in three replicates [55]. ## 4.2.4. Total Flavonoid Content Assay The total flavonoid content was assessed using a colorimetric assay kit (Plant Flavonoids Colorimetric Assay Kit—Elabscience Biotechnology Inc., Houston, TX, USA). The principle of assessment involves the reaction of flavonoids and aluminum ions in a basic medium, which leads to the formation of a red complex. The samples were prepared according to the instructions on the kit. The absorbance of the samples was determined in contrast with a blank sample (bidistilled water) at 510 nm, using the same microplate spectrophotometer as mentioned in the previous determination. A standard curve was obtained for calculation by diluting the standard solution of 1 mg/mL with bidistilled water to six different concentration levels, between 20 and 150 µg/mL. The outcomes were given in µg per mL of extract. The analyses were performed in triplicate [55]. ## 4.2.5. HPLC-DAD-ESI-MS Screening Chromatographic separation of phenolic compounds in the ethanolic extract of Cornus mas L. fruits was conducted on an Agilent 1200 HPLC system packed with photodiode UV-Vis detector (DAD) coupled to a single mass detector (MS), model 1160 (Agilent Technologies, CA, USA). The protocol for separating the compounds was carried out in accordance with Dumitraş et al. [ 55], who detailed the methodology. Three calibration curves were created for quantification of the phenolic compounds, by injecting five different concentrations of $99\%$ purity standard substances as follows: chlorogenic acid for phenolic acids, rutin for flavonoids and cyanidin for anthocyanins. The calculation was made using a mathematical formula: $y = 40.7$ × (−71.5) (R2 = 0.9995). Spectral values had been recorded in the range of 200–600 nm, with phenolic acids being detected at 280 nm, flavonoids at 340 nm and anthocyanins at 520 nm. For LC-MS, the following working conditions were employed: capillary voltage of 3000 V, temperature of 35 °C, nitrogen flow of 7 L/min and monitoring range of 100–1200 m/z. Agilent ChemStation software was used to collect data and interpret results. ## 4.2.6. Total Carotenoid Content Assay In accordance with Dumitraş et al. [ 55], a UV spectrophotometric method was assessed to determine the concentration of total carotenoids. The extract’s absorption spectrum was measured between 350 and 700 nm using the same microplate spectrophotometer mentioned above. The quantity of carotenoid pigments was calculated [56] and the results were expressed as µg/g of DM (dry mass). The tests were conducted in three replicates. ## 4.3.1. Radical Scavenging Activity Assay (DPPH) The principle of DPPH method is based on the gradual formation of a colorless compound as the intensity of the purple color of the DHPP solution decreases after the addition of an antioxidant. Thus, by monitoring the decrease in DPPH absorbance, the antioxidant interest of the compound can be determined [57]. The assay was performed in accordance with Dumitraş et al. [ 55], with slight modifications. In brief, 2 mL of 0.1 g/L DPPH solution in methanol was mixed with 2 mL of extract in various quantities. The samples were kept in a 40 °C thermic bath for half an hour before measuring the change in absorbance at 517 nm. The following percentage of DPPH scavenging capacity was estimated as follows: DPPH inactivation capacity % = (AC − AS/AC) × 100, where AC represents control absorbance and AS represents sample absorbance. The results were provided in IC50 (mg/mL). ## 4.3.2. Ferric Reducing Antioxidant Power Assay (FRAP) The FRAP method was implemented following the methodology described by the study mentioned earlier [55], with minor adjustments. The assay’s principle is built on antioxidants’ ability to convert Fe3+ to Fe2+, an ion that subsequently forms blue complexes in the presence of TPTZ (2,4,6-Tri (2-pyridyl)-s-triazine) and can be detected at 593 nm [58]. Firstly, FRAP reagent was prepared using a known volume of TPTZ solution, ferric chloride solution and acetate buffer. Following this phase, 6 mL of FRAP reagent was mixed with 0.8 mL of deionized water in 4 mL of extract. Correspondingly, a blank solution was created by substituting water for the sample. Measurements of absorbance at 593 nm were used to correlate color change with antioxidant capacity. The antioxidant activity was calculated using a Trolox calibration curve (R2 = 0.992). The scores were expressed as μmol Trolox equivalents/mL of extract. ## 4.4. Antimicrobial Activity The antimicrobial properties of Cornus mas L. extract were in vitro evaluated using the agar well diffusion assay, being an adapted EUCAST (European Committee on Antimicrobial Susceptibility Testing) disk-diffusion assay [59]. Six bacterial reference strains obtained from Oxoid Ltd. (Hampshire, UK) were integrated, namely Staphylococcus aureus ATCC 25923 (methicillin-susceptible S. aureus, MSSA), Staphylococcus aureus ATCC 700699 (methicillin-resistant S. aureus, MRSA), Bacillus cereus ATCC 14579, Enterococcus faecalis ATCC 29219, Escherichia coli ATCC 25922 and Pseudomonas aeruginosa ATCC 27853. Each bacterium was cultured on Mueller Hinton (MH) broth and agar, mediums that were purchased from Merck (Darmstadt, Germany, catalogue number 70192 and 70191-500G). A 24 h pure culture was used to prepare the bacterial inoculums by suspending colonies in sterile saline to obtain 10E6 colony forming unit (CFU)/mL, according to the McFarland scale. After inoculums were “flood-inoculated” on MH agar plates, 6-millimeter diameter wells (three for each testing) were aseptically made into the MH agar and filled with 60 μL of extract. Both negative ($70\%$ ethanol in water v/v) and positive controls (standard antibiotics disks: gentamicin (10 µg), amoxicillin–clavulanic acid (20–10 µg) from Oxoid Ltd., Hampshire, UK, catalog number CT0794B and CT0223B) were included. Following 24 h of incubation at 37 °C, the values of growth inhibition zone diameters (in mm) were measured. A second method, namely the broth microdilution method, was utilized to establish the minimum inhibitory (MIC) and bactericidal (MBC) concentrations. Briefly, two-fold serial dilutions of the tested extract in MH broth were made in 96-well bottom “U” polystyrene plates. The resulting concentrations (ranging from 650 μg GAE/μL to 5.07 μg GAE/μL) were cultured with 5.0 µL bacterial inoculum for 24 h at 37 °C. Reading of MICs values took into account the lowest concentrations able to inhibit the visible bacterial growth (no turbidity in the well) compared to the negative control (MH broth). MBC values were established following the 24 h culture on MH agar of 10.0 µL from each well and considering the lowest concentrations associated with no visible bacterial growth on the agar plates. MH broth was also included as MIC negative control. In addition, the MIC index calculated based on the ratio MBC/MIC indicated whether the extract displays a bactericidal (MBC/MIC ≤ 4) or bacteriostatic (MBC/MIC > 4) effect against the tested bacterial strains [60,61]. ## 4.5.1. Experimental Animals and Protocols The experiment was conducted in the authorized Animal Research Facility of the Faculty of Veterinary Medicine, Cluj-Napoca, Romania. The Institute of Oncology “Prof. Dr. Ion Chiricuţă”, Cluj-Napoca, Romania provided one adult, 6 days pregnant female C57BL/6J mouse, weighing 25 g, which was used in the experiment. In accordance with ISO 10993-6 requirements [62] and Regulation $\frac{63}{2010}$/EU, the female was maintained in an aerated cage, at a temperature of 25 ± 2 °C and a relative humidity of $55\%$ ± $10\%$, with a 12 h diurnal period. In addition, the individual had unrestricted access to fresh water and regular food for rodents, provided by the Cantacuzino Institute, Bucharest, Romania. Before the experimental procedures, the individual was acclaimed in this environment for 1 week. All animal operations adhered to the standards of Regulation $\frac{63}{2010}$ and state legislation no. $\frac{43}{2014.}$ The study was authorized by the Ethics Committee of the University of Agricultural Sciences and Veterinary Medicine, Cluj-Napoca, Romania (no. $\frac{256}{21.04.2021}$) and by the Regional Sanitary Veterinary and Food Safety Authority (no. $\frac{274}{12.11.2021}$). Surgical techniques were carried out in accordance with ISO 10993-6. At the end of the accommodation period, the female was mercifully euthanized under general anesthesia through cervical dislocation, on day 13 of pregnancy. After this procedure, incisions in the abdominal cavity and further in the uterus were performed, with the extraction of five individual fetuses that were separated and washed in Dulbecco’s phosphate buffer saline (PBS). Furthermore, the fetuses’ abdominal cavities were incised and the kidneys were collected and added to PBS solution for further proceedings. ## 4.5.2. Renal Epithelial Cell Cultures In order to obtain primary renal cultures, cells were isolated from the kidneys of mouse fetuses through a mixed method which implies tissue explants and enzymatic treatment. The renal capsule was removed, and kidneys were finely minced and further treated for 30 min with an enzymatic mixing solution consisting of collagenase IV $0.1\%$ and 0.1 mg/mL Dispase (Sigma-Aldrich, Saint Louis, MO, USA). Cell suspension together with residual tissue explants was added to culture plates that had been pretreated with $4\%$ porcine gelatin (Sigma-Aldrich, Saint Louis, MO, USA). For propagation, Dulbecco’s Modified Eagle Medium was used, as it was supplemented with $10\%$ fetal bovine serum, 100 mg/mL streptomycin, 100 U/mL penicillin and 50 mg/mL gentamicin (substances purchased from Gibco Life Technologies, Paisley, UK). Furthermore, the cultures had been incubated at 37 °C, in a microclimate enriched with $5\%$ CO2 and $90\%$ humidity for 5 days. Additionally, the cultures were washed with PBS solution and treated for 10 min at 37 °C with Trypsin–EDTA solution (Sigma-Aldrich, Saint Louis, MO, USA), after which the cell suspension was centrifuged at 1200 rpm for 7 min. Subculturing was completed at a concentration of 5 × 103 cells/plate. ## 4.5.3. Cell Viability Assay The MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) colorimetric assay was used to assess the extract’s potential cytotoxicity. The method functions by reducing the yellow MTT compound to purple formazan crystals using enzymes from metabolically active cells. The formazan is then dissolved in $100\%$ isopropanol, and its concentration is measured spectrophotometrically at 450 nm. The protocol was carried out in accordance with previous research with slight modifications [48]. Therefore, a concentration of 1 × 104 cells/well, corresponding to 200 µL cell suspension, was obtained. The cell suspension was placed in each well of 96-well plates containing normal propagation medium and was further held in abeyance for 24 h. Following that, the extract to be evaluated was added to wells in volumes of 10, 15 and 20 μL, in three differing concentrations, namely CM1, CM2 and CM3. The amount of polyphenolic compounds found in the fruit extract was used to calculate these concentrations. Thus, CM1 denotes 130 μg GAE/μL polyphenols, CM2 denotes 195 μg GAE/μL polyphenols and CM3 denotes 260 μg GAE/μL polyphenols. Several cell cultures were treated with 100 mg/mL gentamicin in three different concentrations (G1 = 100 μg/μL, G2 = 150 μg/μL and G3 = 200 μg/μL), while several others were treated with Cornus mas L. extract and gentamicin together. Untreated cells were used as negative control, while gentamicin-treated cells were used as positive control. Cell proliferation was assessed after 24 h by removing the culture medium and adding 100 μL of MTT solution (1 mg/mL) (Sigma-Aldrich, St. Louis, MO, USA). The MTT solution was removed from each well after 3 h of incubation at 37 °C in darkness, and 150 μL of DMSO (dimethyl sulfoxide) solution was added. The BioTek Synergy 2 spectrophotometer (Winooski, VT, USA) was used to measure the intensity of the chromogenic reaction at 450 nm. The percentage of cell viability was calculated based on a mathematical formula: Viability% = AT/AC × 100, where AT represents the absorbance of treated cells and AC represents the absorbance of control cells. All tests were run in three replicates. ## 4.5.4. Cell Apoptotic Assay The Annexin V-FITC cell apoptosis detection kit (Thermo Fisher Scientific Inc., Waltham, MA, USA) was used to determine the apoptosis rate of renal epithelial cells. This determination was assessed following the guidelines represented in the kit. A total of 2.5 × 105 cells/well were planted in 12-well plates and further treated with the same concentrations of extract (CM1–CM3), gentamicin and a combination of both. Furthermore, PBS (phosphate bovine serum) solution was used to wash the cells before resuspension. To resuspend the cells, 500 μL of Annexin V Binding Buffer was introduced in each well. Subsequently, a total of 5 μL of Annexin V-FITC reagent and 5 μL of fluorescent substance (100 g/mL PI—propidium iodide) were added. Following these procedures, the samples were vortexed and incubated in a sunless environment at room temperature for 15 min. At the end of the incubation period, the samples were analyzed by flow cytometry using the FACS technique (fluorescent sorting of activated cells). As such, flow cytometry was carried out using a flow cytometer outfitted with a 488 nm, air-cooled, 20 mW solid-state excitation laser, as well as a $\frac{530}{30}$ FITC filter and a $\frac{575}{26}$ PI filter for fluorescence detection. The data were analyzed using the FACSDiva 6.1.2 software (Becton Dickinson, San Jose, CA, USA). As for interpretation, it was assumed that Annexin V-FITC+ and PI− indicate apoptosis in its early stages, meanwhile Annexin V-FITC+ and PI+ indicate tardive apoptosis. Likewise, Annexin V-FITC− and PI+ suggest cells to be necrotic and Annexin V-FITC− and PI− suggest cells to be viable [55]. ## 4.6. Statistical Analysis The results were expressed as mean ± standard deviation (SD) after each assessment was conducted in triplicate. The statistical software Graph Pad Prism 9 (San Diego, CA, USA) was used to perform the statistical analysis. Utilizing one-way ANOVA and t-test functions, data analysis was completed. The significance level was established at $p \leq 0.05.$ ## 5. Conclusions To the best of our knowledge, this is the first paper that analyzes the extract of Cornus mas L. fruits in relation to its phytochemical profile, antioxidant capacity, antimicrobial potential and cytoprotective effects. Cornus mas L. fruits have been shown to have high concentrations of biologically active substances, particularly phenolic compounds, whereas carotenoids were only identified in relatively low concentrations when compared to other plant components. The fruit extract demonstrated a significant in vitro antioxidant capacity and antimicrobial activity against all tested reference strains. Furthermore, with the exception of the high dose, which had a similar nephrotoxic impact to that of gentamicin, it also demonstrated cytoprotective benefits in gentamicin-induced nephrotoxicity on mice renal epithelial cells. 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--- title: Effects of Two Feeding Patterns on Growth Performance, Rumen Fermentation Parameters, and Bacterial Community Composition in Yak Calves authors: - Qin Li - Yan Tu - Tao Ma - Kai Cui - Jianxin Zhang - Qiyu Diao - Yanliang Bi journal: Microorganisms year: 2023 pmcid: PMC10058967 doi: 10.3390/microorganisms11030576 license: CC BY 4.0 --- # Effects of Two Feeding Patterns on Growth Performance, Rumen Fermentation Parameters, and Bacterial Community Composition in Yak Calves ## Abstract The health of young ruminants is highly dependent on early rumen microbial colonization. In this study, the effects of milk replacer on growth performance, rumen fermentation, and the rumen microflora in yak calves were evaluated. Sixty yak calves (body weight = 22.5 ± 0.95 kg, age = 30 ± 1 d) were assigned to the CON group (breastfed) or TRT group (milk replacer fed) and evaluated over 120 d. At 120 d, ruminal fluid samples were collected from 14 calves and then conducted for rumen fermentation and microbiota analyses. There was no difference in growth performance; however, calf survival was higher in the TRT group than in the CON group. The concentration of total volatile fatty acids and the molar proportion of butyric acid and lactic acid were increased with milk replacer feed in the TRT group ($p \leq 0.05$), but iso-valeric acid concentration was highest in the CON group ($p \leq 0.05$). Firmicutes and Bacteroidetes were the most dominant phyla in the CON and TRT groups, respectively. In the TRT group, Bacteroidetes, Prevotellaceae, Bacteroidia, Bacteroidetes, and Prevotella_1 were the dominant flora in the rumen of calves. The relative abundances of various taxa were correlated with rumen fermentation parameters; the relative abundance of Quinella and iso-butyrate levels were positively correlated ($r = 0.57$). The relative abundances of the Christensenellaceae_R-7_group and A/P were positively correlated ($r = 0.57$). In summary, milk replacer is conducive to the development of the rumen microflora, the establishment of rumen fermentation function, and the implementation of early weaning in yaks. ## 1. Introduction The yak (Bos grunniens) is an important species on the Tibetan Plateau (3000 m above sea level) [1]. This ruminant is a “living treasure” for the Tibetan people because it can provide milk, meat, hair, hides, and feces (a valuable fuel) [2,3]. The nutritional status of the mother-calf is the most important determinant of female yak reproduction, and farms tend to shorten the duration of the postpartum off-cycle by weaning early and restricting the nutrition provided by cows to calves, which results in slower growth and higher winter mortality in newborn calves [4]. The reproductive rate of adult female yaks undergoing conventional breastfeeding is only $48.61\%$ in this environment [5]. In addition, the survival rate of newborn calves is meager due to extreme cold weather and malnutrition [6,7]. As a result, yak breeding is highly challenged. Milk replacer (MR) has shown beneficial effects in animal experiments [8] and has a positive effect on animal growth and gastrointestinal development [9,10]. MR can not only effectively replace breastfeeding and help the mother and offspring recover their physical condition as soon as possible but can also help the ruminal microorganisms of the calf adapt earlier during the transition from liquid feed to solid feed [11] and promote the colonization of dominant bacteria in the rumen. In ruminants, rumen fermentation must be considered in the feeding management period from birth to weaning [12]. Early feeding programs and nutrition significantly impact the diversity and evolution of the rumen microbial community [13,14]. The early colonization of rumen microorganisms is significant for rumen fermentation and later growth and development [15]. The effect can last for a long time and therefore affect the performance and health of adult ruminants for life. Concerning underlying mechanisms, we focused on the effect of MR consumption in yak calves on rumen fermentation and the rumen microflora in this study. To determine whether MR can achieve the same effect as breastfeeding in yak calves, growth performance, rumen fermentation, and microbiota were evaluated. We hypothesized that MR could promote growth, rumen fermentation, and microbial colonization in yak calves. The results of this study provide a theoretical basis for the use of MR for early weaning in yak calves. ## 2. Materials and Methods The experiment protocol was approved by the ethics committee of the Chinese Academy of Agricultural Sciences Animal, and it was performed in accordance with the animal welfare practices and procedures in the Guidelines for Experimental Animals of the Ministry of Science and Technology. ## 2.1. Animals and Experimental Design A total of 60 yak calves (body weight = 22.5 ± 0.95 kg, age = 30 ± 1 d) were randomly divided into control (CON) and experimental (TRT) groups, with 30 calves in each group. In the CON group, yak calves were breastfed and lived with their mothers throughout the experiment. In the TRM group, yak calves were separated from female yaks and fed on MR. The experiment was conducted for a total of 120 days in Nagqu, Tibet, from September to December 2019. MR for yak calves (Patent Number: 02128844.5) was obtained from the Beijing Precision Animal Nutrition Research Center, China. The nutrient composition of the MR is shown in Table 1. Boiling water was cooled to 50 °C and MR was added at a MR:water ratio of 1:7 until the emulsion cooled naturally to 39 °C. MR was bottle-fed to calves in the TRT group twice a day (08:00 and 18:00) at $1.5\%$ (DM) of the body weight. All calves were allowed to drink water ad libitum. ## 2.2. Growth Performance and Survival Rate At days 0 and 120, yak calves were weighed, and the average daily gain was calculated. During the experiment, the mortality rate of calves was recorded, and the survival rate in each group was calculated. ## 2.3. Milk Replacer Nutrient Content Dry matter (DM) content was determined by drying in an oven at 105 °C for 6 h. Crude protein (CP) was determined by the Kjeldahl method (FOSS-8400). Ether extract (EE) was obtained by Soxhlet extraction. The ash content was determined by a muffle furnace burning for 6 h. Ga was determined by atomic spectrophotometry (M9W-700; Perkin-Elmer, Waltham, MA, USA). The P content was evaluated by molybdenum vanadate colorimetric determination. ## 2.4. Ruminal Chyme Collection On d120, seven calves in each group were used for the collection of ruminal chyme samples through the oral cavity. The first extracted chyme was discarded, and then ruminal chyme samples were aspirated from different parts and immediately frozen in a −80 °C liquid nitrogen tank after mixing completely. Subsequently, microbiome and rumen fermentation characteristics were analyzed. ## 2.5. Ruminal Analysis of Fermentation Parameters After samples were thawed, they were centrifuged at 20,000× g and 4 °C for 15 min. Three 1 mL rumen fluid samples were extracted, 0.25 mL of metaphosphoric acid was added, and volatile fatty acid (VFA) profiles were determined using a gas chromatography instrument (GC-6800; Beijing Beifen Tianpu Instrument Technology Co., Ltd., Beijing, China). ## 2.6. DNA Extraction, PCR Amplification, and 16S rRNA Sequencing Microbial DNA was extracted from rumen fluid samples using the OMEGA E.Z.N.A.® Digesta DNA Kit (OMEGA Bio-Tek, Norcross, GA, USA) according to the protocol described by the manufacturer. DNA quality and quantity were determined using a ND 1000 spectrophotometer (NanoDrop Technologies Inc., Wilmington, DE, USA). Using primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′), the V3-V4 region of the bacterial 16S ribosomal RNA gene was amplified by PCR. The conditions for the PCR were as follows: 95 °C for 3 min, followed by 95 °C for 30 s, 55 °C for 30 s, 72 °C for 45 s, and finally 72 °C for 10 min. The barcode sequence was eight bases long and unique to each sample. The PCR was performed in three 20 μL mixtures consisting of 4 μL of 5× FastPfu Buffer, 2 μL of 2.5 mM dNTPs, 0.8 μL of each primer (5 μm), 0.4 μL of FastPfu Polymerase, and 10 ng of template DNA. Amplicons were extracted from $2\%$ agarose gels and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) according to the manufacturer’s instructions. The QuantiFluor™-ST system (Promega, Madison, WI, USA) was used for quantification. Purified amplicons were aggregated in equimolar ratios on an Illumina MiSeq PE300 platform for 2 × 300 bp paired-end sequencing according to standard protocols. ## 2.7. Sequencing Data Processing After demultiplexing the original FASTQ files, the sequences were filtered using Trimmomatic according to the following criteria: (i) within a 50 bp sliding window, reads longer than 300 bp were truncated at the site with a quality score of <20, and those shorter than 50 bp were discarded; (ii) reads containing any mismatches in the barcode region, two or more nucleotide mismatches in the primer sequence, or ambiguous characters were discarded; and (iii) only overlaps and GT; Bp and 10 and lt; $10\%$ of mismatched sequences were assembled; unassembled reads were discarded. The assembled sequences were then trimmed with primers and barcodes. Chimeric sequences were identified and deleted using USearch. After quality control, assembled sequences were assigned to operational taxonomic units (OTUs) using UPARSE with a $97\%$ identity threshold. RDP classifier version 2.2 and the Silva database were used for annotation at the domain, phylum, class, order, family, genus, and species levels. QIIME 2 was used to calculate the alpha diversity indexes, including the ACE, Chao1, Shannon, and Simpson indexes. The alpha indexes were compared between groups using Kruskal–Wallis tests in R version 4.0.2. The differences in bacterial communities between groups were evaluated by a principal coordinate analysis (PCoA) based on the Bray–Curtis dissimilarity matrix using QIIME 2. Linear discriminant analysis effect size was used to identify significant bacteria in the two groups. ## 2.8. Statistical Analyses All data were tested for normality using the Sharpiro-Wilk test in R-Studio (3.6.1) and were normally distributed ($p \leq 0.05$). Differences in growth performance and rumen fermentation parameters between the CON and TRT groups were compared using the unpaired t-test. Differences in alpha diversity and relative abundance at the phylum, family, and genus levels were evaluated [16]. The Kruskal–Wallis test (in R version 4.0.3) was used to compare the microbiota function between groups. The “ape”, “ggplot2”, “limma”, “GGplot2”, and “GGTree” packages in R were used to visualize results (i.e., to obtain PCoA plots, Venn diagrams, bar plots, and LEfSe plots) [16,17,18]. The “corrplot” package in R was used to analyze the correlations between the top 20 genera of all samples and rumen fermentation parameters (based on Spearman’s correlation coefficients). The network containing the top 20 genera was visualized using the “igraph” package in R version 4.0.3. The transformed data for the abundances of communities at the phylum and genus levels were analyzed by one-way ANOVA using SAS. The MIXED procedure model included the fixed effects of treatment and interactions between treatments, as well as the random effect of the individual nested within treatment. Treatment differences with $p \leq 0.05$ were considered statistically significant, and 0.05 ≤ $p \leq 0.10$ indicated marginal significance. ## 3.1. Growth Performance and Survival of Yak Calves under Two Feeding Modes As summarized in Table 2, there was no significant difference in growth performance between the two groups, indicating that MR satisfied the basic growth needs of calves. However, the survival rate of calves in the TRT group ($73.33\%$) was significantly higher than that in the CON group ($46.47\%$) ($p \leq 0.05$). This suggested that MR feeding helped calves adapt to the highland environment. ## 3.2. Rumen Fermentation Parameters for Yak Calves under Two Feeding Modes As shown in Table 3, rumen fermentation parameters, particularly TVFA, butyric acid, iso-valeric acid, and lactic acid levels, differed significantly between the two feeding patterns ($p \leq 0.05$). The TRT group exhibited higher TVFA and lactic acid concentrations and higher molar ratios of butyric acid and lactic acid than those of the CON group ($p \leq 0.05$). The CON group had a higher molar ratio of iso-valeric acid than the TRT group ($p \leq 0.05$). The remaining fermentation parameters were similar between the two groups; there was no statistical significance. ## 3.3.1. Overview of Sequencing Data for Rumen Microorganisms The flora in rumen fluid samples was subjected to paired-end sequencing, and raw data were filtered to obtain 2,871,736 high-quality reads, with an average of 191,450 reads per sample. Based on the $97\%$ sequence similarity threshold, 4182 OTUs were obtained from 15 groups of rumen fluid samples, of which 3679 OTUs were detected in the CON group and 3270 OTUs were detected in the TRT group. In total, 2785 ($66.59\%$ of the total OTUs) were common to both groups (Figure 1A). The sequencing coverage in both groups was $98\%$ (Table 4), indicating that the depth of the sequencing reflects the true microbial profile in the rumen fluid of calves. The observed_species and PD_whole_tree in the CON group were significantly higher than those in the TRT group ($p \leq 0.05$), indicating a higher species abundance in the CON group. There were no significant differences in other diversity indices, indicating that the difference in microbial diversity between the two groups was small. The results of a PCoA (Figure 1B) showed that there was only partial overlap in OTU frequencies between the two groups, with significant differences ($p \leq 0.003$), as well as significant differences among individuals within the CON group. ## 3.3.2. Relative Abundance of Bacterial Populations To further evaluate the effect of MR on the rumen flora of calves, we compared the relative abundance of each taxon at the phylum and genus levels (Figure 2). Firmicutes ($46.85\%$), Bacteroidetes ($46.83\%$), and Actinobacteria ($1.59\%$) were the dominant flora in the rumen of calves in both feeding modes. However, the most abundant bacterial phylum was Bacteroidetes ($58.33\%$; $$p \leq 0.001$$) in the TRT group and Firmicutes in the CON group ($55.47\%$; $$p \leq 0.003$$) (Figure 2A and Supplementary Table S1). At the genus level, the results for both groups were similar to those for the phylum level, which suggests that the feeding pattern was one of the key drivers of the early colonization of rumen microbes. Notably, the top six dominant genera identified were common to both groups. However, their relative abundances differed between groups. In the TRT group, Prevotella_1 ($39.89\%$), Christensenellaceae_R-7_group ($6.00\%$), Christensenellaceae_R-7_group ($6.00\%$), the Rikenellaceae_RC9_gut_group ($4.17\%$), Succiniclasticum ($2.73\%$), and Ruminococcaceae_NK4A214_group ($2.54\%$) were most abundant. The relative fractions of these bacteria in the CON group were $15.04\%$, $18.98\%$, $15.78\%$, $6.39\%$, $5.23\%$, $3.72\%$, and $2.62\%$, respectively. The relative abundances of the genera Prevotella_1 ($$p \leq 0.001$$) and Lachnospiraceae_XPB1014_group ($$p \leq 0.005$$) were significantly higher in the TRT group than in the CON group. The relative abundances of Prevotellaceae_UCG-003 ($$p \leq 0.026$$) and Eubacterium_coprostanoligenes_group ($0.016\%$) were significantly lower in the TRT group than in the CON group (Figure 2B and Table S1). ## 3.3.3. LEfSe Analysis To better identify specific bacteria in both groups, we used a LEfSe analysis and LDA scores (Figure 3). Taxa with LDA scores of >4 were identified as biomarkers. In the TRT group, the Bacteroidetes phylum, Prevotellaceae family, Bacteroidia class, Bacteroidetes order, and Prevotella_1 genus were highly discriminative (LDA score >4.8). Firmicutes (LDA score > 4.8) was highly discriminative in the CON group. ## 3.4. The Correlation of Ruminal Fermentation Parameters with Bacterial Communities Our results revealed that the rumen microbial composition differed significantly between the two groups. Such differences were often due to differences in the internal environment caused by dietary differences. Accordingly, we analyzed the correlations between the relative abundance of the top 20 bacterial genera and fermentation parameters (Figure 4). The relative abundance of Quinella and iso-butyrate levels were positively correlated ($r = 0.57$). The relative abundances of the Christensenellaceae_R-7_group and A/P were positively correlated ($r = 0.57$). Butyrivibrio_2 relative abundance and iso-butyrate levels were negatively correlated ($r = 0.57$). The relative abundance of Veillonellaceae_UCG-001 was negatively correlated with TVFA (r = −0.55). The relative abundance of Lachnospiraceae_XPB1014_group was positively correlated with butyrate ($r = 0.58$). The relative abundance of Ruminococcaceae_UCG-014 was positively correlated with lactate levels ($r = 0.59$). The relative abundance of Saccharofermentans was positively correlated with A/P ($r = 0.58$). The relative abundance of Ruminococcus_1 was negatively correlated with propionate levels (r = −0.55) and positively correlated with A/P ($r = 0.60$) (Figure 4A). The relative abundance of Lachnospiraceae_NK3A20_group and iso-butyrate levels had a highly significant positive correlation ($r = 0.76$) (Figure 4B). ## 4. Discussion The altitude at which this experiment was carried out (4436 m) was higher than that of a previous study (approximately 3000 m) [19]. However, weight gain data for 30-day-old yak calves have not been reported in existing literature. Yak calves could be weaned and fed MR as early as 30 days after birth; early weaning improved yak calves’ survival rate. We found that MR can completely replace yak milk to feed yak calves; this study provides the first evidence supporting the use of MR in yak calves. Ruminal fermentation parameters are potential markers of rumen microorganisms and are representative of how rumen microorganisms respond to diet [20,21,22]. Ruminal VFA can provide up to $70\%$ of the total energy requirements for ruminants [21]. The total volatile acid concentration was significantly higher in the TRT group than in the CON group, which may be related to a difference in the total intake of dry matter [23]. Furthermore, calves in the TRT group exhibited steady feed intake on a daily basis throughout the experiment. Yak lactation decreases once the calf reaches 2–6 months of age [24]. Therefore, we thought that feed intake was affected by this decrease in the CON group [25]. Butyrate is one of the three most highly produced VFAs in the rumen and has beneficial effects on calf gastrointestinal development, pancreatic secretion, and nutrient digestion [26,27,28]. The incidence of diarrhea is reduced by butyrate [29]. Lactose is a candidate for butyrate enhancement in the rumen, as it increases the concentration of butyrate in cows [30] and promotes the proliferation of probiotics such as Lactobacillus and Bifidobacterium [31]. On the other hand, lactose provided more fermentation substrate for microorganisms in the TRT group. Iso-valerate is a branched-chain fatty acid produced by the rumen fermentation of branched-chain amino acids [32]. It could increase the number of fibrinolytic bacteria with little effect on calves during lactation [33]. A total of $40\%$–$68\%$ of the proteins synthesized by microorganisms are derived from NH3-N [34]. In this study, the differences in NH3-N concentrations between the two groups were not significant, but the results in two groups were in the concentration range with the highest efficiency (5–25 mg/dL) [35]. TRT provided more nitrogen, promoted the synthesis of MCP, and resulted in more metabolizable proteins in the small intestine for use by calves. Rumen fermentation results were consistent with those of a previous study involving yak calves (TVFA = 68 mmol/L) [36]; however, in 6-month-old calves eating roughage, the NH3-N concentrations were reduced (NH3-$$n = 5$.46$ mg/dL) [36]. Considering these results, we believe that MR acts as a stable and rich nutrient source for yaks, providing a favorable environment for the early colonization of rumen bacteria. At 3 weeks of age, concentrate feed intake allows calves to transition from functional non-ruminants to true ruminants, a process that relies on the establishment and activity of the rumen microbiota. Until weaning, the rumen is fully functional [37]. However, the microbial taxa commonly found in the mature rumen are established in the rumen of calves [38,39]. MR ensured that the calves had more concentrated diets in the TRT group, which led to a decrease in the rumen microbiota [40], and this was likely related to the high content of dominant bacteria. Firmicutes and Bacteroides are the main phyla in the rumen, intestines, and feces, and Firmicutes is more dominant in the yak rumen [41,42]. This dominance is positively correlated with the fiber degradation capacity, which is conducive to the digestion of poor-quality pasture [43]. We discovered an increase in microbial diversity of domestic yaks, which enriches Firmicutes in wild yaks [44]; Firmicutes contributes to effective energy harvesting [45]. Calves of the TRT group likely had advantages in adapting to the harsh environment of the plateau. Verrucomicrobia is the dominant bacteria in the rumen of grazing yaks in the CON group, and the high abundance of this taxon may be due to grazing [46]. The relative abundance of Prevotella is high in yak rumen [47], and another study indicated that Prevotella_1 is most abundant in yak stomachs and duodenum [46]. The genus Prevotella is known for its high VFA production using rumen proteins, which may also explain why Prevotella_1 was the most dominant bacteria in both groups [47]. However, calves in the TRT group had higher TVFA contents than those in the CON group. g__Quinella is an H2-incorporating bacterium associated with low methane production [48]. The g__Christensenellaceae_R-7_group belongs to the phylum Firmicutes and is associated with the breakdown of proteins in feed and can promote the absorption of nutrients. The g__Rikenellaceae_RC9_gut_group is abundant in yaks and may play a role in the digestion of plant-derived polysaccharides [49]. These genera are conducive to rumen digestion and absorption and did not differ significantly between the two groups. In summary, the microbial structure of the TRT group was conducive to the absorption and degradation of nutrients, emphasizing the beneficial effects of MR. We analyzed the correlations between the top 20 bacteria and rumen fermentation parameters, revealing that nine bacterial taxa had obvious relationships with rumen fermentation parameters. These bacteria were mainly related to A/P and isobutyric acid concentrations. This suggests that iso-butyric acid and A/P play important roles in the establishment of rumen function before weaning. Iso-butyric acid is a degradation product of proteins in the rumen, and a low concentration of it affects the growth and reproduction of microorganisms [50]. It was reported that the concentration of acetate in the rumen increased with isobutyric acid added to the diet in beef cattle, the concentration of propionic acid remained unchanged, and A/P increased [51]. It was found that the Lachnospiraceae_NK3A20_group was positively correlated with the butyric acid concentration in dairy cows with early lactation [52]. A/P is related to energy utilization and can affect the microbiota structure in the rumen, which is crucial for early breeding [53]. Guo et al. And it was found that Dioscorea feeding increases the A/P ratio and increases the abundance of g__Ruminococcus_1 [54]. Additionally, g__Saccharofermentans is a probiotic and is inversely correlated with propionate concentration [55]. Therefore, we believed that MR optimized the structure of the rumen flora and promoted rumen fermentation by regulating rumen fermentation products. We only discuss rumen microbes but not related studies of gut microbes and metabolomics in the present study, and also due to limited experimental conditions, yak calves were not observed for long enough, especially in the response of yak calves to solid diet after weaning, which would be worth more investigation in the future. ## 5. Conclusions Substituting MR completely replaced yak milk to feed yak calves, optimized the rumen microbiota structure, and ameliorated rumen fermentation by influencing fermentation products, thereby improving the survival rate of yak calves. These results support the positive impact of MR on early weaning and breeding in yaks. It provides an opportunity for the improvement of the yak calf survival rate and the expansion of farmers’ economic profits. ## References 1. Rehman M.U., Zhang H., Huang S., Iqbal M.K., Mehmood K., Luo H., Li J.. Characteristics of Integrons and Associated Gene Cassettes in Antibiotic-Resistant. J. Food Sci. (2017) 82 1902-1907. 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--- title: Physiologically Based Pharmacokinetic Modelling to Predict Pharmacokinetics of Enavogliflozin, a Sodium-Dependent Glucose Transporter 2 Inhibitor, in Humans authors: - Min-Soo Kim - Yoo-Kyung Song - Ji-Soo Choi - Hye Young Ji - Eunsuk Yang - Joon Seok Park - Hyung Sik Kim - Min-Joo Kim - In-Kyung Cho - Suk-Jae Chung - Yoon-Jee Chae - Kyeong-Ryoon Lee journal: Pharmaceutics year: 2023 pmcid: PMC10058973 doi: 10.3390/pharmaceutics15030942 license: CC BY 4.0 --- # Physiologically Based Pharmacokinetic Modelling to Predict Pharmacokinetics of Enavogliflozin, a Sodium-Dependent Glucose Transporter 2 Inhibitor, in Humans ## Abstract Enavogliflozin is a sodium-dependent glucose cotransporter 2 (SGLT2) inhibitor approved for clinical use in South Korea. As SGLT2 inhibitors are a treatment option for patients with diabetes, enavogliflozin is expected to be prescribed in various populations. Physiologically based pharmacokinetic (PBPK) modelling can rationally predict the concentration–time profiles under altered physiological conditions. In previous studies, one of the metabolites (M1) appeared to have a metabolic ratio between 0.20 and 0.25. In this study, PBPK models for enavogliflozin and M1 were developed using published clinical trial data. The PBPK model for enavogliflozin incorporated a non-linear urinary excretion in a mechanistically arranged kidney model and a non-linear formation of M1 in the liver. The PBPK model was evaluated, and the simulated pharmacokinetic characteristics were in a two-fold range from those of the observations. The pharmacokinetic parameters of enavogliflozin were predicted using the PBPK model under pathophysiological conditions. PBPK models for enavogliflozin and M1 were developed and validated, and they seemed useful for logical prediction. ## 1. Introduction Glucose is a critical substrate of metabolism in eukaryotic organisms, and the homeostasis of blood glucose levels is essential for preventing metabolic disorders, including diabetes. Glucose is freely filtered through the renal glomerulus and enters the tubular system of the kidney. However, in healthy individuals, filtered glucose is almost completely reabsorbed in the proximal tubule. Therefore, glucose is absent or present at very low concentrations in the urine, and the loss of glucose is minimized. Sodium-dependent glucose cotransporters (SGLTs) mediate glucose reabsorption against concentration gradients by coupling glucose transport and sodium transport. There are two well-known types of SGLTs in the kidney: SGLT1 and SGLT2 [1]. SGLT1 plays a minor role in renal glucose reabsorption [2]. Simultaneously, most of the glucose reabsorption in the kidney is mediated by the SGLT2, primarily localized in the S1 segment of the proximal tubule in the kidney [1,2,3,4]. Therefore, SGLT2 inhibitors have recently emerged as one of the most promising glucose-lowering therapeutic agents. By selectively inhibiting the tubular reabsorption of glucose, SGLT2 inhibitors promote the urinary excretion of glucose and lower blood glucose levels [1]. Enavogliflozin (DWP16001) is a selective SGLT2 inhibitor developed by Daewoong Pharmaceutical Co., Ltd. (Seoul, Republic of Korea) and approved on 30 November 2022 by the Ministry of Food and Drug Safety for clinical use in South Korea (product name: Envlo Tablet) [1,5]. In Phase I clinical trials, enavogliflozin showed rapid absorption with a peak plasma concentration occurring 1–3 h post-administration and a long terminal half-life of 13–29 h in single and repeated oral administrations [6]. The systemic exposure of enavogliflozin increased dose proportionally after repeated administrations in the dose range of 0.1–2.0 mg [6]. However, the fraction of urinary-excreted enavogliflozin was increased along with increasing dose after a single administration in the dose range of 0.2–5.0 mg (i.e., from $0.87\%$ to $1.67\%$) [6]. In this study, the PBPK model for enavogliflozin and M1 was developed based on the reported clinical trial data in the literature (ClinicalTrials.gov: NCT03364985), whose concentration-time profiles were collected after a single or repeated dosing of enavogliflozin [6]. Certain drug metabolites may be pharmacologically and/or toxicologically meaningful, and the United States Food and Drug Administration has suggested qualifying them when they are present more than 10 percent of total drug-related exposure [7]. Enavogliflozin appears to be metabolized in the human liver microsome system and generates metabolites, such as M1 (that is, (2S,3R,4R,5S,6R)-2-(7-chloro-6-(4-cyclopropylbenzyl)-2-hydroxy-2,3-dihydrobenzofuran-4-yl)-6-(hydroxymethyl)tetrahydro-2H-pyran-3,4,5-triol) and M2 (that is, (2S,3R,4R,5S,6R)-2-(7-chloro-6-(4-(1-hydroxycyclopropyl)benzyl)-2,3-dihydrobenzofuran-4-yl)-6-(hydroxymethyl)tetrahydro-2H-pyran-3,4,5-triol) [8]. In a previous clinical trial, the metabolic ratio of M1 was estimated between 0.20 and 0.25 after daily oral administration of 0.1 to 2.0 mg enavogliflozin in humans [6]. In this study, physiologically based pharmacokinetic (PBPK) models for enavogliflozin and M1 were developed and validated using the published concentration–time profiles of the compounds in humans. Enavogliflozin is believed to be a treatment option for patients with diabetes who have a high chance of suffering from hepatic impairment and nephrotic syndrome [9]. PBPK models can rationally predict concentration–time profiles compared to conventional compartment models for first-in-human, special populations, drug–drug interactions, and pathophysiological situations [10,11,12,13,14]. As quantitative measures of physiological changes have been reported in the patients with hepatic impairment [12], the developed PBPK model could be used in pharmacokinetic predictions for the special populations in further studies. The objective of this study was to develop and validate a PBPK model for orally administered enavogliflozin in humans. ## 2.1. Model Structure To predict compound concentrations, PBPK models for enavogliflozin and metabolite M1 were developed. Whole-body PBPK models consisted of 15 and 13 compartments for enavogliflozin and M1, respectively, including the arterial/venous blood pool and the major tissues (Figure 1). For the kidney compartments, mechanistically arranged kidney sub-compartments were assumed based on the anatomical structure of the tissues, as described in the mechanistic kidney model section below. The anatomical weight and blood flow rates of the tissues were obtained from published data (Davies and Morris, 1993; Brown et al., 1997) [13,15,16] and are summarized in Table 1. Numerical simulations of the PBPK models were performed using Berkeley Madonna software version 10.4.2 (Berkeley Madonna, Inc., Albany, CA, USA). In the present study, the fourth-order Runge–Kutta method was used for numerical integration. Because there were two PBPK models for the two compounds (enavogliflozin and M1), the compound for parameters were specified in a form of subscripts if it is needed. ## 2.2. Absorption A first-order kinetics was used to describe the absorption of enavogliflozin in humans. The differential equation for the enteral compartment (i.e., the absorption compartment) is:[1]dXadt=−Ka·Xa,enavo where Xa,enavo is the amount of enavogliflozin remaining in the absorption compartment (e.g., the intestinal lumen), and Ka is the first-order absorption rate constant. The initial amount of enavogliflozin in the absorption compartment was set to be the product of Fa (i.e., fraction absorbed, predicted as $86.6\%$), Fg (i.e., not metabolized fraction in the gastrointestinal tract, assumed as 1), and the administered dose. Drug permeability in the human jejunum was predicted by the empirical relationship between Caco-2 permeability (Papp; 10−6 cm/s) in vitro and jejunum effective permeability (Peff; 10−4 cm/s) in vivo using the following empirical correlation [17]:[2]log⁡Peff=0.4926×log⁡Papp−0.1454 In this study, the experimentally determined Caco-2 Papp value of enavogliflozin (2.4 × 10−6 cm/s) was scaled using propranolol as a reference compound (i.e., Papp was multiplied by a scaling factor of 2.8) to fit the literature’s values [17]. Subsequently, the fraction of the drug absorbed (Fa) was predicted using the relationship between the effective permeability (Peff) using the following equation and the reported value in the literature [18]:[3]Fa=1−e−2·Tresr·Peff where Tres is the transit time in the small intestine (~3 h) [18] and r is the radius of the small intestine. The first-order absorption rate (Ka) was also predicted by its relationship with the human jejunum effective permeability coefficient (i.e., Ka=2·Peff/r), in which the human intestinal tract is assumed to be a cylindrical tube. ## 2.3. Distribution For enavogliflozin and M1, a perfusion-limited distribution was assumed for all tissue compartments, except the liver model of enavogliflozin. For tissues following perfusion-limited distribution, the differential equation for non-eliminating organs (i.e., tissues except for the liver and kidney) was as follows:[4]VT·dCTdt=QT·Cart−CT·RKp where VT is the anatomical volume of the tissue compartment, CT and Cart are the enavogliflozin or M1 concentrations in the tissue and arterial blood compartments, respectively, QT is the blood flow to the tissue, R is the blood-to-plasma partition coefficient, and Kp is the tissue-to-plasma partition coefficient. For the lung compartment, the input blood flow was from the venous blood pool, and Cart in the equation above was substituted by the compound concentration in the venous blood pool [i.e., VLU·dCLUdt=QLU·Cven−CLU·RKp,LU]. For the liver compartment, the enavogliflozin concentration in the input blood flow could be estimated using the following equation:[5]QLI·Cin,enavo=Ka·Xa,enavo+QLI−QST−QSP−QSm,IN−QLa,IN·Cart,enavo+QST·CST,enavo·RenavoKp,ST,enavo+QSP·CSP,enavo·RenavoKp,SP,enavo+QSm,IN·CSm,IN,enavo·RenavoKp,Sm,IN,enavo+QLa,IN·CLa,IN,enavo·RenavoKp,La,IN,enavo where CST,enavo, CSP,enavo, CSm,IN,enavo, and CLa,IN,enavo are the enavogliflozin concentrations in the stomach, spleen, and small and large intestine, respectively; QLI, QST, QSP, QSm,IN, and QLa,IN are the blood flow to the liver, stomach, spleen, and small and large intestine, respectively; and Kp,LI,enavo, Kp,ST,enavo, Kp,SP,enavo, Kp,Sm,IN,enavo, and Kp,La,IN,enavo are the tissue-to-plasma partition coefficients for the liver, stomach, spleen, and small and large intestine for enavogliflozin, respectively. In the in vitro non-clinical study, enavogliflozin appeared to be a substrate for OATP1B1 and OATP1B3 transporters, and the respective Km values were 39.6 and 50.6 μmol/L in the transiently transporter-expressing HEK293 cells (Corning, Tewksbury, MA, USA). Permeability- and perfusion-limited models were integrated for the liver in the enavogliflozin model to describe the contribution of hepatic uptake transporters (e.g., OATP1B1 and OATP1B3). The integrated model, referred to as Model 1, is called the TUBE model by Jeong et al. [ 19,20] and is a generalized form of the extended clearance concept [21]. Passive diffusion was estimated from the published correlation between physicochemical properties and passive permeability [22]. Even though, there was some clue for the active transport into the liver, specific value for the active permeability term was optimized based on the clinical trial data [6]. The observed concentration-time profiles after a single oral administration of 1 mg enavogliflozin to humans [6] using nonlinear regression method incorporated in the Curve Fit function of Berkeley Madonna software version 10.4.2 after assuming a linear kinetics in the uptake process. The effective surface area was allometrically scaled from the literature (Table S1) [20,23]. The distribution fraction for enavogliflozin to the liver (fd,LI,enavo) was calculated as below:[6]fd,LI,enavo=1−e−PSinf,enavo·fup,enavoRenavo·QLI where PSinf,enavo is the uptake clearance from the extracellular compartment in the liver into hepatocytes for enavogliflozin. Consequently, the enavogliflozin in the liver compartment was calculated using the following equation:[7]VLI·dCLI,enavodt=QLI·{Cin,enavo·1−fd,LI,enavo+PSeff,enavoPSinf,enavo·fu,LI,enavofup,enavo·Renavo·CLI,enavo·fd,LI,enavo−CLu,int,enavo·fu,LI,enavo·CLI,enavo} where VLI is the anatomical volume of the liver and CLu,int,enavo is the intrinsic clearance of enavogliflozin in the liver compartment that was estimated from in vitro microsomal clearance using microsomal protein per gram of liver (e.g., 40 mg protein/g liver) and the liver weight [16,24]. fu,LI,enavo is the unbound fraction of enavogliflozin in the hepatocyte compartments estimated from the predicted liver-to-plasma partition coefficient using Rodgers and coworker’s method considering binding terms [25,26], and PSeff,enavo is the distributional clearance from the liver cells to extracellular space in the liver for enavogliflozin that consists of passive permeability. For M1, the compound concentration in the input blood pool was estimated as follows:[8]QLI·Cin,M1=QLI−QGut−QSP·Cart,M1+QGut·CGut,M1·RM1Kp,Gut,M1+QSP·CSP,M1·RM1Kp,SP,M1+CLu,int,enavo·fu,LI,enavo·CLI,enavo·fm,M1·MWM1MWenavo where Cin,M1, Cart,M1, CGut,M1, and CSP,M1 are the M1 concentrations in the input blood, arterial blood pool, gut, and spleen compartment, respectively; Kp,Gut,M1 and Kp,SP,M1 are the tissue-to-plasma partition coefficients for M1 in the gut and spleen compartments, respectively; fm,M1 is the fraction of metabolism which forms M1 from enavogliflozin as a result of the hepatic metabolism of enavogliflozin; and MWenavo and MWM1 are the molar masses of enavogliflozin and M1, respectively. Molar masses were necessary as the calculation was performed in the gram-based unit (i.e., not in mol unit). For the venous blood compartment, the following equation was used:[9]Vven·dCvendt=QAD·CAD·RKp,AD+QBR·CBR·RKp,BR+QHE·CHE·RKp,HE+QKI,out·CKI·RKp,KI+QLI·CLI·RKp,LI+QSK·CSk·RKp,SK+QBO·CBO·RKp,BO+QMU·CMU·RKp,MU+QRE·Cart−QCO·Cven where Vven is the anatomical volume of venous blood; CAD, CBR, CHE, CKI, CLI, CSk, CBO, CMU, and Cven are enavogliflozin or M1 concentrations in the adipose, brain, heart, kidney, liver, skin, bone, muscle, and venous blood compartments, respectively; QAD, QBR, QHE, QKI, QLI, QSK, QBO, QMU, and QRE are the blood flows to the adrenal gland, adipose, brain, heart, kidney, liver, skin, bone, muscle, and the residual blood flow, respectively; QCO is the cardiac output; and Kp,AD, Kp,BR, Kp,HE, Kp,KI, Kp,LI, Kp,SK, Kp,BO, and Kp,MU are the tissue-to-plasma partition coefficients of adipose, brain, heart, kidney, liver, skin, bone, and muscle, respectively, for enavoglifozin or M1. In the case of the kidney, the outflow of blood from the kidney was adjusted by the filtrate loss via the mechanistic kidney model (i.e., QKI,out=QKI,in−Qurine). The tissue-to-plasma partition coefficients (Kp) of the tissue compartments were predicted for enavogliflozin and M1 according to the method described by Rodgers and Rowland [25,26]. In this study, the Kp value of adipose tissue was predicted using the octanol-to-water partition coefficient for enavogliflozin (logPo:w) instead of the olive oil-to-water partition coefficient (logPvo:w) [25,26], as it provided a better fit to the observed data. The steady-state tissue-to-plasma concentration ratios (Kp,ss) were predicted using the predicted Kp ratios and extraction ratios for the liver (that is, Kp,ss=Kp·1−ERfd, where ER is the extraction ratio, and fd is the distributional fraction into the tissue [19]). Using the anatomical tissue volumes in Table 1 and the predicted Kp,ss values, the calculation of Vss was conducted using the following equation [27,28]: [10]Vss=Vp+Vrbc·EP+∑VT,iKp,ss,i where Vp and Vrbc are the volumes of plasma and blood cells, respectively, and EP is the blood cells-to-plasma partition coefficient. EP was calculated as follows [28]:[11]EP=1+(R−1)/Hct where Hct is the hematocrit (0.45) and R is the blood-to-plasma partition coefficient. The unbound fraction of enavogliflozin in the plasma (fup,enavo) was determined from the results of an experiment on 1 mg/mL enavogliflozin in human blood plasma using a Rapid Equilibrium Dialysis kit (Thermo Fisher Scientific, Waltham, MA, USA) after 4 h of incubation at 37 °C. The fup for M1 (fup,M1) was predicted by a published model (accessible at https://drumap.nibiohn.go.jp/; accessed on 3 January 2023), which was trained using a large dataset [29]. The blood-to-plasma partition coefficients (R) of enavogliflozin and M1 were predicted using ADMET Predictor software version 10.4 (Simulation Plus, Inc., Lancaster, CA, USA). Albumin was assumed to be the binding protein for enavogliflozin and M1 [12] because compounds are slightly acidic. The assumption was needed for the prediction of unbound fraction and blood-to-plasma partition coefficient in the patients with impaired liver [30]. The tissue bindings were adjusted using altered albumin concentrations and hematocrit values in the pathological condition. Tissue-to-plasma partition coefficients were adjusted using the altered unbound fraction in plasma, assuming that the unbound fractions in the tissues were not affected by the disease condition. ## 2.4. Elimination In this study, elimination in the PBPK model consisted of both hepatic and renal clearances. Hepatic metabolism was in vitro–in vivo extrapolated using the results of microsomal stability. The microsomal stability of enavogliflozin was observed temporally in a 0.25 mg microsomal protein/mL suspension with NADPH either with or without UDPGA. The unbound fraction of enavogliflozin and M1 in the microsomal suspension was predicted by ADMET Predictor software version 10.4.0.5 64-bit edition (Simulation Plus, Inc., Lancaster, CA, USA) for the 1 mg protein/mL condition and adjusted to the real experimental condition (0.25 mg protein/mL; i.e., fu,undiluted=1D1fu,diluted−1+1D, where D is the dilution factor in the system [31,32]). As only $3\%$ of a dose of the unchanged form was excreted as bile in bile duct-cannulated rats after oral administration of 14C-enavogliflozin [8], the contribution of bile elimination was neglected in the PBPK model for enavogliflozin. The amount excreted through the renal route occupied 0.87–$1.67\%$ of the total dose of enavogliflozin after a single dose in a clinical trial [6]. Thus, the contribution of renal excretion to the total elimination of enavogliflozin appeared to be minor. However, the kidney is thought to be a target tissue for enavogliflozin, and the fraction of renal excretion (fe) seems to increase with increasing doses [6]. To estimate the relative change in enavogliflozin concentration in the kidney, a mechanistically arranged kidney model was used. Non-linear reabsorption was incorporated into the kidney model based on the mechanistically arranged model [33,34,35]. M1 is a metabolite of enavogliflozin. In a previous study, enavogliflozin was not significantly eliminated in the intestinal microsomal suspension. Briefly, 95.7 ± $15.3\%$ or 111.1 ± $26.2\%$ of the initial enavogliflozin remained after incubating 2 μM enavogliflozin for 120 min at 37 °C in human intestinal microsomal suspensions with or without UDPGA in the system, respectively ($$n = 3$$), and there was no statistical difference among the measured % remaining in 5, 15, 30, 45, 60, and 120 min after incubation of enavogliflozin started in the intestinal microsome suspension ($p \leq 0.05$, one-way ANOVA). As enavogliflozin seemed to be metabolized primarily in the liver, the site of M1 formation was assumed to be the liver. The proportion of M1 formation (fm,M1) was estimated from the ratio between the elimination clearance of enavogliflozin in human liver microsomes and the formation clearance of M1 in human liver microsomes. The formation rate of M1 was obtained from human liver microsomes and recombinant enzymes in the literature [8]. The rate of M1 formation in recombinant enzymes was scaled by the P450 abundance (i.e., 142 pmol/mg protein for CYP3A4 and 14 pmol/mg protein for CYP2C19) and intersystem extrapolation factors (ISEF) for CYP3A4 and 2C19 from the literature [36]. The mean ISEFs for CYP3A4 and 2C19 were 0.154 and 0.248, respectively, based on the intrinsic clearance of the reference compounds in the literature (i.e., midazolam, testosterone and nifedipine for CYP3A4, and S-mephenytoin for CYP2C19) [36]. The calculated formation fractions of M1 were estimated from both the recombinant enzyme and the human liver microsome system and compared. The formation in the PBPK model incorporated the results from the two systems (i.e., microsomes, recombinant enzymes). The formation rate of M1 and M2 was calculated using the Michalis–Menten equation (CLu,HLM,(M1 or M2)=vmax,HLM,(M1 or M2)Km,HLM,(M1 or M2)·fu,mic,enavo+fu,LI,enavo·CLI,enavo, where CLI,enavo and fu,LI,enavo are the enavogliflozin concentration and unbound fraction in the liver, and vmax,HLM,(M1 or M2) and Km,HLM,(M1 or M2) are the maximum rate and Michaelis–Menten constants for M1 or M2 formation in the human liver microsomes) and reported constants [8]. The fraction of M1 and M2 formation (fm,M1 and fm,M2) was predicted dynamically, as follows:[12]fm,(M1 or M2)=CLu,HLM,(M1 or M2)CLu,int,mic,enavo where CLu,int,mic,enavo is the unbound intrinsic clearance of enavogliflozin elimination in the liver microsome. ( e.g., fm,M1=vmax,HLM,M1Km,HLM,M1·fu,mic,enavo+fu,LI,enavo·CLI,enavoCLu,int,mic,enavo). Since the unbound fraction in the recombinant enzyme system was not reported for enavogliflozin, the absolute formation clearance could not be converted from the recombinant enzyme to the microsome system. The contribution of isozymes were estimated using the scaled results of recombinant enzyme assay for the prediction of altered formation rate in the pathophysiological condition (e.g., fm,3A4=fm,M1·vmax,3A4,M1Km,3A4,M1vmax,3A4,M1Km,3A4,M1+vmax,2C19,M1Km,2C19,M1+fm,M2·vmax,3A4,M2Km,3A4,M2vmax,3A4,M2Km,3A4,M2+vmax,2C19,M2Km,2C19,M2). Altered elimination of enavogliflozin was predicted based on the reported model parameters with liver cirrhosis in the literature [12]. The changed activity of CYP2C19 enzyme is calculated from the reported plasma clearance of mephenytoin and formation of 4-hydroxymephenytoin [37], and functional liver mass [12] in the patients with liver cirrhosis. There were no accessible observations about M1 elimination. Metabolic rate and renal clearance for M1 were predicted using the published methods (accessible at https://drumap.nibiohn.go.jp/; accessed on 3 January 2023) [38,39]. The predicted microsomal intrinsic clearance for M1 was assumed to be unbound one, as the literature handled the intrinsic clearance with unbound concentration (that is, Equation [2] of the literature: CLh=Qh·fup·CLu,intQh+fup·CLu,int) [38]. ## 2.5. Mechanistic Kidney Model A mechanistic kidney model for enavogliflozin was developed to predict its non-linear urinary excretion mainly based on the model structures and values with slight changes reported by Pletz et al. [ 33] and Scotcher et al. [ 34,35]. Because the mechanistic kidney model in this study was utilized only for the enavogliflozin (Figure 1), the compound name was not specified on the name of model parameters for the kidney model. The mechanistic kidney model consists of 21 compartments, reflecting the physiological segmentations of the kidney [33,34,35]. The kidney is divided into four major segments (i.e., proximal tubule, loop of Henle, distal tubule, and collecting duct), which are further divided into subsegments (i.e., three subsegments for proximal tubule, one subsegment for the loop of Henle and distal tubule each, and two subsegments for the collecting duct). Each subsegment is divided into three compartments: tubular lumen, cellular compartment, and vascular blood section (Figure 1). The volumes and tubular flow rates of each segment of the kidney were obtained from the literature [33,34,35] and are listed in Tables S2 and S3. The unbound fraction in the kidney cells for enavogliflozin (fu,cell) was estimated from the predicted tissue-to-plasma partition coefficient using Rodgers and coworker’s method [25,26,30], which incorporated various binding terms. In the kidney model, the Michaelis–Menten kinetics model was assumed for non-linear reabsorption, which describes the observed non-linearity in the fraction of renal excretion (fe). The constants for the Michaelis–Menten equation (i.e., Km,reab and vmax,reab) and a secretionary clearance (CLsec) were optimized using the observed enavogliflozin amount in urine after a single oral administration of 0.2–5 mg enavogliflozin in humans (training set), and validated using the enavogliflozin concentration in urine after repeated administration of enavogliflozin in humans (validation set). A detailed description of the kidney sub-compartments is provided in Appendix A along with the mass-balanced equations (Equations (A1)–(A14)). ## 2.6. Modelling Strategies The results from the clinical trials were obtained from Daewoong Pharmaceutical Company and have already been published in an academic journal (ClinicalTrials.gov: NCT03364985) [6]. The observed concentration-time profiles were divided into two groups, the training and validation sets. During the model refinement process, results from a single-dose oral administration study of enavogliflozin ranging from 0.2 to 5 mg were used. For model validation, a repeated administration study for 15 days with doses ranging from 0.3 to 1 mg/day was used. There was no training set for the M1 model, and the M1 concentration-time profiles after repeated administration were utilized for model validation. The proposed PBPK model was validated by comparing the AUCinf, AUCτ (i.e., area under the plasma concentration–time curve from time zero to infinity at the single dosing regimen and a dosing period at the repeated dosing regimen, respectively), and Cmax (i.e., the maximum plasma concentration) values from the simulations to those from the clinical data of repeated administration studies. In the present study, the fold differences of the resulting AUC ratios (AUCpred:AUCobs) and Cmax ratios (Cmax,pred:Cmax,obs) within a factor of two (0.5–2) were considered adequate for model performance estimation [13]. In the case of enavogliflozin in urine, model performance was assessed based on the ratio between the simulated and observed excreted amounts at the last sampling time after a single administration. The mean amounts and concentrations were used as the observed values for the model validation. ## 2.7. Staticstics and Data Analysis Statistical differences between two groups were determined using Student’s t-test, and one-way ANOVA was used for multiple comparisons. In the present study, data were expressed as means ± standard deviation (S.D.), and p-values < 0.05 denoted statistical significance. Standard non-compartmental analysis was performed using WinNonlin software version 8.1 (Pharsight Corporation, Mountain View, CA, USA) and the web-based Blueberry service (accessible at https://pk-square.com; accessed on 3 January 2023). Microsoft Excel software version 2211 (Microsoft Corporation, Redmond, WA, USA) was used for the unpaired t-tests and visualization of the simulation. GraphPad Prism software version 9.5.0 (GraphPad Software, San Diego, CA, USA) was used to visualize the simulations. Web-based Chemicalize service (ChemAxon Kft., Budapest, Hungary; accessible at https://chemicalize.com/; accessed on 3 January 2023) was used to obtain several physicochemical properties. ## 3.1. Optimization of the PBPK Model The input parameters for the PBPK model were derived from in silico and in vitro studies and are summarized in Table 2. The kinetic parameters involved in absorption were derived from the Caco-2 permeability of enavogliflozin. Enavogliflozin was predicted to be rapidly absorbed (Ka value of 0.764 h−1) with good permeability through intestinal membranes (Fa value of 0.866). The unbound fraction in plasma (fup) was observed as 0.015 ± 0.002 for enavogliflozin and predicted as 0.080 for the metabolite M1 [29]. The extent of distribution was derived from the in silico prediction of tissue partition coefficients (Kp). The volumes of distribution at steady state (Vss) were predicted to be 1.44 L/kg for enavogliflozin and 0.431 L/kg for the metabolite M1. Preclinical data suggest that enavogliflozin is primarily eliminated by hepatic pathways, including metabolism and bile excretion. Indeed, phase I clinical data reports that renal excretion of enavogliflozin is negligible (less than $2.5\%$) in humans [6]. Therefore, the predicted metabolic clearance was assumed to be the only intrinsic clearance in the liver. The unbound fraction of enavogliflozin in microsomal suspension was predicted to be 0.577 in 1 mg protein/mL using ADMET Predictor software version 10.4.0.5 and adjusted to 0.845 in the 0.25 mg protein/mL condition after considering the dilution factor. The intrinsic clearance was obtained from an in vitro human microsomal stability assay (13.5 μL/min/mg protein), and the unbound clearance was calculated as 16.0 μL/min/mg protein for enavogliflozin. The unbound intrinsic clearance was incorporated into the model with physiological scalars (e.g., milligram protein per gram of the liver and liver weight in humans) [16,24]. There was no statistically significant difference in the intrinsic clearance of enavogliflozin with or without UDPGA in the human microsomal suspension based on the t-test ($$p \leq 0.329$$). The active uptake clearance (PSu,inf,act,enavo) was optimized as 9.73 L/h/kg using the observed concentration–time profiles after a single oral administration of 0.2 to 5 mg enavogliflozin orally in humans (training set; Figure 2). Renal excretion was predicted using a mechanistic kidney model that incorporated a non-linear reabsorption term for enavogliflozin in humans. The model parameters for the kidney were obtained after non-linear regression using the observed cumulative renal excretion after a single administration of enavogliflozin in humans. The obtained parameters were 0.0845 ng/mL, 305 ng/h and 3.39 L/h for Km,reab, vmax,reab, and the secretionary clearance (CLsec), respectively. Among the metabolites of enavogliflozin, the fractions for M1 and M2 formation (fm,(M1 or M2)) were estimated as $48.4\%$ and $10.4\%$ after comparing the intrinsic elimination clearance (13.5 μL/min/mg protein) for enavogliflozin and the formation clearance for M1 and M2 (6.53 μL/min/mg protein for M1 and 1.41 µL/min/mg protein for M2) in human microsomal suspension from the literature [8]. The fm for M1 and M2 was also calculated based on the results of M1 and M2 formation rate in the recombinant enzymes. As the ISEF-CLint and P450 abundance could be obtained from the literature [8,36], the results between the different isozymes (i.e., CYP3A4 and CYP2C19) were compared. The contribution of CYP3A4 for M1 and M2 formation were $94.4\%$ and $64.6\%$, respectively, which was comparable to the results using specific antibodies in the literature [8]. Those of CYP2C19 for M1 and M2 were $5.62\%$ and $35.3\%$, respectively. Thus, CYP3A4 and CYP2C19 appeared to cover $52.4\%$ and $6.42\%$ of enavogliflozin metabolism in the liver. For the PBPK model of M1, the compound’s elimination rate should be assigned. However, there were no accessible in vitro and in vivo experimental results for the metabolite M1. The unbound intrinsic clearance for M1 was predicted in silico to be 30.542 μL/min/mg protein [38]. The renal clearance was predicted in silico to be 42.27 mL/h/kg by the published method [39]. ## 3.2. Validation of the PBPK Model The proposed PBPK model captured the plasma concentration–time profiles of enavogliflozin (Figure 2) following a single dose (0.2–5 mg enavogliflozin) and repeated doses (i.e., the validation set of 0.3, 0.5, 1 mg/day for 15 days; Figure 3) in humans. The estimated AUCinf and Cmax ratios between simulated and observed values ranged from 0.901 to 1.25 and from 0.812 to 1.04, respectively, after the single administration of enavogliflozin (Table 3). When the proposed model was used to predict the systemic pharmacokinetics of enavogliflozin obtained from the validation dataset (Figure 3), the AUCτ and Cmax ratios for the first day of administration ranged from 0.811 to 1.05 and 0.712 to 0.869, respectively. In addition, the AUCτ and Cmax ratios for the last day of administration ranged from 0.758 to 0.880 and 0.660 to 0.727, respectively (Table 3). Furthermore, the concentration–time profiles of M1 were predicted using the developed PBPK model (Figure 4). Because there were no optimized parameters in the M1 model, there was no training set for the M1 model among the clinical data. The AUCτ ratio and Cmax ratio of M1 were predicted and compared to those of the observed parameters after repeated enavogliflozin dosing in humans (Table 4). The AUCτ ratio ranged from 0.762 to 1.06, and the Cmax ratio was between 0.641 and 0.829 for M1 in the range of repeated enavogliflozin doses. The AUC ratio and Cmax ratio were within the two-fold error range, which was assumed to be the acceptable range of the model performance in the method section. Collectively, the PBPK models developed in this study were found to be valid according to preset criteria. A mechanism-based kidney model for enavogliflozin was developed using the urinary excretion profile of the drug administered within the dose ranges of 0.2–5 mg. The cumulative observed amounts of enavogliflozin in urine were 1.71 ± 0.463, 5.85 ± 1.65, 12.7 ± 2.34, 32.0 ± 6.07, and 81.6 ± 27.9 μg at the last sampling time for excretion after the single administration of 0.2, 0.5, 1, 2, and 5 mg of enavogliflozin in humans, respectively (training set) [6]. The simulated cumulative amounts of enavogliflozin excreted in urine were 1.93, 5.69, 12.8, 29.8, and 85.2 μg after the single administration of 0.2, 0.5, 1, 2, and 5 mg of enavogliflozin, respectively, at the same time point (Figure 5) [33,34,35]. The simulated amount of urinary-excreted enavogliflozin was in the two-fold range of the observed value at the last sampling time after any single dosage examined in humans. ## 4. Discussion This was the first study for publication to simulate concentration–time profiles of enavogliflozin and its metabolite M1 based on PBPK models in humans. In this study, PBPK models for enavogliflozin and its metabolite M1 were developed and validated using in silico and in vitro data accompanied by clinical observations. The PBPK model developed in this study can be used to extend dosing regimens and predict drug–drug interactions and population-related alterations in the pharmacokinetic profiles of enavogliflozin in humans. For example, some marketed drugs require their dosing regimen to be adjusted or are not recommended for patients with hepatic or renal impairment [12,41,42,43]. Additionally, researchers involved in new drug development may need to predict the expected exposure or concentration profiles of the agent before clinical observation. The model-based prediction would have a role in that decision, especially the PBPK model, because of the physiological factors it accounts for, even though the prediction might be verified after clinical trials in the patient population. In a previous study, M1 was reported to have metabolic ratios (i.e., AUC ratio between M1 and enavogliflozin) of $25\%$, $21\%$, and $22\%$ for the repeated doses of 0.3, 0.5, and 1 mg/day, respectively [6]. Based on the AUCτ after the last dose of repeated administration study, the predicted metabolic rates for M1 were $18.8\%$, $16.2\%$, and $16.3\%$ for the 0.3, 0.5, and 1 mg/day doses, respectively. The model appeared to reproduce the slight difference in metabolic rates seen among those doses. For the calculation of the metabolic rate, the AUC values of enavogliflozin and M1 were converted to molar-based values (i.e., not a gram-based unit, but a mol-based unit was incorporated). Though there were Michaelis–Menten constants for those two isozymes, CYP3A4 and CYP2C19, the same contribution ratio among the dose range was assumed because of the absence of the unbound fraction in the recombinant enzyme system. The assumption may be reasonable because of the high Michalis–Menten constant for those two isozymes (Table 2). Although the metabolic fraction for the formation of M1 (fm,M1) was estimated from the in vitro assay, the volume of distribution (i.e., estimated by predicted Kp) and elimination rate for M1 [i.e., metabolism (CLu,int,M1) and renal excretion (CLr,M1)] were predicted using in silico methods [25,26,30,38,39]. Thus, the metabolic rate could be better predicted with more robust information on the formation, distribution, metabolism, and excretion of M1 (e.g., unbound fraction of enavogliflozin in the recombinant enzyme system, cumulatively excreted amount of M1 in vivo, and microsomal stability of M1 in vitro). In a published structure-activity relationship (SAR) study, hetero-bicyclic derivatives of enavogliflozin seemed to have similar IC50 values for SGLT2 and showed a difference in their selectivity between SGLT1 and SGLT2 [1]. However, there were no experimental IC50 values for the metabolite M1 in the SAR study. Further experiments and trials may be required to refine and extend the developed PBPK model along with pharmacodynamic model. The simulated concentrations or amounts of enavogliflozin in plasma and urine, respectively, seemed to match well with observed profile (Figure 2, Figure 3, Figure 4 and Figure 5), and the predicted pharmacokinetic parameters met the criteria (Table 3 and Table 4). Therefore, the developed PBPK model was validated using the established criteria in this study. As a model challenge, the absolute bioavailability was predicted for oral administration in humans. This predicted bioavailability ranged from $78.9\%$ to $79.0\%$ after a single dose of 0.2, 0.5, 1, 2 and 5 mg and at the steady-state after repeated doses of once-daily administration of 0.3, 0.5 and 1 mg enavogliflozin. Although there have been no clinical trials testing intravenous doses, the predicted oral bioavailability in humans is comparable to the reported values in the animal experiments, which were 84.5–$97.2\%$ in mice and 56.3–$77.4\%$ in rats [1,44]. Even though the absorption model had a simple structure (i.e., the first-order kinetics), the predicted exposure (AUC) and Cmax matched to the observed values well. However, a more sophisticated model for the absorption (e.g., CAT, A-CAT, and ADAM models) might be needed to study the absorption level alteration [45,46,47,48]. In the aspects of intestinal metabolism, there were experimental results for enavogliflozin using human intestinal microsome that showed no statistically meaningful elimination ($p \leq 0.05$, one-way ANOVA test for each measuring time) in the intestinal microsomal suspension with NADPH only or with both NADPH and UDPGA. Briefly, the percent remaining after incubation were 97.2 ± $24.2\%$, 109.8 ± $26.2\%$, 117.5 ± $27.8\%$, 96.4 ± $7.2\%$, 101.2 ± $22.9\%$, and 111.1 ± $26.2\%$ for 5, 15, 30, 45, 60, and 120 min, respectively, after the initiation of incubation with NADPH only, and 106.7 ± $3.8\%$, 110.2 ± $5.7\%$, 107.5 ± $10.2\%$, 87.2 ± $10.9\%$, 90.5 ± $10.1\%$, and 95.7 ± $15.3\%$ for 5, 15, 30, 45, 60, and 120 min, respectively, after the incubation starts with NADPH and UDPGA. Though there was no statistical significance among the measured percent remaining, the variability of the measure was larger than the results in the liver microsomal suspension, especially in the group with NADPH only. Because CYP enzymes had a meaningful contribution to the liver metabolism, there might be unseen contributions of the drug-metabolizing enzymes in the intestine. The elimination in the kidney can be attributed to excretion and metabolism [49]. In this study, renal elimination in the PBPK model of enavogliflozin was achieved via urinary excretion. Enavogliflozin revealed a dose-dependent increase in the fraction excreted in urine, and the kidney model for enavogliflozin incorporated nonlinearity in the reabsorption term. Additional observations for renal elimination can be incorporated into the kidney model for future studies, such as predicting the pharmacological effect of enavogliflozin based on pharmacodynamic modelling in humans. Despite this limitation, the PBPK model could simulate the cumulative amounts of urinary excretion of enavogliflozin in the preset range of error (i.e., 2-fold) after a single administration of the drug orally in humans (Figure 5). Based on the model simulation (Figure 6), the half-life at the terminal phase of steady-state were 15.9 h and 38.4 h in the plasma and kidney, respectively. The difference in half-life could be linked to the higher exposure of enavogliflozin in the kidney (i.e., the target organ) than in the plasma. The AUCτ for enavogliflozin in the kidney was predicted by the PBPK model as 100 ng∙h/g tissue at the steady state after 0.3 mg once daily dosing of enavogliflozin in humans, and the total and unbound kidney-to-plasma partition coefficients for enavogliflozin (i.e., Kp,ss,KI,enavo and Kp,uu,ss,KI,enavo, respectively) were predicted to be 2.67 and 8.49, respectively (Figure 6). The targeted exposure may be helpful in expanding the therapeutic window of enavogliflozin. Using the predicted unbound AUC in the kidney, the averaged unbound concentration of enavogliflozin at a steady state in the kidney (Cu,avg,ss,KI,enavo) was calculated after 0.3 mg/day oral dosing of enavogliflozin as 0.446 nmol/L (0.199 ng/mL), which was comparable to the reported IC50 in the previous SAR study (i.e., 0.46 nmol/L for SGLT2) [1]. Though the kidney model in this study could describe and predict in the expected range, there might be needs in the future to incorporate more mechanisms. For example, the kidney model in this study have multiple sub-compartments and physiological flows, but there are still missing physiologies, including bypass of blood flow and pH differences in the sub-compartments, which is included in the commercial model of Simcyp software (MechKiM) [50]. PBPK modelling is useful in a predictive study, including first-in-human dose prediction, drug–drug interaction, pediatrics, geriatrics, altered physiologies, and different ethnicities [10,11,12,14,24]. As enavogliflozin is mainly eliminated by hepatic metabolism, the validated PBPK model for enavogliflozin was challenged in hepatic-impaired patients. Pathophysiological changes in the patients are described in the literature [12], and the fractional activities assumed for CYP2C19 were 0.5, 0.3, and 0.3 in the patients with Child–Pugh score A, B, and C, respectively, for the model of Andrea Edginton and Stefan Willmann [12,37]. Various isozymes are involved in the metabolism of enavogliflozin, including CYP3A4, CYP2C19, UGT1A4, UGT1A9, and UGT2B7 [8]. The primary metabolites of CYP3A4 and CYP2C19 pathways seemed to be M1 and M2, and the estimated contribution of CYP3A4 in the formation of M1 and M2 in this study was comparable to the reported results of anti-CYP3A4 antibody study in the literature [8]. The other primary metabolites were appeared to be the generated by the other drug-metabolizing enzymes, such as UGT1A4, UGT1A9, and UGT2B7 [8]. Since UGTs were not reported as a consistent change in activities for the patients with hepatic impairment [37], the rest fraction, not metabolized to M1 and M2 ($41.2\%$), was assumed not to be affected by the activity alteration of CYP3A4 and CYP2C19 but to be affected only by the changes in the active liver mass under the liver impairments. Among the Child–Pugh classes, a PBPK model simulation was performed. AUCτ for enavogliflozin in plasma was 45.3 ng∙h/mL, 71.7 ng∙h/mL, and 103 ng∙h/mL, after orally administration of enavogliflozin 0.3 mg/day once daily in patients with Child–Pugh score of A, B, and C, respectively. The predicted AUCτ for the patients with scores of A, B, and C were $121\%$, $191\%$, and $273\%$, respectively, compared with the prediction for healthy individuals. Cmax were 3.76 ng/mL, 4.57 ng/mL, and 5.50 ng/mL in the patients with scores of A, B, and C, respectively, after the same dosing regimen. The predicted Cmax values were $87.0\%$, $106\%$, and $127\%$ compared with those predicted for healthy individuals. The predicted unbound fractions in plasma were 0.0187, 0.0222, and 0.0300 in the patients with the score A, B, and C, respectively, which were $123\%$, $146\%$, and $197\%$ of the fraction in the plasma for healthy individuals. The predicted parameters for enavogliflozin were in the range from $80\%$ to $125\%$ range [51] for the patients with mild hepatic impairment (Child-Pugh score A), but the drug would have quite different pharmacokinetic characteristics in the patients with Child–Pugh scores B and C. Estimation for the M1, a major metabolite, concentration may be needed in the population for the further studies, such as dose adjustments. ## 5. Conclusions In this study, PBPK models for enavogliflozin and M1 in humans were developed and evaluated using plasma concentration profiles from multiple clinical trials. For further study, a mechanistically arranged kidney model was developed, and the simulated unbound concentration of enavogliflozin in the kidney appeared to be relevant. The developed PBPK model may be useful for further pharmacokinetic and pharmacodynamic studies in humans. ## Appendix A.1. Blood Compartments In blood compartments, changes in drug concentrations are driven by blood flow through the segments and passive transport to the cellular compartments. For proximal tubular blood compartments, active transport to cellular compartments (i.e., secretion) was also incorporated. Differential equations for enavogliflozin in the blood compartments were: Glomerular Blood (i.e., Bowman’s Capsule) (A1)d(Cbcvas)dt=(Qkid·Car−Qkid−GFR·Cbcvas−GFR·fub·Cbcvas)/Vbcvas 2.Proximal Tubular Blood(A2)d(Cptvas,i)dt=Qkid−GFR·Cbcvas−Qkid−Qptlum,i+1·Cptvas,i−CLsec·Cptvas,i·fub+Ppd·SApt,i·Cptc,i·fucell−Cptvas,i·fub/Vptvas,i where i refers to the subsection of the proximal tubule from 1 to 3. For $i = 2$ or 3, (Qkid−Qptlum,i)·Cptvas,i−1 was used instead of Qkid−GFR·Cbcvas. 3.Blood at the Loop of Henle (A3) d(Clhvas)dt=Qkid−Qlhlum·Cptvas,3−Qkid−Qdtlum·Clhvas+Ppd·SAlh·Clhc·fucell−Clhvas·fub/Vlhvas 4.Blood at the Distal tubule (A4) d(Cdtvas)dt=Qkid−Qdtlum·Clhvas−Qkid−Qcdlum,1·Cdtvas+Ppd·SAdt·Cdtc·fu,cell−Cdtvas·fub/Vdtvas 5.Blood at the Collecting Duct(A5)d(Ccdvas,i)dt=Qkid−Qcdlum,i·Cdtvas−Qkid−Qcdlum,i+1·Ccdvas,i+Ppb·SAcd,i·Ccdc,i·fu,cell−Ccdvas,i·fub/Vcdvas,i where i refers to the subsection of the collecting duct from 1 to 2. For $i = 2$, Qkid−Qcdlum,i was multiplied with Ccdvas,i−1, and Ccdvas,i was multiplied with Qkid−Qurine instead of Qkid−Qcdlum,i+1.) ## Appendix A.2. Cellular Compartments In cellular compartments, the change in drug concentrations are driven by passive diffusion between the vascular compartment and the cells and cells and luminal compartments. For proximal tubular blood compartments, active transport from cellular (i.e., secretion) and luminal (i.e., reabsorption) compartments were also incorporated. Differential equations for enavogliflozin in the cellular compartments were: 6.Cellular Compartments at the Proximal Tubule (A6) dCptc,idt=CLsec·Cptvas,i·fub+Ppd·SApt,i·Cptvas,i·fub−Cptc,i·fu,cell+Vmax,reab·Km,reab+Cptlum,i·Cptlum,i+Ppd·SApt,i·Cptlum,i−Cptc,i·fu,cell/Vptc,i 7.The Cellular Compartment at Loop of Henle (A7) dClhcdt=Ppd·SAlh·Clhvas·fub−Clhc·fu,cell+Ppd·SAlh·Clhlum−Clhc·fu,cell/Vlhc 8.Cellular Compartments at the Distal Tubule (A8) dCdtcdt=Ppd·SAdt·Cdtvas·fub−Cdtc·fu,cell+Ppd·SAdt·Cdtlum−Cdtc·fu,cell/Vdtc 9.Cellular Compartments at the Collecting Duct (A9) dCcdc,idt=Ppb·SAcd,i·Ccdvas,i·fub−Ccdc,i·fu,cell+Ppd·SAcd,i·Ccdlum,i−Ccdc,i·fu,cell/Vcdc,i ## Appendix A.3. Lumenal Compartments The urine filtrate was assumed to flow through the kidney lumen. Differential equations for enavogliflozin in the lumenal compartments were as follows: 10.Glomerular Space (i.e., Bowman’s Capsule) (A10) dCbclumdt=(GFR·fub·Cbcvas−Qptlum1·Cbclum)/Vbclum 11.Lumen of Proximal Tubule(A11)d(Cptlum,i)dt=Qptlum,i·Cbclum−Qptlum,i+1·Cptlum,i−Vmax,reab·Km,reab+Cptlum,i·Cptlum,i+Ppd·SApt,i·Cptc,i·fu,cell−Cptlum,i/Vptlum,i where i refers to the subsection of the proximal tubule from 1 to 3. For $i = 2$ or 3, Qptlum,i was multiplied with Cptlum,i−1 instead of Cbclum. 12.Lumen at the Loop of Henle (A12) d(Clhlum)dt=Qlhlum·Cptlum,3−Qdtlum·Clhlum+Ppd·SAlh·Clhc·fu,cell−Clhlum/Vlhlum 13.Lumen at the Distal Tubule (A13) d(Cdtlum)dt=Qdtlum·Clhlum−Qcdlum·Cdtlum+Ppd·SAdt·Cdtc·fu,cell−Cdtlum/Vdtlum 14.Lumen at the Collecting Duct(A14)d(Ccdlum,i)dt=Qcdlum,i·Cdtlum−Qcdlum,i+1·Ccdlum,i+Ppd·SAcd,i·Ccdc,i·fu,cell−Ccdlum,i/Vcdlum,i where i refers to the subsection of the collecting duct from 1 to 2. For $i = 2$, Qcdlum,i was multiplied with Ccdlum,i−1 instead of Cdtlum. 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--- title: Fungal Secondary Metabolites/Dicationic Pyridinium Iodide Combinations in Combat against Multi-Drug Resistant Microorganisms authors: - Ayoub M. Abdelalatif - Bassma H. Elwakil - Mohamed Zakaria Mohamed - Mohamed Hagar - Zakia A. Olama journal: Molecules year: 2023 pmcid: PMC10058977 doi: 10.3390/molecules28062434 license: CC BY 4.0 --- # Fungal Secondary Metabolites/Dicationic Pyridinium Iodide Combinations in Combat against Multi-Drug Resistant Microorganisms ## Abstract The spread of antibiotic-resistant opportunistic microbes is a huge socioeconomic burden and a growing concern for global public health. In the current study, two endophytic fungal strains were isolated from Mangifera Indica roots and identified as Aspergillus niger MT597434.1 and Trichoderma lixii KU324798.1. Secondary metabolites produced by A. niger and T. lixii were extracted and tested for their antimicrobial activity. The highest activity was noticed against Staphylococcus aureus and E. coli treated with A. niger and T. lixii secondary metabolites, respectively. A. niger crude extract was mainly composed of Pentadecanoic acid, 14-methyl-, methyl ester and 9-Octadecenoic acid (Z)-, methyl ester (26.66 and $18.01\%$, respectively), while T. lixii crude extract’s major components were 2,4-Decadienal, (E,E) and 9-Octadecenoic acid (Z)-, and methyl ester (10.69 and $10.32\%$, respectively). Moreover, a comparative study between the fungal extracts and dicationic pyridinium iodide showed that the combination of A. niger and T. lixii secondary metabolites with dicationic pyridinium iodide compound showed a synergistic effect against Klebsiella pneumoniae. The combined formulae inhibited the bacterial growth after 4 to 6 h through cell wall breakage and cells deformation, with intracellular components leakage and increased ROS production. ## 1. Introduction The emergence of multidrug-resistant microorganisms has increased the urgency of finding effective new antimicrobials to treat bacterial, fungal, and viral illnesses in humans and animals [1]. β-lactam resistance emergence in Gram-negative bacteria has been a major concern that has become an obstacle in the treatment of infectious diseases, especially those caused by Klebsiella pneumoniae. Miryala et al. [ 2] studied the role of the SHV-11 gene in drug resistance mechanism patterns in a K. pneumoniae strain. It was concluded that the SHV11 gene, along with the functional partners, were not only responsible for the drug resistance mechanism, but also helped in maintaining the genomic integrity through the DNA damage repair mechanism. On the other hand, endophytic fungi are a broad collection of microorganisms that live either entirely or partially inside the cells of their host plants, invading healthy tissues with no outward sign of illness [3]. More and more chemicals with diverse biological functions are being extracted from endophytic fungi [4]. Natural products with biological functions which are called secondary metabolites and endophytic filamentous fungi are among the most prolific producers [4]. Many useful bioactive chemicals with antibacterial, insecticidal, cytotoxic, and anticancer activities have been isolated in the last two decades from endophytic fungi [5]. Alkaloids, terpenoids, steroids, quinolones, isocoumarins, lignans, phenylpropanoids, phenols, and lactones are some of the most common classes of fungal bioactive chemicals [6]. Antimicrobial action against a wide variety of microorganisms has been shown by Trichoderma sp., a fungal species present in many habitats [7]. Moreover, Aspergillus niger is one of the most well-known fungi, and has been isolated from several niches (soil, nuts and food). Extracellular enzymes and citric acid produced from A. niger are known as Generally Recognized As Safe for human consumption (GRAS) by the FDA because of their usage in several industrial settings [8]. Hence, A. niger has been considered a valuable resource for the biotechnological sector due to the abundance of secondary metabolites with immunomodulatory and cytotoxic properties against cancer cells [9]. On the other hand, chemically synthesized compounds, namely ionic liquids (ILs), are one of the most interesting scientific and technological advancements for their various applications over the last few decades. There have been significant developments regarding the relevance of these types of unique molecules with adjustable biological and industrial properties [10,11]. Initially, ionic liquids were identified as a combination of inorganic counter anions and organic counter cations. During the synthesis of ionic liquids, the generation of nitrogen-containing heterocyclic molecules contributes significantly [12]. In contrast, hydrazones have become significant molecules in modern chemical synthesis, garnering considerable interest. They were used in a variety of pharmaceuticals and chemotherapeutic drugs [13]. Their attachment to organic molecules plays a crucial role in essential biological processes and in the formulation of medications with a wide range of biological characteristics, including antibacterial [14], anticancer [15], anti-inflammatory [16], antifungal [17], and antitubercular [18] activities. Recently, dicationic ionic liquids (DiILs), a new category of the ILs family, has attracted a great amount of researchers’ attention as it represents an interesting variation of the cationic partner. DiILs consist of two head groups (cations) linked by a rigid or flexible spacer and two anions [19]. Hence, the aim of the present study was to synthesize a dicationic pyridinium iodide compound, and characterize and combine it with a biologically active natural product for its potential synergistic effect. ## 2.1. Molecular Identification of Fungal Isolates In the current study, two endophytic fungal strains were isolated from Mangifera Indica roots. The isolates were identified using ITS4 and ITS5 rRNA sequencing. The sequences obtained were compared with the nucleotide sequences of the international database. The isolated fungal strains were Aspergillus niger with GenBank accession number MT597434.1 ($100\%$ similarity) and Trichoderma lixii with GenBank accession number KU324798.1 ($98.18\%$ similarity). Furthermore, the phylogenetic tree was generated by performing a distance matrix analysis (Figure 1). ## 2.2. Antibacterial Activity of Fungal Bioactive Secondary Metabolites Data in Table 1 revealed that the inhibition zones (IZ) diameter of T. lixii and A. niger crude extracts ranged from 8.0 to 20.0 mm and from 7.5 to 21.0 mm, respectively, against the tested pathogens. Staphylococcus aureus and E. coli were the most susceptible organisms against A. niger and T. lixii crude extracts, respectively. Quang et al. [ 20] stated that A. niger metabolites have been considered as a promising source of antibiotics that inhibit the growth of the Gram-positive bacterium E. faecalis, with MIC values ranging from 32 to 64 mM, and of Candida albicans, with MIC values ranged from 64 to 128 mM. Meanwhile, Padhi et al. [ 21] revealed that A. niger metabolites showed antifungal activity against Candida albicans with IC50 31 mg/mL, and antibacterial activity against Pseudomonas aeruginosa, Escherichia coli and Staphylococcus aureus with IC50 of 160 mg/mL, 47 mg/mL and 135 mg/mL, respectively. Chigozie et al. [ 22] reported that the fungal extract of Aspergillus sp. isolated from fresh leaves of Mangifera indica. exhibited antibacterial activity against P. aeruginosa and E. coli. ## 2.3. GC-MS Analysis of Fungal Secondary Metabolites Data in Figure 2 proved that the A. niger crude extract was mainly composed of Pentadecanoic acid, 14-methyl-, methyl ester and 9-Octadecenoic acid (Z)-, and methyl ester (26.66 and $18.01\%$, respectively). However, the T. lixii crude extract’s relatively major components were 2,4-Decadienal, (E,E) and 9-Octadecenoic acid (Z)-, and methyl ester (10.69 and $10.32\%$, respectively) (Table 2). Venice et al. [ 23] stated that a GC-MS analysis of T. lixii crude extract identified the presence of 1,3,3-Trimethyl-Diepoxyhexadecane and 3-Octadecenoic acid compounds. An analysis of endophytes’ diversity has determined relationships among host plants and the endophytic fungi, through determining various secondary metabolites biosynthesized from the culture extract of the endophytic fungal isolates [23]. ## 2.4. Molecular Docking Study Among the most common mechanisms, the Extended-spectrum β-lactamases (ESBLs) were widely reported [24]. One of the main concerns is that resistance caused by these enzymes may result in an efficacy reduction of antimicrobial therapy, or in failed treatment [25]. The reported findings demonstrated that ESBL-variants of SHV-type were the most frequent mechanisms of resistance in ESBL-producing K. pneumoniae isolates implicated in bacteremia. Hence, the SHV enzyme was chosen in the present investigation to assess the possible mechanistic action of the synthesized dicationic pyridinium iodide compound, as well as the naturally extracted compounds. In the current study, molecular docking was performed to predict the binding affinity of the naturally extracted and chemically synthesized compounds toward the target ESBL enzyme SHV-1 (Table 3). The results of the docking studies showed an excellent binding manner with the active site of the target macromolecules, in comparison to the reference drug co-crystallized ligand LN1-255. The naturally extracted compounds showed higher binding scores when compared to the dicationic pyridinium iodide compound (−6.38 kcal/mol), where Pentadecanoic acid, 14-methyl-, methyl ester and 9-Octadecenoic acid (Z)-, methyl ester (extracted from Aspergillus niger) had −6.51 and −6.50 kcal/mol. Trichoderma lixii’s most potent compounds were 9-Octadecenoic acid (Z)-, methyl ester, 1,2-15,16-Diepoxyhexadecane and Heptadecane, 9hexyl, showing −6.96, −6.56 and −6.99 kcal/mol binding affinity, respectively. The binding interactions of the dicationic pyridinium iodide compound revealed that the dicationic pyridinium iodide compound was well oriented inside the enzyme pockets and showed hydrophobic interaction with Arg244, Ala280 and Tyr105. ## 2.5.1. Disc Diffusion Technique Data in Table 4 revealed that the combined action of A. niger crude extract with the dicationic pyridinium iodide compound was synergistic against all the tested pathogens except S. aureus, while the combined action of T. lixii crude extract with dicationic pyridinium iodide was synergistic only against K. pneumoniae (Figure 3). Hence, K. pneumoniae was selected for further analyses. ## 2.5.2. Checkerboard Dilution Technique Data in Table 5 proved that the combined actions of the dicationic pyridinium iodide compound with A. niger and T. lixii crude extracts were synergistic against K. pneumoniae, with FICI 0.35 and 0.4, respectively. The observed antibacterial effect was further investigated against K. pneumoniae based on the FICI and MIC values. ## 2.6. Mechanistic Action of the Combined Formula Transmission electron microscopic (TEM) study was applied to the treated cells of K. pneumoniae against the combined drugs (A. niger/dicationic pyridinium iodide and T. lixii/dicationic pyridinium iodide). Figure 4 revealed a breakage in the cell wall and deformation of the cells, with leakage of the intracellular components that lead to cell death. Moreover, A. niger/dicationic pyridinium iodide and T. lixii/dicationic pyridinium iodide combined drugs showed potent antibacterial activity by inhibiting the bacterial growth after 6 and 4 h, respectively (Figure 5). Moreover, the reactive oxygen species (ROS) study of the treated bacterial cells revealed that by increasing the formula concentration the ROS increased, which elaborated the cell membrane damage and reduced bacterial cells’ viability (Figure 6). Guo et al. [ 26] studied the antibacterial activity of Aspergillus niger crude extract (fraction B10) against Agrobacterium tumefaciens T-37 with an inhibition percentage of $98.22\%$, and the dose required to achieve $50\%$ inhibition was 0.035 0.018 mg/mL. The antibacterial mechanism was evaluated by using electric conductivity, the release of proteins and nucleic acids, sodium dodecyl sulphate–polyacrylamide gel electrophoresis (SDS–PAGE), and the detection of reactive oxygen species (ROS). An increase in the relative electric conductivity of the supernatant was noticed with the addition of Aspergillus niger crude extract B10, which indicated that there was electrolyte transfer from the intracellular to the extracellular matrix. In contrast to the control group, the B10 fraction treated group showed a high increase in the amount of extracellular nucleic acid and protein between 0 and 18 h, and damage in the cytoplasmic membranes was noticed. SDS–PAGE analysis showed that the amounts of extracellular protein and nucleic acid were consistent with the lower levels of total protein inside the cells. It was demonstrated that B10 was responsible for the rise in ROS. On the other hand, Qiao et al. [ 27] revealed that aspermerodione extracted from the endophytic fungus Aspergillus sp. TJ23 showed a synergistic effect with β-lactam antibiotics oxacillin and piperacillin as potent antibacterial combinations against MRSA. It was reported that combination therapy can be used as a promising strategy for combatting MRSA through extending the lifespan and efficacy of the currently employed antibiotics. The present investigation may pave the way into combating microbial infections through natural/synthetic combinations. ## 3.1. Tested Pathogens Pseudomonas aeruginosa, Acinetobacter baumannii, Proteus vulgaris, Staphylococcus aureus, Escherichia coli, Klebsiella aerogenes and Klebsiella pneumoniae were kindly provided and identified by El-Shatby pediatric hospital using the Vitek 2 automated system (bioMerieux, Marcy l’Etoile, France) at the Medical Research Center, Faculty of Medicine, Alexandria University. The tested pathogens were kept in brain–heart infusion glycerol broth at −4 °C for further investigations, with monthly transfer into fresh media. The tested pathogens were identified as multi-drug resistant according to CLSI guidelines (Table S1). ## 3.2. Endophytic Fungal Isolation Fungal samples were isolated from the roots of fully matured and healthy plants of Mangifera Indica at El Nubaria, Alexandria (30°41′57″ N, 30°40′1″ E), with firmed leaves and well-formed fruits, leaves and root systems. The root samples were rinsed with running tap water followed by deionized water and subsequently dipped in $70\%$ ethanol (1–2 min), followed by sterilization in $0.1\%$ sodium hypochlorite (2–3 min). They were further dipped in $70\%$ ethanol and finally rinsed with distilled water. The roots were allowed to dry, and were cut aseptically into small pieces (1 cm2) and patched onto potato dextrose agar (PDA) (Himedia, Mumbai, India) plates containing streptomycin (SRL, Mumbai, India) at a concentration of 250 μg/mL to prevent bacterial contamination [28]. ## 3.3. Molecular Identification of the Fungal Isolates Fungal isolates were identified through ITS based DNA sequencing using the conserved ITS region of fungal gDNA amplified by general primers ITS4 (5′-TCCTCCGCTTATTGATATGC-3′) and ITS5 (5′-GGAAGTAAAAGTCGTAACAAGG-3′). ITS sequences of the identified fungi were submitted to GenBank for the retrieval of their accession numbers [28]. The study of percentage identity of the aligned sequences was carried out using a Kolmogorov–Smirnov statistical test in GeneDoc (version 2.7). Using the obtained sequences, phylogenetic analysis was performed and a phylogenetic tree was constructed through MEGA (v10.1.8) by the maximum likelihood Bootstrap (MLBS) method. ## 3.4. Seed Culture Preparations and Extraction of Fungal Secondary Metabolites Spore suspension seed cultures were prepared according to CLSI guidelines [29]. Fungal isolates were inoculated (mycelial plugs (1 × 1 cm2)) into 300 mL potato-dextrose broth then incubated for 21 days at 25 °C under shaken conditions (140 rpm). At the end of the incubation period, the mycelia were harvested through filtration and the filtrate was extracted with chloroform/methanol (2:1, v/v) for 4 h. The crude fungal extract containing the bioactive compounds was stored at 4 °C for further experimental processes [28]. ## 3.5. Antibacterial Activity of Fungal Secondary Metabolites Antibacterial activity was carried out using the disc-diffusion method; the discs were saturated with 25 µL of each fungal extract (20 mg/mL) and placed on the surface of inoculated Müeller–Hinton agar plates [30]. Further antibacterial activity evaluation was carried out by assessing the minimal inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values [31]. MIC and MBC evaluations were performed through mixing 80 μL of sterile Müeller–Hinton broth, 20 μL tween 80, and 100 μL of the fungal secondary metabolites one at a time. The mixture was then diluted serially using a two-fold dilution in a 96-well microtiter plate. Then, 100 μL of 0.5 McFarland of the tested bacterial suspensions was inoculated in each well. MIC is the minimum concentration of the tested drugs that inhibited the bacterial growth, while the MBC is the minimum concentration needed to completely kill the microbial cells [32]. ## 3.6. GC-MS Analysis of Fungal Secondary Metabolites For the GC-MS analysis, 2 µL of samples were injected into the GC-MS device equipped with a spitless injector and a PE Auto system XL gas chromatograph interfaced with a Turbo-mass spectrometric mass selective detector system. The MS was operated in the EI mode (70 eV) with helium as the carrier gas (flow rate 1 mL/min) and an analytical column HP (length 30 mm−0.20 mm, 0.11 mm film thickness). The MS was operated in the total ion current (TIC) mode, scanning from m/z 30 to 400. The bioactive compounds were identified by comparing their retention time (RT in min) and mass spectra with the library of the National Institute of Standards and Technology (NIST), USA [33]. ## 3.7. Chemical Synthesis of Dicationic Pyridinium Iodide Compounds A mixture of 4-pyridinecarboxaldehyde (10 mmol) in ethanol (30 mL) and isonicotinic acid hydrazide [1] (10 mmol) with a few drops of hydrochloric acid was heated under reflux for 1 h. The solid obtained after the solvent evaporation under pressure was recrystallized from ethanol to furnish the desired Schiff base 2. The 4(2-iodoethoxy)benzene (10 mmol) was added under stirring to a solution of dipyridine Schiff base 2 (5 mmol) in acetonitrile (30 mL). Then, the reaction mixture was heated under reflux for 8 h, until the consumption of the starting material was indicated by TLC (silica gel, hexane-ethyl acetate). The solvent was reduced by evaporation under reduced pressure; the product formed was collected by filtration to afford the desired dicationic pyridinium iodide [3] (Scheme 1) [19]. ## 3.7.1. Characterization of the Prepared Dicationic Pyridinium Iodide (3) mp: 82–83 °C. 1H NMR (400 MHz, DMSO-d6): δH = 4.54 (t, 4H, $J = 8$ Hz, 2 × NCH2), 5.18 (t, 4H, $J = 8$ Hz, 2 × OCH2), 6.94–6.96 (m, 6H, Ar-H), 7.31 (dd, 4H, $J = 4$ Hz, 8 Hz, Ar-H), 8.24 (d, 0.5H, $J = 4$ Hz, Ar-H), 8.33 (d, 0.5H, $J = 4$ Hz, Ar-H), 8.48 (d, 1.5H, $J = 4$ Hz, Ar-H), 8.63 (d, 1.5H, $J = 4$ Hz, Ar-H), 8.71 (s, 0.75H, H-C-N), 8.84 (s, 0.25H, H-C-N), 9.08 (d, 0.5H, $J = 4$ Hz, Ar-H), 9.22 (d, 1.5H, $J = 4$ Hz, Ar-H), 9.35 (d, 0.5H, $J = 4$ Hz, Ar-H), 9.45 (d, 1.5H, $J = 4$ Hz, Ar-H), 12.89 (s, 0.25H, CONH), 13.28 (s, 0.75H, CONH). 13C NMR (100 MHz, DMSO-d6): δC = 60.22, 60.90 (2 × NCH-), 66.43, 66.54 (2 × OCH-), 115.11, 121.94, 125.19, 126.76, 130.08, 144.95, 146.38, 147.05, 147.51, 149.69 (Ar-C), 157.93, 160.34 (C=N, C=O) ## 3.7.2. Molecular Docking The crystal structure of SHV-1 β-lactamase (Pdb: 3D4F), available at RCSB Protein Data Bank, was used as a template for constructing the 3D models [34]. ## Database Generation and Optimization The ChemDraw application was used to draw the test compounds, and the MOE software database was utilized to gather these compounds once they had been drawn. Displaying hydrogen, computing partial charges, and using the default energy minimization were the three methods that were used in the optimization of the database. After the triangular matcher algorithm ligand was applied to the setting of the ligand placement, the default scoring function was employed to obtain the top five non-redundant poses that had the lowest binding energy of the test compound. In order to record the most effective potential molecular interactions, the docking of the optimized database was carried out using the induced fitting methodology. The docking score, expressed in Kcal/mol, was determined by combining the results of two different scoring functions—namely, alpha hydrogen bonding and London dG forces. The acquired results were organized into a list based on the S-scores that had an RMSD value of less than 2. The correctness of the employed software is heavily reliant on the training set, and the results of the molecular docking may be confirmed using a training set of experimental ligand–protein complexes. In order to guarantee a genuine and dependable docking strategy, the software that is being used needs to be able to reproduce the binding mode of an established reference inhibitor for the enzyme that is being targeted. The co-crystallized ligand LN1-255 was chosen as the comparison standard for the docking study in the experiment as a positive control (reference values). In the end, conformers that had the greatest binding scores and the best ligand–enzyme interactions were detected and examined [35]. ## 3.8. Combination Study between the Fungal Extracts and the Synthesized Dicationic Pyridinium Iodide Compound Combination studies were carried out according to White et al. [ 36]. The disc diffusion method was used to assess the possible differences in the inhibition zone diameter upon mixing the fungal extracts and the synthesized dicationic pyridinium iodide compound (1:1 w/w). Furthermore, the broth microdilution checkerboard technique was employed to study the synergistic effect between the fungal extract (Agent A) and dicationic pyridinium iodide compound (Agent B). Two-fold serial dilutions of the fungal extract and dicationic pyridinium iodide compound were dispensed in a 96-well microtiter plate with sub-MIC concentration. A 100 µL quantity of the bacterial suspension (1.5 × 106 CFU/mL) was dispensed into each well and incubated for 24 h at 35 ± 2 °C. The fractional inhibitory concentration index (FICI) was computed, with the following equation:FICI=FIC of agent A+FIC of agent B where FIC of agent A=MIC of antimicrobial agent A in combinationMIC of antimicrobial agent A alone FIC of agent B=MIC of antimicrobial agent B in combinationMIC of antimicrobial agent B alone FICI was considered as a synergistic when it was ≤0.5, and as additive when it was >0.5–1, indifferent when it was ≥1–4.0 and antagonistic when it was >4 [31]. ## 3.9.1. Transmission Electron Microscopic (TEM) Examination of the Treated Microbial Cells On the basis of FIC and FICI values, the most susceptible bacterial strain (K. pneumoniae) was treated with the combined drugs. Samples were fixed using a universal electron microscope fixative. A series of dehydration steps were followed using ethanol and propylene oxide. The samples were then embedded in labeled beam capsules and polymerized. Thin sections of cells exposed to extracts were cut using LKB 2209-180 ultra-microtome and stained with a saturated solution of uranyl acetate for half an hour and lead acetate for 2 min [31]. Electron Micrographs were taken using a Transmission Electron Microscope (JEM-100 CX Joel). ## 3.9.2. Time-Kill Curve A time-kill curve was investigated to estimate the optimum time required to inhibit the bacterial vegetative cells. Fungal secondary metabolites combined with the dicationic pyridinium iodide compound (FIC and FICI values of each) were added one at a time to 10 mL Müeller–Hinton broth containing 1 × 106 CFU/mL bacterial cells. Aliquots were withdrawn to assess the bacterial growth through different incubation time (0, 2, 4, 6, 8, 12 and 24 h) at OD 600 nm [37]. ## 3.9.3. Reactive Oxygen Species (ROS) Study The reactive oxygen species (ROS) generation assay was measured according to Almotairy et al. [ 38] and Bhuvaneshwari et al. [ 39] using 2,7-dichlorofluorescin diacetate (DCFH-DA) dye by comparing the extracellular ROS of the treated and control bacterial cells. ## 4. Conclusions In the current study, two endophytic fungal strains with antimicrobial activities were isolated from Mangifera Indica roots and identified as Aspergillus niger MT597434.1 and Trichoderma lixii KU324798.1. A dicationic pyridinium iodide compound was synthesized and then evaluated for its potential synergistic effect with the extracted fungal crude extract. The molecular modeling study revealed that the synthesized dicationic pyridinium iodide compound and the extracted fungal secondary metabolites showed promising inhibitory effects against the SHV-1 enzyme. The combination of A. niger and T. lixii secondary metabolites with the dicationic pyridinium iodide compound showed a synergistic effect against K. pneumoniae. Fungal secondary metabolites combined drugs inhibited the bacterial growth after 6 and 4 h through cell wall breakage and cells’ deformation with intracellular components leakage and increased ROS production, which led to bacterial cell death. This study proved the importance of the combination of fungal secondary metabolites and some synthetic drugs against multi-drug resistant microbial cells through several modes of action, which may pave the way to more available naturally derived options. ## Figures, Scheme and Tables Figure 1: Phylogenetic tree of A. niger MT597434.1 (A) and Trichoderma lixii* KU324798.1 (B).* Figure 2: GC-MS chromatogram of Aspergillus niger (A), and Trichoderma lixii* (B).* Figure 3: The combined effect of dicationic pyridinium iodide compound with T. lixii crude extracts (A) and A. niger (B) against K. pneumoniae. Figure 4: Transmission electron microscopic micrograph of K. pneumoniae untreated control (A), T. 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--- title: 'Nutritional Assessment of Plant-Based Meat Alternatives: A Comparison of Nutritional Information of Plant-Based Meat Alternatives in Spanish Supermarkets' authors: - Lucía Rizzolo-Brime - Alicia Orta-Ramirez - Yael Puyol Martin - Paula Jakszyn journal: Nutrients year: 2023 pmcid: PMC10058979 doi: 10.3390/nu15061325 license: CC BY 4.0 --- # Nutritional Assessment of Plant-Based Meat Alternatives: A Comparison of Nutritional Information of Plant-Based Meat Alternatives in Spanish Supermarkets ## Abstract Since the classification of processed meat as carcinogenic by the International Agency for Research on Cancer (IARC) in 2015, an increase in consumption of plant-based meat alternatives (PBMAs) has been observed worldwide. This occurs in a context characterized by concern for health, animal welfare, and sustainability; however, evidence of their nutritional quality is still limited. Therefore, our objective was to evaluate the nutritional profile and processing degree of PBMAs available in Spain. In 2020, products from seven Spanish supermarkets were analyzed for their nutritional content and ingredients. Of the 148 products, the majority were low in sugars but moderate in carbohydrates, total and saturated fat, and high in salt. The main vegetable protein sources were soy ($\frac{91}{148}$) and wheat gluten ($\frac{42}{148}$). Comparatively, $\frac{43}{148}$ contained animal protein, the most common being egg. Overall, PBMAs had a long list of ingredients and additives, and they were classified as ultra-processed foods (UPFs) according to the NOVA system. This study shows that the PBMAs available in Spanish supermarkets have a variable nutritional composition within and between categories. Further research is needed to determine if replacing meat with these UPFs could be a good alternative towards healthier and more sustainable dietary patterns. ## 1. Introduction In October 2015, the International Agency for Research on Cancer (IARC) released a report that classified unprocessed red meat as “probably carcinogenic” and processed meat as “carcinogenic” to humans based on the association between consumption of red and processed meat and colorectal cancer [1]. In this context, there has been an increasing number of people removing meat from their diets, or at least reducing its consumption, and asking for alternative products [2,3,4]. Consequently, there has been a considerable need to increase the offer of plant-based meat alternative products (PBMAs) to please consumers. In fact, plant-based products sales increased $49\%$ from 2018 to 2020 in Europe [5] and, in Spain alone, the sales volume of PBMAs increased by $32\%$ from 2019 to 2020 [6]. This trend has been observed worldwide as reported in studies done in the UK, Brazil, Norway, the US, Australia and Germany [7,8,9,10,11,12]. Among the reasons for the growing consumption of PBMAs, however, in addition to the health issues, is also concern for animal welfare, greenhouse gas emissions, and overall environmental impacts attributed to meat production [13]. Curiosity and interest in trying new products has also been identified as a fundamental reason for why consumers are motivated to try plant-based products [14]. Currently, despite the nutritional information on PBMAs, there is need for a regulatory framework to allow the population to have better food choices [15]. Furthermore, manufacturers frequently use nutrition and health claims on food labels to emphasize the positive nutritional attributes of their products, which can influence consumer purchasing and food choices [16]. Additionally, although there is some evidence that PBMAs may contain similar amounts of calories, protein and iron as the meats they are supposed to replace [17] and some studies show that PBMAs may have a relatively better nutritional composition [18], there is not sufficient evidence to consider them healthier than their meat counterparts. In fact, most of the available PBMAs are manufactured in the form of sausages, burgers or nuggets and contain higher amounts of sodium, oil and additives, including coloring, flavoring and binding agents, in comparison to unprocessed meats [19,20]. Several studies have shown that the avoidance of animal-based food appears to be associated with the introduction of ultra-processed PBMAs over more natural plant sources, compromising the general quality of a plant-based diet [21,22,23]. Moreover, ultra-processed food has been associated with several health problems, like overweight and obesity, as well as metabolic syndrome prevalence, LDL cholesterol, risk of hypertension, and higher risks of cardiovascular, coronary heart, and cerebrovascular diseases [24,25]. NOVA is a food classification system based on the degree of processing. In general, the classification criteria are based on the nature, extent, and purpose of industrial processing [26,27]. Thus, our aim was to evaluate the nutritional composition and processing degree and to perform a quantitative analysis of the ingredients of PBMA products currently available in Spanish supermarkets. ## 2.1. Product Description and Classification Between September 2020 and December 2021, a sampling of PBMAs was conducted in seven of the most common supermarket chains in Spain, namely Alcampo, Aldi, Carrefour, Dia, El Corte Inglés, Lidl and Mercadona. These chains are well positioned throughout the country and were chosen to represent choices available to the majority of the Spanish population [28]. For each product, the following data were collected: name, list of ingredients, nutritional content, and organic or conventional farming. In terms of nutritional content, the following information was collected: calories, carbohydrates, sugars, proteins, total fat, saturated fat, salt, and fiber per 100 g of product. This information was obtained from the nutritional label of the product packages (through photographs) and double-checked from the website where the product was published. Spanish PBMAs were categorized into eight different food groups according to their format characteristics: [1] plant-based sausages, [2] plant-based nuggets and breaded food, [3] plant-based meatballs, [4] vegetarian cold cuts, [5] veggie patties, [6] “Beyond Meat-type” hamburger patties, [7] “Chicken-type” strips (vegan/vegetarian products made from soy), and [8] plant-based mince. Each item was classified into a single main group, based on the similarity to meat-based products and dishes. Products excluded from the study were those vegetarian foods not specifically created to mimic meat products, such as tofu, tempeh, seitan and falafel. In order to classify the products by their nutritional composition, we used nutritional claims from AESAN [29] (Table 1). However, in some cases, the UK’s FoP labeling [30] was used (according to the nutrition claims of EU Nutrition and Health Claims Regulation legislation (EC) $\frac{1924}{2006}$) [31] in order to categorize the products based on the content of total fat, saturated fat and salt as shown in Table 2. To classify the products according to the degree of processing, we used the NOVA system [26,27] and the four groups currently described: 1. Unprocessed or minimally processed foods; 2. Foods with a simple or basic processing; 3. Moderately processed foods and 4. Ultra-processed foods. ## 2.2. Statistical Analysis Descriptive statistics (median, minimum and maximum) of energy and selected nutrients (carbohydrates, sugars, fat, saturated fat, protein, sodium and dietary fiber) were calculated per 100 g. As expected, there was missing information about dietary fiber and iron, unless specifically added to these products. Groups were assigned according to their main ingredients and similar characteristics to comparable processed meat products. The statistical analysis was performed using the statistical software Rstudio Desktop version 4.1.2, with the significance level set at $p \leq 0.05.$ ## 3. Results Overall, 176 plant-based meat alternatives were identified, but due to the repetition of some products in the different Spanish supermarkets, we analyzed a total of 148 individual products. Alcampo supermarket had the largest number of products on offer ($$n = 54$$), whereas the other supermarkets had lower quantities of products available (Aldi $$n = 28$$, Carrefour $$n = 30$$, El Corte Inglés $$n = 24$$, Dia $$n = 5$$, Lidl $$n = 26$$ and Mercadona $$n = 11$$). Table 3 shows the plant-based product categories analyzed in this study. The products were classified into eight different categories according to their similarity to comparable processed meats. Veggie patties were the group most found in supermarkets ($\frac{29}{148}$), followed by plant-based meatballs ($\frac{25}{148}$), plant-based sausages ($\frac{21}{148}$), “Beyond Meat-type” hamburger patties ($\frac{20}{148}$), vegetarian cold cuts ($\frac{17}{148}$), plant-based mince ($\frac{17}{148}$), “Chicken-type” strips ($\frac{10}{148}$) and plant-based nuggets and breaded food ($\frac{9}{148}$). We evaluated every group in order to compare quantitative and qualitative information and estimate the degree of processing using the NOVA classification system. ## 3.1. Ingredient Analysis Table 4 summarizes the main ingredients of the products analyzed. The main protein sources of these products diverged greatly depending on the item. The most common was soy protein ($\frac{91}{148}$), used in a variety of forms, including concentrated soy protein, isolated soy protein, hydrolyzed soy protein and texturized soy protein. The second most common was gluten ($\frac{42}{148}$). A variety of whole grains and flours such as black beans, chickpeas, rice, spelt, corn and quinoa were present in $\frac{64}{148}$ of the products. However, $\frac{43}{148}$ of the products contained some type of animal protein, making them non-vegan products. The main animal protein sources were egg white and milk. Overall, vegetarian cold cuts were the category that had more animal protein content in their ingredients, followed by plant-based nuggets and breaded food, and plant-based meatballs. With regard to fat, only a few products reported the percentage of the main oil that they contain. The most common was sunflower oil, present in $\frac{101}{148}$ of the products, followed by rapeseed oil, reported in $\frac{44}{148}$ of the items. The use of saturated fats like coconut oil or palm oil was significantly lower ($\frac{15}{148}$ and $\frac{2}{148}$, respectively). Only $\frac{8}{148}$ of the products contained olive oil exclusively in their formulation and $\frac{5}{148}$ of the products had a combination of olive oil and sunflower or rapeseed oil. Egg yolk was present in $\frac{9}{148}$ products, making them non-vegan. Considering carbohydrate sources, wheat flour was the most common ingredient, present in $\frac{64}{148}$ of the products. Only $\frac{11}{148}$ of the products were fortified with iron and $\frac{10}{148}$ with vitamin B12. Overall, only $\frac{21}{148}$ of the products were fortified. ## 3.2. Organic Farming There was a diversity of the percentages of the products labeled as organic (Table 5) in the different categories, but the majority of the products available in the supermarkets were produced conventionally. Organic vegetable protein was found in $\frac{52}{148}$ of the products, whereas $\frac{45}{148}$ contained organic fat and only $\frac{3}{148}$ of products contained organic animal protein. ## 3.3. Nutritional Composition Table 6 shows the nutritional information by group as the median (minimum and maximum) per 100 g of product across each category. The average energy was 215 kcal/100 g. Plant-based mince had the highest value (320 kcal/100 g) followed by plant-based sausage (254 kcal/100 g), plant-based nuggets and breaded food (229 kcal/100 g), and veggie patties (201 kcal/100 g), whereas “Chicken-type” strips had the lowest energy (154 kcal/100 g). Regarding the protein content, the average was 15.0 g/100 g, with vegetarian cold cuts showing the lowest content (7.30 g/100 g) and plant-based mince the highest (47.30 g/100 g). Total carbohydrates ranged from 2.65 g to 17.9 g/100 g. Plant-based nuggets and breaded food (17.9 g/100 g), veggie patties (15.6 g/100 g) and plant-based mince (13.0 g/100 g) contained the highest amounts. Sugars were generally low (<5 g/100 g) and only plant-based mince had a moderate content (5.80 g/100 g). Almost all products can be considered a source of fiber (>3 g/100 g). In regard to total fat and saturated fat, the average values, 10.0 g/100 g and 1.30 g/100 g, respectively, can be considered moderate. Most products were upper-moderate to high in salt (>1 g/100 g), with vegetarian cold cuts having the highest content (2.00 g/100 g) and excepting the plant-based mince group, which presented the lowest (0.07 g/100 g) [30]. According to the NOVA classification system, $93.9\%$ of the products were categorized as ultra-processed food (Group 4) and the remaining $6.08\%$ of PBMAs were categorized as processed food (Group 3, for the plant-based mince group). ## 4. Discussion According to recent studies, PBMA consumption is growing worldwide, reflecting a shift to a diet rich in vegetables and low in animal protein [32,33]. The recent report of the WHO’s International Agency for Research on Cancer (IARC) in which processed meat has been classified as carcinogenic for humans (Group 1) and red meat as a probable cause of cancer (Group 2A) in humans [1] has caused a great concern within the scientific community as well as for consumers. Alternative strategies for change include reducing the size of meat pieces or increasing the consumption of vegetable proteins [32]. As a consequence, there is a new market niche that includes PBMAs, and the impact of these products on customers’ daily food decisions has increased. Although more studies assessing the nutritional profile and healthiness of PBMAs are being published [18,34,35], to our knowledge, the present study is the first that not only describes the nutritional composition but also the processing degree of PMBAs available in Spanish supermarkets and, in addition, is the first to provide a quantitative analysis of the ingredients of these PBMAs. Our findings indicate that PBMAs are quite widespread in Spanish supermarkets (176 products available in seven supermarkets analyzed). This is in agreement with the worldwide trend of increased consumption of PBMAs and with the fact that this type of products is in demand, accepted and used not only by vegetarians and vegan consumers, but is also included in omnivore diets [36,37]. However, although PBMA consumers demand these products for reasons like health, animal welfare, the environment and rejection of meat, there is still not enough evidence to support that all plant-based products are as healthy and/or sustainable as they appear to be. As seen in our results, most PBMAs contained high salt and the vast majority were classified as UPFs according to the NOVA system. A study by Hu et al. [ 38] found that replacing meat with a plant-based substitute does not necessarily reflect a healthy dietary pattern. Khandurpur et al. [ 39] reported that within vegetarian diets, vegans were the largest consumers of UPFs, followed by lacto-ovo vegetarians and pescatarians. Recent studies have shown that consumption of UPFs is associated with greater caloric intake, weight gain and, thus, negative health outcomes [40,41]. Our results agree with other studies which examined the nutritional information of PBMAs, reporting similar energy values [8,12]. Similarly, according to the British Nutrition Foundation (BNF), PBMAs had medium energy density (1.5–4 kcal/g) [42]. Taking into account that weight gain is associated with excessive energy intake [43], energy derived from consumption of PBMAs should be considered by policy makers when implementing actions that promote consumption of fresh or minimally processed plant-based products in order to prevent secondary diseases [44]. The total fat and saturated fat in PBMAs were moderate and varied substantially in all categories. The most common fat sources for the majority of products were sunflower oil and rapeseed oil. It has been shown that sunflower oil induced an increase of different proinflammatory markers [45] and that intake of polyunsaturated fatty acids (PUFA-fatty acid identified in sunflower oil) was highest in vegans, followed by pescatarians, semi-vegetarians and vegetarians, and lowest in meat-eaters [46]. Even though the PBMAs showed a moderate fat content, overconsumption can lead to a diet high in fat which can be associated with unfavorable changes in gut microbiota, fecal metabolic profiles and plasma proinflammatory factors, which could have unfavorable consequences for long-term health outcomes [47]. Our results agreed again with other studies; for example, in the plant-based sausages category, which shows similar total fat ranges [8,11,12] as well as common fat sources [11,48]. Regarding proteins, the main protein sources in Spanish PBMAs were soy and gluten, which agrees with other studies done on products found in Germany or Brazil [12,49]. Unfortunately, these two vegetable proteins are considered common allergens [50,51]. According to the SEOM (Sociedad Española de Oncología Médica), plant-based nuggets and breaded and veggie patties had a medium content of proteins (10–15 g/100 g), whereas “Beyond Meat-type” hamburger patties, plant-based meatballs, plant-based sausages, “Chicken-style” strips and plant-based mince had a high content (>15 g/100 g) [52]. On the other hand, it has been shown that plant protein, as a part of plant-based diet, is associated with improvements in body composition and reduction in both body weight and insulin resistance [53]. Interestingly, many products contained combinations of different protein sources, including animal protein. This fact is important in order to make a good, safe and true nutritional claim for the vegan population. In this context, leghemoglobin (LegH) protein from soy, an analogue of myoglobin, performs a crucial role: when it is cooked, it unfolds, releasing, similarly to myoglobin, the heme cofactor to catalyze reactions that result in the variety of compounds that define the exceptional aroma and flavor of meat [54]. Moreover, the heme cofactor of LegH is identical to the heme found in animal meat [55]. Some studies have evaluated the safety of LegH, establishing a no-observed-adverse-effect level of 750 mg/kg/d LegH, which is over 100 times greater than the 90th percentile estimated daily intake [54]. On the other hand, one third of the products had methylcellulose (E461) added to their ingredients. It has been shown that after an overdose of methylcellulose, or for people who are allergic to it, problems like hives, breathing difficulty, and/or swelling of the face, lips, tongue or throat can occur [56]. PBMAs showed variable content in carbohydrates and were low in sugars due to the presence of pulses in their ingredients. Pointke et al. [ 12] reported a similar overall carbohydrates and sugars content. Our results also agreed with Bryngelsson et al. [ 48] in the plant-based nuggets and breaded foods category. PBMAs may be responsible for contributing a part of the carbohydrates and sugars in diets, as they are added as flours or starches as well as gums. Salt content was substantially high in most PBMAs. The WHO recommends consuming less than 5 g/day [57]. Considering the categorization of foods by their salt content, only the category of plant-based mince had a low salt content, and the category of vegetarian cold cuts had a high content of salt. Different studies have shown similar results in relation to high salt content in PBMAs [11,58]. At the end of 2020 in Spain, consumption of salt peaked at $14.8\%$ [59]. It has been observed that about $75\%$ of dietary salt comes from consuming processed foods, so it is an important aspect to consider for consumers’ nutrition guidelines [60]. As PBMAs continue to grow in their number of product categories as well as consumer acceptance, it is important to highlight the need for nutrition guidelines in their development. In addition to comparing the nutritional facts of PBMAs, they were also categorized using the NOVA classification. Results have shown that almost $94\%$ of the products were classified as UPFs (4. Ultra-processed foods). The NOVA classification is one of the most referenced in the literature and it has been applied in several countries [61]; however, it has been notably criticized for problems with the correct definition of ultra-processed food, for example: it does not define critical nutrients, it does not allow micronutrient intake to be quantified, and some examples do not match with the classification, among others. Nevertheless, PBMAs are characterized as an ultra-processed food [62], a type of products which is associated with noncommunicable diseases or their risk factors [63,64,65]. In general, UPFs are high in unhealthy types of fat, free sugars and salt and refined starches, are energy-dense, and are poor sources of dietary fiber, protein and micronutrients [66]. For these reasons, it is important to provide consumers with adequate information that reflects not only the nutritional quality of the products, but the processing level too. The present study is the first that describes the nutritional composition and processing degree of PMBAs available in Spanish supermarkets. In addition, it provides a quantitative analysis of the ingredients of Spanish PBMAs, allowing the comparison of the nutritional quality between and within the eight categories. However, some limitations should be mentioned. First of all, we did not include all supermarket chains in the study, nor all products that are exclusively found in vegan specialty stores. Further research is needed to identify some nutrition gaps, such as the micronutrient content and bioavailability, protein quality and digestibility, and dietary fiber type found in PBMAs. ## 5. Conclusions This study shows that a great number of plant-based meat alternative products available in Spanish supermarkets have a variable nutritional composition depending on the product category. There exists a false belief about the healthiness of these products because of their plant origin. Although PBMAs may show medium to high contents of vegetable protein and can be considered sources of dietary fiber, the majority of these products also meet the criteria of ultra-processed food, so their consumption should be sporadic within a plant-based diet with fresh vegetables, fruit and legumes. After a closer examination, both nutritional and quality information about PBMAs is needed to develop guidelines to counsel consumers about including these products in a healthy plant-based diet. To our awareness, the present study was the first one to focus on plant-based meat alternatives available in Spanish supermarkets, analyze the nutritional information, and estimate NOVA classifications for these products. Further research is needed to determine if replacing processed or unprocessed foods with plant-based meat alternatives in people’s diets can eventually lead to healthier dietary patterns. ## References 1. 1. International Agency for Research on Cancer. 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--- title: The Successive Next Network as Augmented Regularization for Deformable Brain MR Image Registration authors: - Meng Li - Shunbo Hu - Guoqiang Li - Fuchun Zhang - Jitao Li - Yue Yang - Lintao Zhang - Mingtao Liu - Yan Xu - Deqian Fu - Wenyin Zhang - Xing Wang journal: Sensors (Basel, Switzerland) year: 2023 pmcid: PMC10058981 doi: 10.3390/s23063208 license: CC BY 4.0 --- # The Successive Next Network as Augmented Regularization for Deformable Brain MR Image Registration ## Abstract Deep-learning-based registration methods can not only save time but also automatically extract deep features from images. In order to obtain better registration performance, many scholars use cascade networks to realize a coarse-to-fine registration progress. However, such cascade networks will increase network parameters by an n-times multiplication factor and entail long training and testing stages. In this paper, we only use a cascade network in the training stage. Unlike others, the role of the second network is to improve the registration performance of the first network and function as an augmented regularization term in the whole process. In the training stage, the mean squared error loss function between the dense deformation field (DDF) with which the second network has been trained and the zero field is added to constrain the learned DDF such that it tends to 0 at each position and to compel the first network to conceive of a better deformation field and improve the network’s registration performance. In the testing stage, only the first network is used to estimate a better DDF; the second network is not used again. The advantages of this kind of design are reflected in two aspects: [1] it retains the good registration performance of the cascade network; [2] it retains the time efficiency of the single network in the testing stage. The experimental results show that the proposed method effectively improves the network’s registration performance compared to other state-of-the-art methods. ## 1. Introduction Image registration is one of the basic tasks in medical image processing. It involves the acquisition of a dense deformation field (DDF) when a moving image is matched with a fixed image so that the two to-be-aligned images and their corresponding anatomical structures are aligned accurately in space [1]. The traditional registration method optimizes the cost function through a large number of iterations, a process that usually requires a significant amount of computation and time [2]. With the popularization and application of deep learning in the field of medical image registration, the deep learning registration method is now faster than the traditional image registration method. Therefore, for moving and fixed images, deformation fields can be generated by training a neural network, thus achieving rapid registration for a forward pass in the testing stage. Fan et al. [ 3] studied the computational costs of seven different deformable registration algorithms. The results showed that the assessed deep-learning network (BIRNet) without any iterative optimization needed the least time. Additionally, the registration accuracy improved after applying the deep learning method. For example, Cao et al. [ 4] proposed a deep learning method for registering brain MRI images, and it was revealed that the method’s Dice coefficient was improved in terms of registering white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). The unsupervised learning image registration method has been widely applied because it is not difficult to obtain gold-standard registration [5]. Balakrishnan et al. [ 6] optimized the U-Net neural network by defining the loss function as a combination of the mean square error similarity measure and the deformation field’s smoothing constraint. de Vos et al. [ 7] accomplished affine and deformable registration by superimposing several networks through unsupervised training. Kim et al. [ 8,9] used cyclic consistency to provide implicit regularization for maintaining topology and realizing 2D or 3D image registration. Moreover, a multi-scale strategy was adopted during the experiment to solve the relevant storage problem. Jiang et al. [ 10] proposed an unsupervised network framework (MJ-CNN) that adopted a multi-scale joint training scheme to achieve end-to-end optimization. Kong et al. [ 11] designed a cascade-connected channel attention mechanism network. During cascade registration, the attention module is incorporated to learn the features of the input image, thereby improving the expression ability of the image features. Through five iterations of the deformation field, improved bidirectional image registration was realized. Yang et al. [ 12] used multiple cascaded U-Net models to form a network structure. In their structure, each U-Net is trained with smooth regularization parameters to improve the accuracy of 3D medical image registration. Zhu et al. [ 13] helped a network develop high-similarity spatial correspondence by introducing a local attention model and integrated multi-scale functionality into the attention mechanism module to achieve the coarse-to-fine registration of local information. Ouyang et al. [ 14] trained their designed subnetworks synergistically by training the residual recursive cascade network to realize cooperation between the subnetworks. Through the connection of the residual network, the registration speed was accelerated. Guo et al. [ 15] improved the image registration accuracy and efficiency of CT-MR and used two cyclic consistency methods in a full convolution neural network to generate the spatial deformation field. Sideri-Lampretsa et al. [ 16] considered that it was easy to obtain edge images, so they used the image’s edges to drive the multimodal registration training process and thus help the network learn more effective information. Qian et al. [ 17] proposed a cascade framework of a registration network, and then registered images in training stages. The authors compared the performance of the cascade network framework with the traditional registration methods, subsequently, it was determined that the registration efficiency of the proposed method was significantly improved. Golkar et al. [ 18] proposed a hybrid registration framework of vessel extraction and thinning for retinal image segmentation, which improved the registration accuracy of complex retinal vessels. Inspired by the idea of two-person zero-sum game from game theory, Goodefellow et al. [ 19] proposed a generation adversarial network (GAN) that used two neural networks for adversarial training and continuously improved the performance of the network in all directions during a game between the two networks. In addition to the in-depth study of the generative adversarial network (GAN), the application of an adversarial network has been integrated with techniques and aims from other fields, for instance, the combination of GAN and image processing. Therefore, GANs are also widely used in image registration. Santarossa et al. [ 20] used generation adversarial networks combined with ranking loss for multimodal image registration. Fan et al. [ 21,22] implemented a GAN in the unsupervised deformable registration of 3D brain MR images. In this approach, the discrimination network identifies whether a pair of images are sufficiently similar. The resulting feedback is then used to train the registration network. Simultaneously, GANs have been applied to single- and multi-mode image registration. Zheng et al. [ 23] used a GAN network to realize symmetric image registration and then transformed the symmetric registration formula of single- and multi-mode images into a conditional GAN. To align a pair of single-mode images, the registration method constitutes a cyclical process of transformation from one image to another and its inverse transformation. To align images with different modes, mode conversion should be performed before registration. In the training process, the method also adopts the semi-supervised method and trains using labeled and unlabeled images. Many registration methods have been produced based on the application of generation adversarial networks [24,25,26,27,28]. Huang et al. [ 29] fused a difficulty perception model into a cascade neural network composed of three networks. These networks are used to predict the coarse deformation field and the fine deformation field, respectively, so as to achieve accurate registration. GANs showed excellent performance in the aforementioned studies. In the previous study, a GAN based on dual attention mechanisms was proposed, which showed good registration performance in areas with relatively flat edges, but poor registration performance in narrow and long-edge areas. To this end, based on previous research, this paper proposes a method to assist GANs in realizing the registration of long and narrow regions at the peripheries of the brain, which differs from the methods of coarse registration and fine registration. Our main contributions are summarized as follows:During training, the cascade networks are trained simultaneously to save network training time. The second network is used as a loss function. The mean square error loss function added to the second network can constrain the deformation field output by the second network such that it tends to 0. Only the first network is used during testing, which saves testing time. Coupled with the adversarial training of GANs, the registration performance of the first network is further improved. The rest of this paper is organized as follows. Section 2 introduces the networks proposed in this paper in detail. Section 3 introduces the experimental datasets and evaluation indicators. Section 4 introduces the experimental results obtained from the HBN and ABIDE datasets. In Section 5, we provide a discussion. Finally, the conclusions are given in Section 6. ## 2. Methodology This paper proposes a method combining adversarial learning with cascade learning. Joint training of cascaded networks can allow them to predict more accurate deformation fields. The first (registration) network is used to study the deformation field ϕ1. The second (augmented) network enables the first network to learn more deformations. A discrimination network improves the first network’s performance through adversarial training. The structures of each cascading network are similar to those of VoxelMorph [6]. The proposed overall learning framework is illustrated in Figure 1. ## 2.1. First (Registration) Network The registration network is the first network in cascading framework. Its inputs are the fixed image F and the moving image M. Its output is the deformation field ϕ1, i.e., ϕ1=G(F,M). This network realizes the alignment from M to F, i.e., F = M(ϕ1), where M(ϕ1) is the warped image. Subsequently, the loss function between M(ϕ1) and F is calculated to drive the training process. This loss function includes three parts: intensity similarity loss Lsim, adversarial loss Ladv, and smooth regularization term Lsmooth. The adversarial loss function of the registration network is:[1]Ladvp=−log⁡1−p,c∈P+−log⁡p,c∈P− where p is the output value of the discrimination network and c indicates the registration network input. Local cross-correlation metric is used to calculate the similarity of the intensity between fixed image F and warped image M(ϕ1). The specific formula of the loss function is:[2]CCF,Mϕ1=∑p∈Ω(∑pi(Fpi−F(p))(Mϕpi−M(ϕp)))2(∑piFpi−Fp2)(∑pi(Mϕpi−M(ϕ(p)))2) where pi denotes the iteration of the n3 volume center at voxel p, and Ω represents a three-dimensional voxel. In this paper, $$n = 9$$ Fpi, and M(ϕ1(pi)) represents the voxel intensities of F and M(ϕ1) at pi, respectively. F(p) and M(ϕ1(p)) are the local mean values of n3 volume. A higher CC indicates a more accurate alignment. According to the definition of CC, the intensity similarity loss Lsim is defined as follows:[3]LsimF,Mϕ1=−CC(F,M(ϕ1)) Additionally, L2 regularization is implemented to smooth the deformation field ϕ1:[4]Lsmoothϕ1=∑p∈Ω∇ϕ1(p)2 ## 2.2. Successive (Augmented) Network The inputs of the successive network are F and M(ϕ1); the output is DDF ϕ2. ϕ2 is used to deform M(ϕ1) to obtain ϕ2(M(ϕ1)). Simultaneously, to clarify the warped image, we perform a composed operation on ϕ1 and ϕ2, i.e., ϕ1°ϕ2. M(ϕ1°ϕ2) is obtained by the moving image M with the composed DDF. Next, two intensity loss functions, namely, Lsim(F,M(ϕ1°ϕ2)) and Lsim(F,ϕ2(M(ϕ1))), are calculated between M(ϕ1°ϕ2) and F and between ϕ2(M(ϕ1)) and F, respectively. The DDF ϕ2 is also constrained as it approaches zero deformation field through the following MSE loss function, allowing the deformation field ϕ1 to learn more accurate deformations. The formula of MSE loss function is defined as:[5]Lmseϕ2= Lmseϕ2,0=∑p∈Ω∇ϕ2(p)2 Through this function, the output effect of the first network can achieve fine registration after the two networks are connected in series. The loss function for the registration network is as follows:[6]LG=Ladv (p)+αLsim(F,M(ϕ1))+λLsmooth(ϕ1) In addition, the loss function used by the second network is:[7]LA=LsimF,Mϕ1+Lsim(M(ϕ1°ϕ2))+LsimF,ϕ2Mϕ1+ Lmse ϕ2+Lsmooth ϕ1+Lsmooth ϕ2+Lsmooth(ϕ1°ϕ2) The total loss function is:[8]Ltotal=LG + LA ## 2.3. Discrimination Network The discrimination network consists of four convolutional layers combined with leakyReLU activation layers. Finally, the sigmoid activation function is used to output the probability value. The discrimination network is shown in Figure 2. The discrimination network distinguishes the authenticity of image. The harder it is to distinguish the warped image from the fixed image, the harder it is to judge the authenticity of the image by the discrimination network. ## 3.1. Experimental Details Python and TensorFlow were used to implement the experimental process. The program was trained and tested with GPU NVIDIA GeForce GTX 2080 Ti [30]. In the training process, the patch-based training method is adopted to reduce the occupied memory. Herein, 127 blocks are obtained from each image with a size of 182 × 218 × 182. Each block size is 64 × 64 × 64. The stride is 32. The learning rates for training the registration and discrimination networks are set to 0.00001 and 0.000001, respectively. The traditional methods of Demons and SyN are used as comparative experiments. The deep learning model VoxelMorph is also trained. VoxelMorph is a model of medical image registration based on unsupervised learning. Therefore, VoxelMorph is selected as the comparative experiment for deep learning. The Dice score, structural similarity, and Pearson’s correlation coefficient are used as the evaluation indicators to verify the superiority of the experimental results. Moreover, the influence of the MSE and Lsim loss functions on the experimental results is investigated. ## 3.2. Datasets To prove the flexibility and superior performance of the proposed method, the HBN [31] and ABIDE datasets [32] are used for training and testing. The HBN dataset consists of brain data obtained from patients with ADHD (aged 5–21 years). Herein, 496 and 31 T1-weighted brain images are selected for training and testing, respectively. ABIDE is a dataset consisting of brain images from patients with autism (aged 5–64 years). Herein, 928 and 60 T1-weighted brain images are used for training and testing, respectively. The fixed image used in training comprises a pair of images randomly selected from the training set such that each image is linearly aligned to the fixed image. The image size of both the HBN and ABIDE datasets is 182 × 218 × 182 voxels with a resolution of 1 × 1 × 1 mm3. Both these datasets contain segmentation marker images of CSF, GM, and WM. ## 3.3.1. Dice Score The Dice coefficient (Dice) index is used to evaluate the degree of overlap between a warped segmentation image and the segmentation image of the fixed image. This index reflects the similarity between the experimental and the standard segmentation images. It is defined as follows:[9]Dice=2Xseg∩YsegXseg∪Yseg where Xseg and Yseg represent the standard and warped segmentation images, respectively. The range of Dice values is 0–1, corresponding to a range in the gap between the warped and the standard segmentation images progressing from large to small values, respectively. Alternatively, the closer the experimental result is to 1, the more similar the warped segmentation image is to the standard segmentation image, and the better is the registration result. ## 3.3.2. Structural Similarity The structure similarity index measure [33] can measure the similarity of two images. The SSIM is calculated as:[10]SSIMX,Y=(2μXμY+c1)(2σXY+c2)(μX2+μY2+c1)(σX2+σY2+c2) where X, Y represent the two input 3D images; μX and μY represent the average value of X and Y, respectively. σX2 and σY2 are the variances of X and Y, respectively. σX and σY represent the standard deviation of X and Y, respectively. σXY represents the covariance of X and Y. c1 and c2 are constants used to avoid system errors caused by a denominator equal to 0. The SSIM can measure the structural similarity between the real and warped images. A SSIM value close to 1 indicates that the two images have a high degree of similarity. ## 3.3.3. Pearson’s Correlation Coefficient Pearson’s correlation coefficient (PCC) was used to measure the similarity between two 3D images. The calculation formula of PCC is:[11]ρ(X,Y)∑$i = 1$n(Xi−X−)(Yi−Y−)∑$i = 1$n(Xi−X−)2∑$i = 1$n(Yi−Y−)2 The closer the value of PCC is to 1, the greater is the correlation. A PCC of 0 indicates no correlation. X, Y refer to the two input 3D images. X− and Y− represent the mean value of X and Y, respectively. ## 4. Results The proposed methodology is compared with the following approaches: [1] Demons and SyN, two traditional registration methods; [2] Voxelmorph (VM), an unsupervised deep learning registration method; and [3] VM + A, a method consisting of a simultaneously trained registration network and augmented network. First, the proposed GAN method (VM + A + GAN) is compared with Demons and SyN, which are two traditional methods. Table 1 and Table 2 summarize the test results obtained through different datasets, and all indicators show that our experimental results are the best. Figure 3 shows the comparison of the test results of the two datasets. The first row of the experimental image represents the original image obtained from the HBN dataset, and the second row represents the segmentation image corresponding to the original image derived from the HBN dataset. Similarly, the third row represents the original image based on the ABIDE dataset, and the fourth row represents the segmentation image corresponding to the original image derived from the ABIDE dataset. Compared with Demons and SyN, the image obtained by the proposed GAN method is closer in appearance to the fixed image, and the parts with differences are shown in the enlarged image on the right. Second, the proposed GAN method is compared with the VM and VM + A methods. Figure 4 shows the registered moving image and the fixed image. Moreover, the first row represents the original image from the HBN dataset, and the second row represents the segmentation image corresponding to the original image from the HBN dataset. Similarly, the third row represents the original image from the ABIDE dataset, and the fourth row represents the segmentation image corresponding to the original image from the ABIDE dataset. Additionally, the enlarged figure on the right shows that the result for the proposed method regarding the training of the registration, augmented, and discrimination networks together is closer to the fixed image. Through the experimental results, the performance of the registration, augmented, and discrimination networks when trained together is verifiably better than that of the registration network trained individually and of the registration and augmented networks trained simultaneously. In order to more clearly highlight the effectiveness of the method proposed in this paper, Figure 5 shows the experimental results of the three parts of the brain tissue based on the HBN dataset, and Figure 6 shows the experimental results of the three parts of the brain tissue based on the ABIDE dataset. The dotted circle in the figure is the result obtained by the method proposed in this paper. Table 3 and Table 4 summarize the Dice, SSIM, and PCC indices corresponding to the different datasets. Considering Table 3, for the HBN dataset, the proposed method improves the precision values by 0.030, 0.032, and 0.034 compared with the VM method. For the ABIDE dataset, the proposed method improves the accuracies by 0.008, 0.004, and 0.004 compared with the VM method. Considering Table 4, for the HBN dataset, the proposed method increases the SSIM and PCC indices by 0.02 and 0.008, respectively, compared with the VM method. For the ABIDE dataset, the proposed method improves the SSIM and PCC indices by 0.006 and 0.003, respectively, compared with the VM method. ## 5. Discussion The usage of a registration and discrimination networks for image registration is a common method. Such a registration method has been investigated experimentally in previous work [34]. However, this adversarial method for training a GAN only limitedly improves a registration network’s performance, and the registration capacity in some narrow and long edge areas needs to be further improved. Therefore, this paper proposes a method of training three networks together to allow the registration network to learn more deformations, further improving the registration performance. When the three networks are trained together, the use of different loss functions has a certain impact on the experimental results, which is discussed in the following subsections. ## 5.1. Importance of MSE When two networks (VM + A) were trained together, both the Lsmooth loss function of the deformation field ϕ2 and the MSE loss function were calculated. An experiment was also performed without the MSE loss function (VM + A − MSE) to verify its effectiveness. Additionally, when the three networks (VM + A + GAN) were trained together, the MSE loss function was removed again (VM + A + GAN − MSE), and experiments were performed to verify the impact of the MSE loss function on the experimental results. Through comparison, the best registration effect was achieved when the three networks were trained together and combined with the MSE loss function. The results are shown in Figure 7. Table 5 summarizes the experimental results regarding the removal of the MSE loss function (VM + A − MSE) when two networks were trained together (VM + A) and the removal of the MSE loss function (VM + A + GAN − MSE) when three networks were trained together (VM + A + GAN). When comparing the results, note that the removal of the MSE loss function reduces registration accuracy, thus verifying that registration performance can be improved by adding the MSE loss function when these three networks are trained together. Comparing the SSIM and PCC metrics in Table 6, the loss function used by the proposed method achieves good results. Figure 4 shows the comparison of the experimental results after the MSE loss function was removed (VM + A − MSE) when two networks were trained together and after the MSE loss function was removed (VM + A + GAN − MSE) when three networks were trained together. Evidently, the proposed method obtained a result that is closer to the fixed image, which confirms the effectiveness of training three networks simultaneously; moreover, note that the proposed method intuitively shows a good registration effect in the narrow and long regions of the peripheries of the brain images. The first row of the resulting images represents the original image from the experimental results for the HBN dataset, and the second row represents the segmentation image corresponding to the original image from the experimental results for the HBN dataset. Similarly, the third row represents the original image from the experimental results for the ABIDE dataset, and the second row represents the segmentation image corresponding to the original image from the experimental results for the ABIDE dataset. ## 5.2. Importance of Lsim When the three networks (VM + A + GAN) are trained together, the Lsmooth loss functions between the ϕ2(M(ϕ1)) image and the fixed image F as well as the M(ϕ1°ϕ2) image and the fixed image F are removed for experimental comparison. After removing the two Lsim loss functions, the registration accuracy decreases significantly. Through this experimental analysis, it is evident that the Lsim loss function can restrict the similarity among the images to a certain extent, which proves the effectiveness of adding the Lsim loss function. By observing the histogram in Figure 8, it is evident that the proposed method improves the Dice, SSIM, and PCC indices. In Figure 8, note that (a) shows the importance of verifying the Lsim loss function for the HBN dataset; (b) shows the difference between verifying the proposed method for the ABIDE dataset and removing the Lsim loss function in the Dice index; (c) shows the impact of removing the Lsim loss function on the SSIM and PCC indices for the HBN dataset; and (d) shows the impact of removing the Lsim loss function on the SSIM and PCC indices for the ABIDE dataset. ## 5.3. Importance of Different Deformation Fields The Dice values for when two networks were trained simultaneously are calculated and discussed next to verify ϕ1, ϕ2, and ϕ1°ϕ2 in the images. For ϕ1, the similarity is calculated between the warped moving image segmentation image Mseg(ϕ1) and the fixed image segmentation image Fseg, expressed as Msegϕ1−Fseg. For ϕ2, the similarity is calculated between the warped (Msegϕ1)(ϕ2) and the fixed image segmentation image Fseg, expressed as Msegϕ1ϕ2−Fseg. For ϕ1°ϕ2, the similarity is calculated between the warped moving image segmentation image Msegϕ1°ϕ2 and the fixed image segmentation image Fseg, expressed as Msegϕ1°ϕ2−Fseg. Considering the Dice values in the Table 7, the deformation field (ϕ2) still plays a certain role in image registration, but a significantly miniscule role. Therefore, the registration network still allows the deformation field (ϕ1) to learn more deformations, and the augmented network only plays a secondary role. ## 6. Conclusions In this paper, a method wherein three networks (registration, augmented, and discrimination networks) are trained together is proposed, for which the MSE loss function is introduced into the augmented network to improve the registration network’s performance. It was demonstrated that the registration network’s performance was further improved when coupled with the adversarial capacity of a GAN. 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--- title: 'A Causality between Thyroid Function and Bone Mineral Density in Childhood: Abnormal Thyrotropin May Be Another Pediatric Predictor of Bone Fragility' authors: - Dongjin Lee - Moon Bae Ahn journal: Metabolites year: 2023 pmcid: PMC10058985 doi: 10.3390/metabo13030372 license: CC BY 4.0 --- # A Causality between Thyroid Function and Bone Mineral Density in Childhood: Abnormal Thyrotropin May Be Another Pediatric Predictor of Bone Fragility ## Abstract Low bone mass can occur in children and adolescents with numerous chronic conditions; however, the influence of abnormal thyroid hormone and thyroid-stimulating hormone (TSH) levels on low bone mineral density (BMD) in children and adolescents remains controversial. Investigating the effects of excessive or deficient thyroid hormone and TSH levels on the risk of childhood bone fragility may provide a better understanding of the role of thyroid function on bone density in the pediatric population. The triiodothyronine (T3), thyroxine (T4), and TSH levels and BMD of 619 children diagnosed with various underlying conditions and whose treatment was completed were simultaneously assessed. The T3, free thyroxine (FT4), and TSH levels were subcategorized based on the age-matched reference range, and the lumbar spine BMD (LSBMD) data were compared. The mean LSBMD z-score was 0.49 ± 1.28, while T3, FT4, and TSH levels were 1.25 ± 0.29 ng/mL, 1.28 ± 0.19 ng/dL, and 2.76 ± 1.87 µU/mL, respectively. Both lumbar and femoral BMD z-scores were lower in children with abnormal TSH levels. TSH abnormality was the strongest risk factor for decreased LSBMD z-scores, and thus could be an early indicator of low BMD in children and adolescents with various underlying conditions. ## 1. Introduction Thyroid hormone (TH), whose synthesis and secretion are mainly regulated by thyrotropin (a thyroid-stimulating hormone (TSH)), which is secreted from the anterior pituitary lobe, plays a critical role in the metabolism, growth, and development of the human body. Although TH is responsible for the normal growth and differentiation of various organs, bone is one of the major endocrine organs affected by the regulation of TH. Upon the release of thyrotropin, the thyroid gland produces thyroxine (T4) and triiodothyronine (T3), and the effect of TH on the bone occurs when T3 is bound to the α1 and β1 subtypes of nuclear TH receptors, which are mainly expressed in the bone [1]. TH maintains the skeletal homeostasis by differentiating and regulating chondrocytes, osteoblasts, and osteoclasts via the interaction of multiple signaling cascades that affect the bone turnover [2]. The TSH action on the bone remains controversial due to its inhibitory effect on osteoblastogenesis and osteoclastogenesis; therefore, understanding its direct interaction with the bone requires further investigation of the association between TSH receptor activation and skeletal signaling pathways of growth factors such as Indian hedgehog, wingless/integrated, insulin-like growth factor 1, and bone morphogenetic protein [3]. Low bone mass or osteoporosis can occur in children and adolescents with numerous chronic conditions owing to disease progression or treatment-associated factors [4,5,6,7]. Among various causes, endocrine origins such as hypogonadism, Cushing’s syndrome, growth hormone deficiency, hyperparathyroidism, and thyroid disorders are major triggering conditions resulting in low bone mineral density (BMD) and secondary osteoporosis [8]. Both hyperthyroidism and hypothyroidism may lead to the loss of BMD by affecting the bone turnover via the dysregulation of endochondral bone formation and osteoclastogenesis [9]. Excessive levels of TH exert a direct effect on the bone resorption via the cytokine- and cycle adenosine monophosphate-mediated mechanisms, as well as the increased sensitivity of β-adrenergic receptors and bone cells to catecholamines and parathyroid hormone, respectively [10]. On the contrary, TH deficiency not only causes growth retardation and persistent short stature, but also leads to decreased bone turnover due to the disturbance in endochondral ossification induced by a slowed bone formation and resorption process [11]. The influence of abnormal TH and TSH levels, under subclinical or overt conditions, on low BMD in children and adolescents remains controversial. Although the TSH receptor expression in chondrocytes, osteoblasts, and osteoclasts indicates the direct action of TSH on the cartilage and bone, the interpretation remains unclear since the TSH exerts stimulatory and inhibitory effects on osteoblastogenesis and osteoclastogenesis mediated by tumor necrosis factor-α, receptor activator or nuclear factor κ-B ligand, and osteoprotegerin [12]. Proliferating chondrocytes, bone marrow stromal cells, and osteoblasts are the major sites of TH receptor expression. TH is essential for the coordinated progression of endochondral ossification and cartilage matrix mineralization; however, the underlying mechanism of TH’s interaction with the bone matrix needs to be determined [12,13]. In addition, pediatric reference intervals for TH and TSH differ from the adult range and vary with age during childhood; therefore, the accurate identification of abnormal thyroid function is recommended. Likewise, the thyroid regulation of bone growth and development seems clear, yet the underlying mechanism associated with the action of abnormal thyroid function on the density of a growing skeleton requires further investigation. We hypothesize that abnormal TH or TSH levels affected by various pediatric chronic conditions are associated with low BMD and lead to a higher risk of osteoporosis. Investigating the effects of excessive or deficient T3, T4, and TSH levels on childhood BMD may provide a better understanding of the role of thyroid function in bone density in the pediatric population. Therefore, this study aimed to examine the association between thyroid function and BMD in children with various underlying conditions and to elucidate the association between abnormal thyroid function and low bone mass in order to support the role of early screening of thyroid function in the prevention of osteoporosis. ## 2.1. Participants The present study retrospectively and cross-sectionally reviewed 619 children and adolescents aged 10–18 years who were previously diagnosed with hemato-oncologic, rheumatoid, gastrointestinal, and endocrinologic diseases at a single tertiary care center and completed a disease-associated therapy within at least 1 year prior to the study enrollment. Patients diagnosed with anorexia nervosa, epilepsy, hydrocephalus, or nephrotic syndrome and who were not on any ongoing therapeutic intervention that could affect the skeletal or thyroid function were classified under the miscellaneous category. The serum TH and TSH levels of all patients were simultaneously assessed by performing lumbar and femoral BMD measurements. This study was approved by the Institutional Review Board of the Catholic University of Korea (KC22RISI0387) and was conducted in accordance with the principles of the Declaration of Helsinki. The requirement for informed patient consent was waived as no interventions or further examinations were performed. ## 2.2.1. Hemato-Oncologic Disease Patients previously diagnosed with leukemia, lymphoma, histiocytosis, solid organ tumor, or bone marrow failure based on the bone marrow biopsy or radiologic findings underwent surgery, repeat blood transfusions, multidrug chemotherapy, or focal or total body irradiation, with or without peripheral blood stem cell transplantation. The treatment plan was implemented in accordance with the uniform institution-based protocol of the Division of Pediatric Hemato-Oncology. ## 2.2.2. Rheumatoid Disease Patients previously diagnosed with systemic lupus erythematosus, juvenile rheumatoid or idiopathic arthritis, Sjogren–Larsson syndrome, Behçet’s disease, and juvenile dermatomyositis, characterized by the presence of disease-specific antibiotics, were treated with glucocorticoids, nonsteroidal anti-inflammatory drugs, and disease-modifying antirheumatic drugs. The treatment plan was implemented in accordance with the uniform institution-based protocol of the Division of Pediatric Rheumatology. ## 2.2.3. Gastrointestinal Disease Patients previously diagnosed with inflammatory bowel disease, including Crohn’s disease and ulcerative colitis, based on the gastroduodenocolonoscopic and radiologic findings, were treated with glucocorticoids, 5-aminosalicylic acids, and immune modulators (methotrexate or azathioprine), with or without biologics (such as antitumor necrosis factor or anti-integrin). The treatment plan was implemented in accordance with the uniform institution-based protocol of the Division of Pediatric Gastroenterology and Nutrition. ## 2.2.4. Endocrine Disease Patients previously diagnosed with growth hormone deficiency, idiopathic short stature, constitutional delay in growth and puberty, hypophosphatemic rickets, idiopathic osteoporosis, or congenital adrenal hyperplasia underwent hormone replacements. None of the patients with endocrine diseases were previously diagnosed with hyperthyroidism or hypothyroidism or had any history of taking antithyroid drugs or TH therapy. The treatment plan was implemented in accordance with the uniform institution-based protocol of the Division of Pediatric Endocrinology. ## 2.3.1. Anthropometric Measurement Height (cm) was measured using a Harpenden Stadiometer (Holtain®, Crymych, UK), while weight (kg) was measured using a Simple Weighing Scale (CAS®, Seoul, Republic of Korea). The body mass index (BMI) (kg/m2) was calculated and converted to age- and sex-matched standard deviation (z) scores, based on the national growth chart [14]. ## 2.3.2. BMD Assessment The BMD of the lumbar spine (LSBMD), right femur (RFBMD), and left femur (LFBMD) was measured in the anterior–posterior direction using dual-energy X-ray absorptiometry (DXA) (HorizonW DXA system®, Hologic Corp., Marlborough, MA, USA), whereas the age- and sex-matched z-scores for areal BMD (g/cm2) were determined based on native Normative Pediatric reference data [15]. All DXA measurements were performed by a single radiographer who was blinded to the patients’ clinical history. A low bone mass was defined as an LSBMD z-score of less than 0 to −3.0. ## 2.3.3. Thyroid Function Test The T3, FT4, and TSH levels were determined using the blood sample obtained on the same morning that the BMD was measured. The serum T3, FT4, and TSH levels were measured by performing a direct chemiluminescent immunoassay (Atellica IM, Siemens Healthcare Diagnostics Inc.®, Malvern, PA, USA) with inter-assay coefficients of variation of less than $13\%$, $8\%$, and $10\%$ for T3, FT4, and TSH, respectively. Subsequently, the T3, FT4, and TSH levels were subcategorized into either the high/normal/low or normal/abnormal based on the age-matched reference range (0.83–2.13 ng/mL for T3, 0.8–2 ng/dL for FT4, and 0.6–8 and 0.6–6 µU/mL for TSH of individuals aged 10–15 years and 16–18 years, respectively), and the LSBMD z-scores of each group were compared [16]. ## 2.4. Statistical Analysis For all descriptive variables, the normality of distribution was determined using the Shapiro–Wilk test. Comparison of BMD z-scores between the two (normal/abnormal T3, FT4, or TSH) groups was carried out using the Mann–Whitney U test, while the comparison of BMD z-scores among the three (low/normal/high T3, FT4, or TSH) groups was performed using one-way analysis of variance. The Pearson’s correlation coefficient (r) was generated to represent the linear correlation of LSBMD z-scores with T3, FT4, and TSH levels. Univariate and multivariate regression analyses were then performed to estimate the beta coefficients (β) for factors associated with the LSBMD z-score. Subsequently, a multiple logistic regression analysis of the abnormal T3, FT4, and TSH levels with decreased LSBMD z-scores as dependent variables was performed to determine the odds ratio (OR) and $95\%$ confidence interval (CI) after adjusting for age, sex, BMI, and underlying conditions. All statistical analyses were performed using SPSS software (version 24.0; IBM Corp.®, Armonk, NY, USA). ## 3.1. Demographic and Clinical Characteristics The clinical characteristics of the 619 children and adolescents are presented in Table 1. Half of the population were male, with a mean age and a BMI z-score of 13.22 ± 3.23 years and 0.03 ± 1.52, respectively. Hemato-oncologic patients accounted for $79.6\%$ of the total study population, with leukemia either originating from the lymphoid or myeloid white blood cells ($66.1\%$) being most prevalent, followed by primary bone marrow failure, including aplastic anemia ($9.7\%$). The most commonly diagnosed rheumatoid diseases were systemic lupus erythematosus ($65.6\%$) and juvenile rheumatoid or idiopathic arthritis ($12.5\%$). The overall proportions of patients with gastrointestinal ($3.7\%$) and endocrinological disorders ($3.1\%$) were similar. The miscellaneous conditions included anorexia nervosa [13], epilepsy [3], hydrocephalus [2], and nephrotic syndrome [2]. The ages at diagnosis of an underlying disease were 8.67 ± 13.03, 12.29 ± 3.75, 13.59 ± 2.48, 9.48 ± 4.75, and 9.01 ± 5.95 years for the hemato-oncologic, rheumatoid, gastrointestinal, endocrinologic, and miscellaneous groups, respectively. The mean LSBMD z-score was 0.49 ± 1.28. Approximately $37.7\%$ of the patients had a mean LSBMD z-score of less than −1.0. Meanwhile, the femoral BMD z-scores were lower than the LSBMD z-scores. More than $90\%$ of all subjects showed normal thyroid function on DXA assessment, and those who initially showed abnormal T3, FT4, or TSH levels did not undergo TH replacement or antithyroid drug therapy, as the follow-up concentrations returned to normal within 6 months. ## 3.2. LSBMD and Thyroid Function of Patients with an Underlying Condition LSBMD and thyroid function were compared based on the five underlying conditions (Figure 1). The magnitude of the LSBMD z-scores for hemato-oncologic and endocrinologic diseases was the highest (the highest and lowest LSBMD z-scores were 3.1 and −5.2 for hemato-oncologic patients and 2.7 and −5.2 for endocrinologic patients, respectively). Meanwhile, the mean LSBMD z-scores did not show a significant difference among the study groups. The serum T3 and TSH levels were higher in the hemato-oncologic group compared with that in the rheumatoid group (1.28 ± 0.27 mIU/L vs. 1.13 ± 0.32 mIU/L, $$p \leq 0.009$$; 2.86 ± 1.87 µIU/mL vs. 2.29 ± 1.65 µIU/mL, $$p \leq 0.033$$); however, no significant difference was observed between the rest of the study groups. In contrast, no significant difference was observed in the serum FT4 level in all study groups. ## 3.3. BMD Status under Abnormal Thyroid Function The serum T3, FT4, and TSH levels were subcategorized into either normal/abnormal (Table 2) or high/normal/low (Figure 2) based on the age-matched reference range, and the BMD z-scores were compared. Both lumbar ($$p \leq 0.018$$) and femoral ($$p \leq 0.036$$ for left, $$p \leq 0.007$$ for right) BMD z-scores were significantly lower in the abnormal TSH group compared with that in the normal TSH group; meanwhile, the left femoral BMD z-scores were the lowest, while the z-score difference was greatest in patients with abnormal serum TSH levels compared with that in patients with normal serum TSH levels. In contrast, no significant difference in BMD z-scores was observed between patients with abnormal and normal T3 or FT4 levels (Table 2). Figure 2 demonstrated the corresponding LSBMD z-scores for low, normal, or high serum T3, FT4, and TSH levels. The LSBMD z-score difference was not significant when the serum T3, FT4, or TSH levels were either low or high. None of the participants had hyperthyroxemia. ## 3.4. Causal Association between BMD and Thyroid Function Both the areal BMD (g/cm2) and z-scores for the lumbar spine showed no direct correlation with serum FT4 or TSH levels (Figure 3). The serum T3 level was not correlated with LSBMD z-scores but was negatively correlated ($r = 0.044$, $$p \leq 0.302$$) with LSBMD (g/cm2). In the univariate regression, the height (β = 0.42, $p \leq 0.001$), weight (β = 0.41, $p \leq 0.001$), and BMI (β = 0.31, $p \leq 0.001$) z-scores as well as the RFBMD (β = 0.73, $p \leq 0.001$) and LFBMD (β = 0.74, $p \leq 0.001$) z-scores were significantly associated with the LSBMD z-scores, while the serum T3, FT4, and TSH levels were not (Table 3). The BMI z-score (β = 0.32, $p \leq 0.001$) was independently related to the LSBMD z-scores, while serum T3, FT4, and TSH levels showed no association with the LSBMD z-scores in the following multivariate regression analyses. In a subsequent multiple logistic regression analysis, the unadjusted ORs of abnormal TSH levels for LSBMD z-scores of less than −1.0, −2.0, and −3.0 were 1.85 ($95\%$ CI = 1.08–3.17; $$p \leq 0.026$$), 2.4 ($95\%$ CI = 1.23–4.7; $$p \leq 0.011$$), and 3.89 ($95\%$ CI = 1.34–11.34; $$p \leq 0.0.013$$), respectively (Table 4). The unadjusted-abnormal T3 level had an OR of 2.38 (95 % CI = 1.07–5.25; $$p \leq 0.033$$) for an LSBMD z-score of less than −2.0, but it was not significant for LSBMD z-scores of less than −1.0 and −3.0. Unadjusted abnormal FT4 levels were not associated with the LSBMD z-scores at any time interval. After adjusting for age, sex, BMI, and underlying conditions, the ORs of abnormal TSH levels were greater within all intervals of LSBMD z-scores and increased as the LSBMD z-scores decreased (OR = 2.25, $95\%$ CI = 1.24–4.08, $$p \leq 0.008$$ for LSBMD z-score less than −1.0; OR = 2.65, $95\%$ CI = 1.29–5.46, $$p \leq 0.008$$ for less than −2.0; OR = 6.21, $95\%$ CI = 1.8–21.41, $$p \leq 0.004$$ for less than −3.0). Even after adjusting for confounders, the abnormal T3 and FT4 levels were still not significantly associated with decreased LSBMD z-scores. ## 4. Discussion Although the direct causality between abnormal thyroid function and low bone mass remains controversial, an abnormality in TSH level seems to exert a more sensitive effect on pediatric bone fragility compared with TH. Owing to the variety of underlying systemic conditions and the fact that their treatment-associated factors simultaneously result in severe secondary osteoporosis and thyroid illness, recognizing which is more affected is as important as identifying the causes. The association between thyroid function and bone assessment in children and adolescents with a wide range of chronic illnesses suggests that abnormal TSH levels, whether elevated or decreased, could become a susceptibility indicator closely linked to decreased BMD; thus, it could be considered an early predictor of secondary osteoporosis. This information may prompt any pediatric healthcare provider, including pediatric endocrinologists, to closely monitor the thyroid function with skeletal assessment to prevent further complications, such as fracture. The recently developed evidence-based consensus guidelines and recommendations for therapeutic intervention and prevention of secondary osteoporosis have pointed out that the hyperthyroidism-induced acceleration of bone turnover followed by increased cartilage maturation and bone resorption is a vital mechanism of bone loss [8,9,17]. Recent guidelines published by the Korean Thyroid Association highlighted that bone health assessment is critical in adult patients with endogenous overt hyperthyroidism or hyperthyroidism induced by TSH suppression therapy for differentiated thyroid cancer [18]. On the contrary, hypothyroidism might slow the rate of bone resorption; however, its existence could hinder the activity of osteoblasts, leading to impaired bone formation and turnover, which is critical, especially in a growing child [19]. Multiple chronic childhood illnesses requiring aggressive and lifelong care with a combination of different treatment regimens can affect the intact hypothalamic–pituitary–thyroid (HPT) axis, leading to thyroid dysfunction. For example, glucocorticoids, the most widely used drugs for controlling the inflammatory and autoimmune reactions, not only suppress the secretion of thyrotropin-releasing hormones (TRHs) and TSHs by altering the HPT axis, but also diminish the TH secretion by reducing the deiondinase activity [20]. Whether excessive or deficient TH level can adversely affect bone loss remains unknown; hence, maintaining euthyroidism prevents further progression to secondary osteoporosis during childhood. TSH secretion is stimulated by thyrotrophs in the anterior pituitary gland and is mainly regulated by TRH release driven by the hypothalamic THR neurons. TSH signals the thyroid follicular cells to produce T3 and T4, whose excess exerts an inhibitory action via a negative feedback loop system on the anterior pituitary gland, thus suppressing the TSH secretion. TSH receptor expression was observed not only in the thyroid tissue but also in normal osteoblasts, implying the direct action of TSH on bone formation [21]. Several observational studies conducted in an adult population concluded that individuals with low normal TSH levels, regardless of TH levels, are at risk of developing osteoporosis [22]. However, BMD loss was more likely attributed to the diverse immune–skeletal–endocrine interactions between TSH in the bone marrow cells and TSH receptors in the skeletal tissues based on the osteoclastogenic effect of tumor necrosis factor α and the expression of splice variants of TSH [23]. Upon the TSH surge occurring at birth, the elevated TSH level begins to gradually reduce and plateau between 6 and 12 months of age; meanwhile, the surge could be somewhat attenuated or prolonged in prematurely born infants. The age-specific reference intervals for TSH in pediatric populations are much wider than those in adults, with upper limits ranging up to 39.0, 12.5, and 8.0 mU/L at 7 days, 3 months, and 5–10 years of age, respectively [16,24]. Without the classic symptoms of hypothyroidism, TSH screening is commonly performed in pediatric endocrinology clinics, because the elevation of TSH levels is frequently observed in association with childhood obesity, short stature, and delayed or accelerated pubertal progression [25]. Low TSH levels mostly occur in patients with TH-excessive conditions; however, the level of TSH seems to decrease, specifically in children diagnosed with eating disorders with abrupt weight loss or in patients who are taking high-dose glucocorticoids, dopamine, and amiodarone [26,27]. Due to its finely tuned and sensitively controlled negative feedback loop, the regulation of TSH secretion can easily be affected in children with chronic illnesses, which is currently referred to as non-thyroidal illness syndrome and commonly manifests as subclinical hypothyroidism [28]. Majority of our study participants from five different disease categories had normal TSH, T3, and FT4 levels at DXA assessment; meanwhile, the proportions of patients with abnormal TSH, T3, and FT4 levels were $9.5\%$, $7.4\%$, and $0.5\%$, respectively. The effect of pediatric chronic diseases on HPT axis dysfunction through different mechanisms seems to result in TSH alteration; however, insufficient TH levels may trigger overt hyperthyroidism or hypothyroidism of central origin. Since an abnormal TSH level is considered a potential parameter for predicting low LSBMD z-scores, the serum TSH levels should not be overlooked, despite having a normal TH status. Knowing the age-related reference interval may be critical in interpreting the association between thyroid function and bone health. According to Sheng et al., TSH showed no significant correlation with BMD of euthyroid adults and was also not associated with the variations of BMD and the fracture risk in the elderly [29]. A similar study by Lin et al. yielded consistent results and suggested thyroid hormone, particularly T4, as a more appropriate indicator between bone and thyroid function, demonstrating weak negative correlations between T4 and BMD [30]. Both studies were conducted based on an adult population in euthyroid and disease-free states. Veldscholte et al. demonstrated no significant association between TSH and BMD (g/cm2) and BMC (g) of the total body without the head in a healthy 6-year-old population, and they also suggested that FT4 is a better indicator of bone turnover [13]. According to our results, based on the thyroid function of unhealthy patients and sex- and age-matched LSBMD z-scores, TSH showed no direct correlation with BMD as well. Taken together, it is agreed that there hardly exists a simple correlation between TSH and BMD, and BMD does not simply increase as the TSH increases or decreases. On the other hand, our subjects were a pediatric population of euthyroid state but having been diagnosed with various chronic illnesses affecting the HPT axis. There is not enough evidence to discuss the difference between adult and pediatric populations regarding the effect of bone mineral accrual on the regulation of the HPT axis. Nevertheless, the novelty of this study showed that any abnormal TSH level out of the age-specific reference interval, whether elevated or decreased, could be a sign of low LSBMD z-scores, and the link between these two factors became more evident in severely osteoporotic children. Compared with the OR of unadjusted-abnormal TSH for an LSBMD z-score of less than −1.0, a six-fold increase was observed in the abnormal TSH level for an LSBMD z-score of less than −3.0 when the abnormal TSH level was adjusted for age, sex, BMI, and underlying conditions. In addition, our results showed that FT4 levels could not be an indicator of low BMD. After all, it might be a unique characteristic occurring during childhood and adolescent periods. Our study has several limitations. First, this was an age-unmatched, single-armed, cross-sectional study based on an unevenly distributed number of patients from each underlying disease category. Hemato-oncologic and rheumatoid diseases accounted for the majority ($89.9\%$) of the total study participants. Second, children with abnormal TH and TSH levels comprised less than $10\%$ of the total study participants, whereas one-third had relatively low bone mass with an LSBMD z-score of less than −1.0. Additionally, the number of participants with hyperthyroidism and triiodothyroninemia was relatively small to determine the effect of elevated T3 and T4 levels on bone mass. Third, the BMD z-scores of the lumbar spine were used to explore their causal relationship with thyroid function. Although the overall femoral BMD z-scores were lower than the LSBMD z-scores, the lumbar spine and total body-less head were the internationally preferred skeletal sites for performing areal BMD measurements in pediatric patients [31]. Since the national reference values for BMD are provided, additional measurements of BMD z-scores for total body-less head could have been useful to elucidate the connection between bone and thyroid function [15]. Nevertheless, to the best of our knowledge, our study is the first to examine the connection between thyroid function and BMD in children with various underlying conditions, and it aimed to identify which among the three thyroid function parameters more sensitively reflected a low BMD. ## 5. Conclusions In conclusion, abnormal TSH levels showed a stronger association with low LSBMD z-scores compared with T3, FT4, and TSH levels. This parameter could be an early indicator of low BMD in children and adolescents with various underlying conditions. Therefore, immediate bone health assessment is recommended when the TSH levels, whether elevated or decreased, are outside the age-specific reference range. 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--- title: Melatonin Prescription in Children and Adolescents in Relation to Body Weight and Age authors: - Elin E. Kimland - Elin Dahlén - Jari Martikainen - Jimmy Célind - Jenny M. Kindblom journal: Pharmaceuticals year: 2023 pmcid: PMC10058986 doi: 10.3390/ph16030396 license: CC BY 4.0 --- # Melatonin Prescription in Children and Adolescents in Relation to Body Weight and Age ## Abstract The prescription of melatonin to children and adolescents has increased dramatically in Sweden and internationally during the last ten years. In the present study we aimed to evaluate the prescribed melatonin dose in relation to body weight and age in children. The population-based BMI Epidemiology Study Gothenburg cohort has weight available from school health care records, and information on melatonin prescription through linkage with high-quality national registers. We included prescriptions of melatonin to individuals below 18 years of age where a weight measurement not earlier than three months before, or later than six months after the dispensing date, was available ($$n = 1554$$). Similar maximum doses were prescribed to individuals with overweight orobesity as to individuals with normal weight, and to individuals below and above 9 years of age. Age and weight only explained a marginal part of the variance in maximum dose, but were inversely associated and explained a substantial part of the variance in maximum dose per kg. As a result, individuals overweight or with obesity, or age above 9 years, received lower maximum dose per kg of body weight, compared with individuals with normal weight or below 9 years of age. Thus, the prescribed melatonin dose to individuals under 18 years of age is not primarily informed by body weight or age, resulting in substantial differences in prescribed dose per kg of body weight across BMI and age distribution. ## 1. Introduction Pediatric sleep disorders are common. About one in four, and among individuals with neuropsychiatric disorders an even higher proportion, experience sleeping difficulties at some point during childhood [1,2,3,4,5]. As a result, the prescription of melatonin to children and adolescents has increased dramatically in Sweden [6] and other Nordic countries [7,8] during the last ten years. Melatonin is used for sleep disorders in children and adolescents, and it is recommended in national guidelines as a second line of treatment after non-pharmacological alternatives [9,10]. Although melatonin is recommended as a short-term treatment, several register-based studies show that long-term use is common [6,8,11,12]. These findings indicate a substantial exposure for some individuals where treatment is initiated during childhood and continues long-term. The adverse events following short-term treatment have been reported to be minor, transient, and easily managed, mostly related to fatigue, mood, or psychomotor and neurocognitive performance and therefore melatonin is considered a safe medication [13]. There is no reported withdrawal syndrome, and the risk of acute toxicity appears to be low, even at high doses. It has been discussed that long-term medication with melatonin may influence sexual maturation, although a recent cohort study refuted this [14]. Further investigations are needed before long-term safety of melatonin use starting in childhood or adolescence can be established [13]. Melatonin is metabolized mainly via cytochrome p450 (CYP) 1A2 together with several other psychiatric drugs, and this metabolizing enzyme has fluvoxamine and paroxetine as known inhibitors [15]. These drugs however, are rarely used in children in Sweden. The authorization status for melatonin varies among countries. In the USA, melatonin is regarded as a dietary supplement, while it is available as an over-the-counter drug or on prescription for adults in several European countries. Since 2018 melatonin is approved for sleep disorders in children with neuropsychiatric comorbidity by the EMA. In most European countries melatonin is available as a prescribed medicine as well as an over-the-counter drug and in some countries also regarded as a dietary supplement. Only authorized medical products are under pharmacovigilance surveillance and good manufacturing practice to guarantee correct substance in an adequate amount and no contamination. Authorized melatonin is available both as an oral solution (1 mg/mL) as well as direct acting tablets in strengths from 1–5 mg and prolonged-release tablets 1–5 mg. Melatonin dosing largely depends on purposes [16]. In children and adolescents, melatonin is labelled for insomnia and as far as sleep and circadian disorders are considered, low doses are considered preferable [16]. Medicines to children are commonly dosed according to weight and/or age to adjust for physiologic and pharmacokinetic differences compared to adults [17]. Growth and development have profound effects on drug disposition in children as a consequence of maturational alterations in drug absorption, distribution, metabolism and elimination, and due to increased weight and changes in body composition [18]. Obesity is associated with additional changes in body composition and physiology that may affect pharmacokinetics of drugs. Increased liver size, hepatic perfusion and glomerular filtration rate have been reported in children with obesity. The rate-limiting pharmacokinetic and physiological variables do not display alterations that are proportionate with the increase in body size [19]. Therefore, the conventional mg/kg dosing may not be applicable in children with obesity. Pediatric pharmacokinetic studies rarely include data for the population of children with obesity and hence, this is an area where knowledge gaps are especially large [19]. For melatonin, the starting dose according to the information in the summary of product characteristics for melatonin products approved by the European Medicines Agency (EMA), as well as recommendations in Nordic national guidelines [9,10], is 1–5 mg in children 4 years of age and older. The further recommendation is to increase the dose until sufficient effect is reached. In line with these national recommendations, the melatonin doses were in the range from 1 to 10 mg in the studies included in a recently published systematic review [20]. However, the optimal dose per kg of body weight, and whether children and adolescents overweight and with obesity, or older children, would benefit from higher doses, has not been established. In the present study we aimed to evaluate the prescription of melatonin in relation to body weight and age. ## 2. Results In the present study we used the population-based cohort BMI Epidemiology Study Gothenburg to evaluate the prescription of melatonin in relation to body weight and age. In total, 1554 children below 18 years of age were dispensed melatonin at least once during the study period and had a weight measurement available in the required interval. The mean age at prescription was 11.7 years (SD 3.5 years) and $62.7\%$ were males. Overweight or obesity was seen in $24.8\%$ of the individuals in the cohort (Table 1). We found that $77\%$ received a maximum melatonin dose of 5 mg or less, and the most prescribed tablet strengths were 2 mg and 3 mg (Table 1). 1007 ($64.8\%$) individuals received a first prescription while 547 ($35.2\%$) received an iterated prescription. The maximum dose displayed a range of 1.0–25.0 mg, and the maximum dose in relation to body weight was 0.01–1.53 mg/kg. We observed that the maximum dose, and maximum dose per kg of body weight, were significantly higher among the iterated prescriptions (4.6 mg (SD 3.2) and 0.13 mg/kg body weight (SD 0.15), respectively), than the first prescriptions (3.5 mg (SD 2.2) and 0.09 mg/kg body weight (SD 0.07), respectively, $p \leq 0.001$ for both). We therefore present the subsequent results divided into first and iterated prescriptions of melatonin. ## 2.1. Maximum Dose of Melatonin The range of the maximum dose of melatonin was 1–20 mg for first prescriptions and 1–25 mg for iterated prescriptions. Individuals with overweight or obesity were prescribed similar maximum total doses as individuals with normal weight, and children under 9 years of age received similar maximum doses as children above 9 years of age (Table 2). Weight and age (separately) only marginally explained the variance in maximum dose for first or iterated prescriptions (Table S1). These findings demonstrate that similar maximum doses of melatonin were prescribed irrespective of age and weight. ## 2.2. Maximum Dose per Kg of Body Weight The range of the maximum prescribed melatonin dose per kg of body weight was 0.01–0.85 mg/kg for first prescriptions and 0.02–1.53 mg/kg for iterated prescriptions. Individuals with overweight or obesity were prescribed significantly lower maximum dose per kg of body weight compared with individuals without overweight or obesity, for both first and iterated prescriptions (Table 2). Children above 9 years of age received significantly lower doses per kg of body weight in both first prescriptions and iterated prescriptions compared to children below 9 years of age (Table 2). Weight was a strong inverse predictor of the maximum dose per kg and explained a substantial part of the variance in dose per kg (Table S1). Similarly, age at prescription showed a strong inverse association with the maximum dose per kg and explained a substantial part of the variance. Thus, lower doses per kg of body weight were prescribed to individuals with overweight or obesity compared with individuals without elevated BMI, and to individuals over 9 years of age compared to below 9 years of age. ## 2.3. Prescriptions According to Sex, Psychiatric and Neuropsychiatric Co-Morbidities There were no statistically significant differences in maximum total dose or maximum dose per kg of body weight for girls versus boys, or individuals with or without psychiatric comorbidity in the first or iterated prescriptions (Table 3). There were no significant differences in age or weight between children with and without psychiatric comorbidity. Individuals with neuropsychiatric disorder received lower maximum doses and lower dose per kg of body weight on iterated prescriptions (Table 3). ## 2.4. Prediction of Dose and Dose per Kg A linear regression model showed that age, weight, sex, psychiatric comorbidity, and neuropsychiatric disorder together explained only a marginal part of the variance in dose (Table S1). For dose per kg however, age and weight explained a substantial part of the variance but the addition of sex, psychiatric comorbidity or neuropsychiatric disorder only marginally increased the variance explained (Table S1). ## 2.5. Dosing in Individuals According to Ideal Body Weight For children with excess weight, it is sometimes recommended to use the ideal body weight (IBW) to calculate a drug dose. Using the Moore method [22], we calculated the IBW of a girl and boy with obesity based on the mean age and height for the group of girls and boys with obesity in the present study. According to the Swedish reference growth charts [23], the IBW of a 12-year-old girl of 1.51 m was 41 kg, and for a boy of 11.5 years and 1.55 m it was 44 kg. The results demonstrate that the dose per kg of IBW for the average girl and boy with obesity equaled the dose per kg in children without obesity (Table S2). There was no statistical difference in dose or dose per kg between girls and boys with obesity (Table S2). ## 3. Discussion In the present study we used the population-based BEST Gothenburg cohort with information on body weight together with data on melatonin prescriptions to study the dispensed maximum dose of melatonin in relation to body weight and age. We found that most of the individuals were prescribed a maximum dose of 5 mg or less but that the dose per kg of body weight displayed a large variability. The main finding was that there was no association between body weight and the maximum dose. Similar maximum doses were prescribed to individuals overweight or with obesity as to individuals without elevated BMI, and to older and younger individuals. As a result, individuals with an elevated BMI or older age received lower maximum dose per kg of body weight. Thus, melatonin prescriptions to individuals under 18 years of age are not primarily informed by body weight or age, resulting in substantial differences in prescribed dose per kg of body weight across BMI and age distribution. The effectivity of melatonin as treatment of sleep disorders is rather well studied in children with neuropsychiatric disorders. Melatonin in the dose range of 2–10 mg demonstrated improved sleep duration and sleep latency onset in pediatric patients 2–18 years of age with neuropsychiatric disorder in a recent systematic review [20]. In another systematic review, melatonin was shown to be the most effective treatment for sleep disorders together with parental education and behavioral interventions in children with autism spectrum disorder [24]. In children without neuropsychiatric disorders there is less evidence to support the use. One small, randomized study demonstrated statistically significant improvements in sleep parameters with melatonin 5 mg compared with placebo in children 6–12 years of age [25]. Short term use of melatonin has demonstrated good safety [13], but several register-based studies show that long-term use is common [6,12]. Considering the multiple physiological effects of melatonin and the scarce knowledge of long-term safety in the pediatric population [13,26,27], along with an exponential rise in use, it is of great importance for health care professionals, care givers and regulatory authorities to follow up the use of melatonin in the pediatric population. In the present study evaluating melatonin prescription according to body weight and age, we demonstrate that similar doses are prescribed to individuals with and without overweight and obesity, as well as to individuals above and below 9 years of age. As a result, individuals receive highly varying doses per kg of body weight. Moreover, similar maximum dose and dose per kg of body weight were seen for girls and boys, and for individuals with and without psychiatric comorbidity, but individuals with neuropsychiatric disorders were prescribed lower doses compared to individuals without neuropsychiatric disorders on iterated prescriptions. Pediatric sleep disorders are common and may have a significant negative impact on a child’s development and quality of life, including well-being, learning, growth, behavior, and the regulation of emotions [1]. Adequate treatment is therefore important. Melatonin is recommended as the drug of choice in international and national guidelines when pharmacological treatment is needed [9,10,14]. Although the first line of treatment for pediatric sleep disorders is non-pharmacological, there has been a substantial increase in prescriptions of melatonin for sleep disorders among children and adolescents in the Nordic countries [6,7,8,28,29,30]. The recommendations in the summary of products characteristics for different melatonin products authorized in the EU [15] as well as the national guidelines in Sweden [9], recommend 1–5 mg in children 4 years of age and older as a starting dose, and to further increase the dose up to sufficient effect. The studies included in a recent systematic review used melatonin doses ranging from 1 to 10 mg in children under 18 years of age [20]. This is in line with the results in the present study, where $77\%$ were prescribed a dose of 5 mg or lower. However, the optimal dose per kg of body weight, and whether children and adolescents who are overweight and have obesity or are older in age would benefit from higher doses, has not been established. In the present study, we found that similar doses were used for overweight individuals as for individuals with normal BMI, resulting in higher doses per kg of body weight in normal weight individuals. A recent study assessed the link between BMI and effective daily dose of melatonin in adults. Of note, they found that individuals with a higher BMI needed higher doses of melatonin [31]. The authors present two possible mechanisms that might at least partially explain the need for larger doses: that melatonin distributes into fat mass and thus has a larger distribution in individuals with expanded fat mass, and that a receptor variant associated with weaker melatonin signaling is found more frequently in individuals with obesity [32]. Given the lipophilic nature of melatonin, an altered distribution in individuals with obesity is plausible. The findings in that study, together with the findings in the present study that individuals with elevated BMI receive lower melatonin doses, indicate that there is a need to further evaluate the impact of high BMI on the effective dose of melatonin in children. For older adults, a systematic review evaluated melatonin dosing and concluded that the lowest effective dose should be used [16,33]. However, the dosing in that study displayed a large variation [33], indicating that several individual factors may be of importance for dosing of melatonin, such as pronounced inter-individual differences in melatonin production [34], endogenous melatonin production sensitivity to ambient light [35,36], timing of intake of melatonin and pharmaceutical formulation, which has been described in adults. Moreover, some mechanistic studies performed in cell cultures have indicated that melatonin receptors might become desensitized if exposed to exogenous melatonin over a long period of time [37,38]. Although likely to be of importance in children, there are no studies directly assessing the importance of these factors in the pediatric population. The strengths with the present study are the population-based nature of our cohort, data on melatonin prescriptions together with weight during childhood and adolescence, and that the coverage of the National Prescribed Drug Register is over $99\%$. The limitations are that no information is available regarding the effect of the melatonin treatment, possible adverse drug reactions, or whether the individuals who were dispensed melatonin used the medication. Another limitation is the restricted geographical representation (mainly the Gothenburg area). There is a general lack of knowledge regarding medicines in children, but for the sub-population of children with obesity, this knowledge gap is even larger. With the obesity epidemic there is a huge need to learn more regarding drug disposition in children and youth with obesity and therefore, high-quality clinical studies addressing pharmacodynamics, pharmacokinetics, and optimal dosing in this population are warranted. ## 4. Methods The population-based BMI Epidemiology Study (BEST) Gothenburg cohort was initiated with the overall aim to study the impact of height, weight, and BMI during childhood and puberty on adult diseases, as previously described [39]. The BEST Gothenburg cohort has developmental height and weight measurements available from school health care and child health care [40], and information on causes of death, diagnoses, and prescribed drugs from high-quality national registers in Sweden. Individuals in the BEST Gothenburg cohort were eligible for the present study if they had at least one prescription of melatonin dispensed before 18 years of age in the National Prescribed Drug Register, and in addition had a weight measurement available in the interval up to 3 months before to 6 months after the melatonin dispensing. Melatonin was defined using the Anatomical Therapeutic Chemical (ATC) code N05CH01 [41]. ## 4.1. Exposures The exposures in the present study were body weight, overweight and obesity status, and age at dispensing. We calculated BMI as weight in kilograms divided by height in meters squared and used the International Taskforce for Obesity’s cutoffs for overweight and obesity for age and sex [21]. Furthermore, using information from the National Patient Register in Sweden, we defined psychiatric and neuropsychiatric disorders according to diagnoses in the International Classification of Diseases ICD) system (F00–F99; F84 and F90–F98, respectively). Psychiatric comorbidity was defined as either presence of an F00–F99 diagnosis before the dispensing date of melatonin, or an anti-depressant, treatment for attention-deficit hyperactivity disorder (ADHD), neuroleptic, anxiolytic, or sedative (other than melatonin) in the National Prescribed Drugs Register, dispensed within 6 months before, or 6 months after, the dispensing date of melatonin. The drug treatments were defined using the following ATC codes: N06A (anti-depressants), N06BA and C02AC02 (treatment for ADHD), N05A (neuroleptics), N05B, R06AD (anxiolytics), and N05C, excluding N05CH01 (sedatives other than melatonin). ## 4.2. Outcomes The National Prescribed Drugs Register is held by the National Board of Health and Welfare in Sweden and was initiated in 2005. The outcome in the present study was maximum dose of melatonin (mg), and maximum dose of melatonin per kilogram body weight (mg/kg) for the first eligible prescription dispensed before 31 January in 2021. The included first eligible prescription could be either a first or an iterated prescription. We defined a prescription as first if there were no previous melatonin prescriptions for that individual during the study period and required at least one year free of melatonin dispensings. For individuals with several dispensings that fulfilled the inclusion criteria, we included the first eligible dispensing. For the maximum dose, we used the tablet strength and information given with the prescription available as free text in the National Prescribed Drugs Register. Two of the investigators (JC and JMK) reviewed every included prescription and retrieved the maximum prescribed dose. For example, if a study subject was prescribed a 2 mg tablet of melatonin with the free text instruction “One tablet each night, if needed increase to 2–3 tablets”, the maximum dose for that prescription was concluded to be 6 mg. For the maximum dose per kilogram body weight, we used the maximum dose divided by the subject’s body weight (mg/kg) in the interval up to 3 months before to 6 months after the date of the melatonin dispensing. The included prescriptions could be first or iterated prescriptions. ## 4.3. Statistical Analyses Descriptive statistics for continuous variables are presented using mean and standard deviation (SD), and dichotomous variables using number and percentage. 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--- title: 'Clinical Features of Diabetes Mellitus on Rheumatoid Arthritis: Data from the Cardiovascular Obesity and Rheumatic DISease (CORDIS) Study Group' authors: - Fabio Cacciapaglia - Francesca Romana Spinelli - Elena Bartoloni - Serena Bugatti - Gian Luca Erre - Marco Fornaro - Andreina Manfredi - Matteo Piga - Garifallia Sakellariou - Ombretta Viapiana - Fabiola Atzeni - Elisa Gremese journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10058987 doi: 10.3390/jcm12062148 license: CC BY 4.0 --- # Clinical Features of Diabetes Mellitus on Rheumatoid Arthritis: Data from the Cardiovascular Obesity and Rheumatic DISease (CORDIS) Study Group ## Abstract Rheumatoid arthritis (RA) and diabetes mellitus (DM) are linked by underlying inflammation influencing their development and progression. Nevertheless, the profile of diabetic RA patients and the impact of DM on RA need to be elucidated. This cross-sectional study includes 1523 patients with RA and no episodes of cardiovascular events, followed up in 10 Italian University Rheumatologic Centers between 1 January and 31 December 2019 belonging to the “Cardiovascular Obesity and Rheumatic DISease (CORDIS)” Study Group of the Italian Society of Rheumatology. The demographic and clinical features of DM RA patients were compared to non-diabetic ones evaluating factors associated with increased risk of DM. Overall, $9.3\%$ of the RA patients had DM, and DM type 2 was more common ($90.2\%$). DM patients were significantly older ($p \leq 0.001$), more frequently male ($$p \leq 0.017$$), with a significantly higher BMI and mean weight ($p \leq 0.001$) compared to non-diabetic patients. DM patients were less likely to be on glucocorticoids ($p \leq 0.001$), with a trend towards a more frequent use of b/ts DMARDs ($$p \leq 0.08$$), and demonstrated higher HAQ ($$p \leq 0.001$$). In around $42\%$ of patients ($$n = 114$$), DM diagnosis preceded that of RA. Treatment lines were identical in diabetic and non-diabetic RA patients. DM is a comorbidity that may influence RA management and outcome. The association between DM and RA supports the theory of systemic inflammation as a condition underlying the development of both diseases. DM may not have a substantial impact on bDMARDs resistance, although further investigation is required to clarify the implications of biological therapy resistance in RA patients. ## 1. Introduction Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by both local and systemic inflammation, ultimately leading to joint damage [1]. The global prevalence of RA has been estimated at around $0.46\%$ from studies conducted between 1980 and 2019 [2], and a similar prevalence ($0.48\%$) is reported for the Italian population [3]. The prevalence of RA is highest around the fifth decade of life and is generally higher in females than in males. [ 1,4]. Several inflammatory pathways are involved in the pathogenesis and development of RA, including pro-inflammatory cytokines such as tumor necrosis factor α (TNFα), interleukin 1 (IL-1), IL-6, and immune cells such as autoreactive CD4+ T cells, B cells and macrophages [1,5]. Local synovial inflammation characterizes the early stages of RA, subsequently expanding and becoming systemic due to the diffusion of inflammatory cytokines and immune cells. Systemic inflammation is supposed to damage tissues other than joints, such as the cardiovascular (CV) system [6]. Indeed, a high risk of CV events was observed in this patient population [7,8], and CV disease is the main contributor to the excess mortality that characterizes people with RA. [ 1]. Diabetes mellitus (DM) is a metabolic disease that affects over 530 million people globally, a number that is expected to rise in the next 25 years [9]. An estimated 3 million Italians ($5\%$ of the population and up to $16\%$ of those over 65) have diabetes [10]. In comparison to non-diabetic persons, diabetic patients, especially females and those with type 2 DM, have a two- to four-fold greater risk for CV events [11,12]. Diabetes patients frequently have obesity, insulin resistance, and uncontrolled hyperglycemia, all of which increase the risk of CV disease. Both type 1 and type 2 DM have inflammation-related pathogenesis, and some of the mediators of inflammation are also present in RA, suggesting a potential connection between these two diseases [13]. About $20\%$ of RA patients have DM as a comorbidity, and RA is linked to a higher risk of DM development [14,15]. Previous longitudinal studies have demonstrated a significantly higher and at least double CV risk in RA patients compared to the general population, comparable to the magnitude of CV events observed in type 2 DM [16,17]. Furthermore, the CARRÉ (CARdiovascular research and RhEumatoid arthritis) study found, in a prospective cohort examining CVD in long-term RA, an even higher risk in patients with RA compared to DM, and the association of RA with the two conditions of DM or insulin resistance was associated with the highest risk of developing CVD [18]. Therefore, treating both conditions with appropriate therapy is essential to slow the progression of these diseases and avoid CV events. The profile of diabetic RA patients and the impact of DM on RA progression are still debated. Therefore, the present study aimed to analyze the demographic and clinical features of RA patients with and without diabetes, describing possible differences in therapeutic management eventually responsible for a different profile of CV complications. ## 2. Patients and Methods RA patients included in this cross-sectional study fulfilled the 2010 American College of Rheumatology (ACR)/EULAR classification criteria [19] and were regularly evaluated and followed up with in 10 Italian University Rheumatologic Centers. The database of the “Cardiovascular Obesity and Rheumatic DISease (CORDIS)” Study Group was screened for consecutive patients with a medical examination between 1 January and 31 December 2019 [7]. The CORDIS study group is a non-profit study group established within the Italian Society of Rheumatology on the initiative of academic rheumatologists interested in the study of CV risk in rheumatic diseases. This group aims to understand the interrelation between inflammation, autoimmunity and CVD by collecting epidemiological, clinical and laboratory data from Italian patients with musculoskeletal rheumatic diseases. Patients were excluded if they presented prior CV events (acute coronary syndrome, that is, ST- and non-ST elevation myocardial infarction, coronary revascularization and unstable angina), stable angina pectoris, ischemic stroke and peripheral artery disease (with or without revascularization procedures), retrieved by review of medical charts [7]. Patients enrolled were characterized by the following clinical and serological data: age, sex, smoking status, body mass index (BMI), systolic and diastolic blood pressure, lipid profile, presence of DM, and hypertension. Dyslipidemia was defined by the use of lipid-lowering drugs and/or low-density lipoprotein (LDL) cholesterol targets, based on each patient’s CV risk, as recommended by the ESC/EAS guidelines for the management of dyslipidemia. [ 20]. Patients with hypertension had either a history of hypertension or made use of blood-pressure-lowering drugs. DM was defined based on previous medical history and/or the use of oral or parenteral hypoglycemic medications or insulin as reported [21]. Information on current treatments—ongoing anti-hypertensive, lipid-lowering therapies, and anti-rheumatic drugs, including conventional synthetic (cs) disease-modifying anti-rheumatic drugs (DMARDs), biologic (b) and targeted synthetic (ts) DMARDs and glucocorticoids (mean weekly dose since diagnosis and the current daily dose of prednisone or equivalent)—were recorded. In addition, rheumatoid factor (RF) and anti-citrullinated peptide antibodies (ACPA) were evaluated via serological assays [7]. At baseline, disease-specific factors such as disease duration, C reactive protein (CRP), disease activity index based on 28-joint evaluation (DAS28), and Clinical Disease Activity Index (CDAI) as measures of disease activity and the Health Assessment Questionnaire (HAQ) disability index as the function index were evaluated [22]. The present study was conducted according to the ethical guidelines of the Declaration of Helsinki and was approved by the local Ethical Committee as part of the GISEA Registry protocol (approval number DG-$\frac{624}{2012}$). At the start of the observational period, written informed consent was obtained from all patients. ## Statistical Analysis Data were expressed as mean ± standard deviation (SD) or $95\%$ confidence intervals ($95\%$ CI) when appropriate. Differences in continuous variables were evaluated using the paired t-test and/or repeated analysis of variance (ANOVA) followed by the Bonferroni post hoc test. Fisher’s exact test was used for categorical data to assess differences between the two groups. A p-value < 0.05 was considered statistically significant, while variables with a p-value < 0.1 in descriptive statistical analysis were evaluated with a logistic regression model and univariate analysis. Subsequently, variables that achieved statistical significance ($p \leq 0.05$) in univariate analysis were then included in a multivariate logistic regression model adjusted for age, sex, and disease duration. All analyses were performed using the SPSS statistic program (version 21—IBM software, New York, NY, USA). ## 3.1. Patient Demographics Overall, 1523 patients diagnosed with RA and with no previous CV events were included in the analysis. Demographics and clinical features of patients are reported in Table 1. Diabetic patients were $9.3\%$ of the total population, were significantly older than non-diabetic patients ($p \leq 0.001$), and were more frequently male ($$p \leq 0.017$$). In addition, diabetic patients had a significantly higher BMI and mean weight ($p \leq 0.001$) compared to non-diabetic patients. The prevalence of obesity, hypertension and use of antiplatelet drugs was also significantly higher in diabetic patients than in their non-diabetic counterparts ($p \leq 0.001$). Of note, 613 out of 649 ($94.4\%$) of our RA patients were on anti-hypertensive treatment with no significant differences among diabetic and non-diabetic patients (88 out of 93 vs. 525 out of 556—$$p \leq 0.93$$). Considering the disease-specific factors, diabetic patients demonstrated higher HAQ ($$p \leq 0.001$$) despite a similar mean duration of the disease. Patients with DM were less frequently on glucocorticoids ($p \leq 0.001$) and demonstrated a trend towards a more frequent use of b/tsDMARDs ($$p \leq 0.08$$). After logistic regression analysis adjusted for age, sex, and disease duration, the variables BMI, weight, obesity, hypertension, anti-platelets drugs, HAQ, and bDMARDs use were independently associated with an increased risk of DM in RA patients (Table 2). ## 3.2. Rheumatoid Arthritis Patients with Concomitant DM Specific clinical features of diabetic patients are reported in Table 3. The majority of RA diabetic patients ($90.2\%$) suffered from type 2 DM. Data about the time of onset, available for 114 patients, indicated that in around $42\%$ of patients, DM diagnosis preceded the diagnosis of RA. Diabetic-related complications were present in $\frac{29}{121}$ patients, and oral hypoglycemic drugs were the most used for the treatment of DM. ## 4. Discussion This cross-sectional study on a large cohort of RA patients included in the database of the “Cardiovascular Obesity and Rheumatic DISease (CORDIS)” Study Group of the Italian Society of Rheumatology indicated a prevalence of DM around $10\%$ among RA patients, suggesting that DM, as a frequent comorbidity, may influence the management and outcome of RA. When compared to non-diabetic RA patients, diabetic RA patients were older, more usually men, had a greater incidence of being overweight and obese, and were more frequently hypertensive. All these characteristics were confirmed after adjustment for age, sex and disease duration. Notably, diabetic RA patients were less likely to be on corticosteroids. However, after adjusting for sex, age and disease duration, we found that diabetic RA patients had a significantly higher probability of being on biological drugs, as evidenced by a significantly lower HAQ-DI among non-diabetic RA patients compared to diabetic ones, who are known to suffer from more comorbidities. This observation could be linked to a more severe disease course in RA patients with DM. The overall prevalence of diabetes mellitus (DM) was higher in our cohort of RA patients compared to osteoarthritis control subjects [7] and the general Italian population [10], supporting the theory that systemic inflammation and the concurrent use of glucocorticoids may contribute to the development of both diseases. There is a great deal of geographical heterogeneity in the data that are currently available [23,24] regarding the prevalence of DM in the RA community, ranging from $2\%$ in Ireland to $20\%$ in a German study [14]. A recent meta-analysis found that RA patients have a $23\%$ greater chance of developing DM [15]. Such inconsistency may be explained by differences in environmental exposure, lifestyle-related factors, geographic setting, study design, DM definition criteria (ICD-10 code, prescription of hypoglycemic drugs or insulin, physician diagnosis, fasting glucose concentration), selection of the comparison group, and characteristics of populations studied. However, studies show a consistent, significantly higher incidence of DM in RA patients compared to the general population [25,26,27]. Furthermore, when compared to the general population, type 2 DM was more prevalent in our RA patient cohort, which was previously reported by an Italian study [28]. Interestingly, we observed that DM onset, for about $58\%$ of patients, occurred after the diagnosis of RA. The onset of DM after RA may depend on different ages but can also suggest a role for glucocorticoids on the glycol-metabolic functions of such patients, as previously described [29]. In RA patients, glucocorticoid therapy has been associated with an increase in insulin resistance, a decrease in insulin sensitivity, and a higher risk of type 2 DM [30]. However, in our study, diabetic patients were less likely to be taking glucocorticoids at enrollment compared to non-diabetic RA patients, which may indicate an attempt by doctors to improve glycemic management [31]. This hypothesis is supported by the significantly higher prevalence of biological drugs prescribed to our diabetic patients as steroid-sparing medications, which is consistent with the EULAR recommendation to taper glucocorticoid doses in RA patients “as rapidly as clinically feasible” to prevent long-term side effects such as hyperglycemia and DM [32]. Additionally, EULAR guidelines for managing CV risk in people with inflammatory arthritis include restricting the use of glucocorticoids, which are linked to an increased risk of CV events and all-cause mortality, particularly in those with concurrent DM [23,33,34]. We cannot rule out the possibility that the cumulative dose of glucocorticoids in our population may have induced DM; at the time of data collection, the dose of prednisone prescribed was significantly lower in patients with RA and DM than in non-diabetic patients, possibly as a result of this comorbidity. Moreover, one should consider the beneficial effects of some conventional drugs, such as methotrexate and hydroxychloroquine, on glucose metabolism as well as the various effects of bDMARDs, such as tumor necrosis factor, IL-6, or IL-1 antagonists, on insulin resistance [30]. The increased risk of developing DM may be due to an inflammatory condition associated with RA, with the over-activation of TNFα and IL-6 pathways contributing to an increase in insulin resistance and causing DM [35]. Intriguingly, independent of BMI or specific RA therapy, such as the use of glucocorticoids, higher baseline disease activity and elevated levels of pro-inflammatory cytokines, including IL-1 and IL-6, are associated with a significantly higher risk of incident DM in RA patients [36]. This confirms the significant relation between systemic inflammation, insulin resistance, and the risk of developing DM in RA patients and highlights the significance of achieving optimal disease activity control in these patients. The results of the current study are noteworthy in that, although diabetic patients with RA received various pharmaceutical treatments, DM was not adequately controlled in about one-third of them, as evidenced by the average HbA1c values. As evidenced by a recent retrospective study reporting that around one-third of RA patients had baseline HbA1c levels ≥7, DM is underdiagnosed and not appropriately managed in diabetic RA patients, just as blood pressure is in RA patients with hypertension [37]. This suggests that it is crucial for RA patients to be aware of their glycometabolic profile, which needs to be managed appropriately. Under the current guidelines, metformin should be used as a first-line treatment for DM in RA patients or sodium-glucose cotransporter 2 inhibitors (such as empagliflozin) or glucagon-like peptide 1 receptor in those who have established CV disease or are at greater risk for developing it in the future [38]. The low DAS28 and CDAI scores within our group of patients demonstrate that several therapies recommended by various centers were effective in controlling RA activity. It is interesting to note that the number of treatment lines was identical in diabetic and non-diabetic RA patients, indicating that DM may not have a substantial impact on bDMARDs resistance. However, more investigation is required to clarify the implications of biological therapy resistance in RA patients [39,40]. Our analysis supports previous cohort study findings [41] that comorbidities are more common in diabetic patients, and it shows that DM risk in these individuals should not be attributed solely to inflammation. Particularly, our diabetic RA patients had significantly higher rates of hypertension and overweight/obesity. Such comorbidities are closely linked to DM [42,43]. Data on prevalence and control of hypertension in RA are discordant, showing higher prevalence but also underdiagnosis and higher or lower likelihood of antihypertensive treatment [38]. In our cohort, 649 ($42.6\%$) of patients had a previous diagnosis of hypertension and 613 of them ($94.4\%$) were taking anti-hypertensive drugs, with no differences among diabetic and non-diabetic patients. The coexistence of hypertension and diabetes is not fully unexpected; indeed, in the general population, hypertension is commonly associated with diabetes [44]. Moreover, RA patients also took glucocorticoids significantly more frequently, above all if non-diabetic. As is known, chronic glucocorticoid use may increase the risk of developing both hypertension and diabetes [45], and some anti-hypertensive agents can also improve glucose metabolism [46,47]. Comorbidities may have an impact on how patients with RA are managed and eventually their quality of life, which emphasizes the value of a customized therapeutic approach [48,49]. It is important to note some of our study’s shortcomings. To begin with, this is a cross-sectional study of a small sample; in addition, because this is an observational study, there are some missing data regarding DM characteristics and therapeutic care. Furthermore, this sort of study does not allow for speculation on the impact of treatment duration and the effect of RA treatments on DM outcome. The exclusion of patients with previous CV events might appear to be a bias. On the contrary, as the impact of a previous CV event on subsequent CV risk is well known, we opted for the evaluation of patients without a history of CV events to reduce the potential bias on the clinical management of RA and DM: patients with previous CV events have a peculiar therapeutic strategy and specific follow-up that might influence the clinical management of the underlying disease, both for RA and DM. The inclusion of consecutive RA patients treated according to local (Italian) indications in tertiary-level rheumatology centers may have selected a population with more severe disease. However, the fact that about $40\%$ of the entire study population was treated with bDMARDs indicates there was a balanced proportion of patients that would certainly have been higher if only patients with a more severe disease had been selected. Finally, residual confounding factors such as diet adherence and physical activity were not considered in data interpretation. Despite these drawbacks, the present study’s findings portray a real-life population indicative of all diverse Italian settings, allowing a more in-depth delineation of the characteristics and clinical management of DM as a comorbidity in RA patients. 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--- title: '2,5-Hexanedione Affects Ovarian Granulosa Cells in Swine by Regulating the CDKN1A Gene: A Transcriptome Analysis' authors: - Yige Chen - Chengcheng Kong - Min Yang - Yangguang Liu - Zheng Han - Liming Xu - Xianrui Zheng - Yueyun Ding - Zongjun Yin - Xiaodong Zhang journal: Veterinary Sciences year: 2023 pmcid: PMC10058995 doi: 10.3390/vetsci10030201 license: CC BY 4.0 --- # 2,5-Hexanedione Affects Ovarian Granulosa Cells in Swine by Regulating the CDKN1A Gene: A Transcriptome Analysis ## Abstract ### Simple Summary Porcine ovarian granulosa cells (pGCs), the main somatic cells in the follicular microenvironment, are close to oocytes. Under the action of various regulatory factors and exogenous substances, their abnormal proliferation, apoptosis and oxidative stress directly affect the quality of oocytes and embryonic development. Although 2,5-hexanedione (2,5-HD), a metabolite of n-hexane, has been linked to animal fertility in recent studies, the underlying mechanisms are still not clearly known. In this research, we aim to investigate the effects of different concentrations of 2,5-HD on cell morphology and apoptosis in pGCs. RNA-seq analyses revealed 4817 differentially expressed genes (DEGs) following 2,5-HD treatment. GO enrichment and KEGG pathway analysis suggested that the DEG, CDKN1A, was significantly enriched in the p53 signaling pathway that had the functions of apoptosis, growth inhibition and inhibition of cell cycle progression. After the interference of the CDKN1A gene, we found that it decreased pGC apoptosis, with lower cells in the G1 phase and higher cells in the S phase. Through a 2,5-HD cytotoxicity study and transcriptome bioinformatics analysis, these results deepen our understanding of the toxicological effects of 2,5-HD on porcine ovarian granulosa cells (pGCs), which is expected to help to understand the toxic mechanism of 2,5-HD in the female animal reproductive system. ### Abstract N-hexane, a common industrial organic solvent, causes multiple organ damage owing to its metabolite, 2,5-hexanedione (2,5-HD). To identify and evaluate the effects of 2,5-HD on sows’ reproductive performance, we used porcine ovarian granulosa cells (pGCs) as a vehicle and carried out cell morphology and transcriptome analyses. 2,5-HD has the potential to inhibit the proliferation of pGCs and induce morphological changes and apoptosis depending on the dose. RNA-seq analyses identified 4817 differentially expressed genes (DEGs), with 2394 down-regulated and 2423 up-regulated following 2,5-HD exposure treatment. The DEG, cyclin-dependent kinase inhibitor 1A (CDKN1A), according to the Kyoto Encyclopedia of Genes and Genomes enrichment analysis, was significantly enriched in the p53 signaling pathway. Thus, we evaluated its function in pGC apoptosis in vitro. Then, we knocked down the CDKN1A gene in the pGCs to identify its effects on pGCs. Its knockdown decreased pGC apoptosis, with significantly fewer cells in the G1 phase ($p \leq 0.05$) and very significantly more cells in the S phase ($p \leq 0.01$). Herein, we revealed novel candidate genes that influence pGCs apoptosis and cell cycle and provided new insights into the role of CDKN1A in pGCs during apoptosis and cell cycle arrest. ## 1. Introduction N-hexane is a type of volatile organic solvent that is mainly utilized in industrial printing, electronic device cleaning, oil extraction, and leather adhesion [1]. Inhaled n-hexane can be absorbed and can then be transported to lipid-rich tissues and organs such as the brain, peripheral nerves, liver, spleen, and kidneys [2,3,4]. Long-term exposure to n-hexane causes severe neuropathy in both humans and experimental animals [5]. An earlier study showed that the body’s primary metabolite of n-hexane was 2,5-hexanedione (2,5-HD) [6]. However, present studies on the toxicity of 2,5-HD have mainly focused on neurotoxicity [7,8,9] and testicular toxicity [10]. Despite the fact that previous studies have shown that n-hexane has harmful effects on the central and peripheral nervous systems [11,12,13], its toxic mechanisms on the female reproductive system have remained unclear. The ovary is an important reproductive organ of mammals, and an abnormal ovulation process will directly affect the reproductive performance of female animals. The proliferation, apoptosis, and functional differentiation of ovarian granulosa cells are of great significance to the ovary, the growth and development of follicles, and the formation of the corpus luteum. Ovarian granulosa cells are essential for oocyte development [14]. N-hexane may directly mediate granulosa cell apoptosis by changing hormone secretion, which may be one of the important mechanisms of n-hexane-induced ovarian dysfunction in mice [15]. Sun et al. discovered that in human ovarian granulosa cells, BAX and active CASPASE-3 (p17) expression significantly increased in a dose-dependent manner, while BCL-2 expression reduced with increasing 2,5-HD concentrations [16]. Apoptosis was the mechanism of germ cell loss in 2,5-HD-induced testicular injury [17]. When the testes were treated with 2,5-HD, it increased the retention time of the sperm head in the semen and decreased sperm motility [18]. Exploring the mechanism for the cytotoxic effect of 2,5-HD on ovarian granulosa cells would thus prove meaningful. In this study, we explored the toxicological effects of 2,5-HD on porcine ovarian granulosa cells (pGCs) via a 2,5-HD cytotoxicity study and RNA-seq. The findings of the present study are expected to contribute to a better understanding of the molecular biological mechanism by which 2,5-HD causes apoptosis in ovarian granulosa cells. ## 2. Materials and Methods The entire procedure was carried out exactly in accordance with the guidelines approved by the Anhui Agricultural University Animal Ethics Committee under Permission No. AHAU20180615. ## 2.1. Porcine Ovarian Granulosa Cells (pGCs) Culture In Vitro and under 2,5-HD Treatment Fresh porcine ovaries ($$n = 60$$, from Landrace, approximately 180 days old) with a bright surface, healthy development, full follicles, and more antral follicles were obtained from a commercial slaughterhouse (Hefei, Anhui, China), around which the fatty tissue was removed. The ovaries were maintained in sterile saline solution at 37 °C containing $1\%$ penicillin/streptomycin mixture and delivered to the lab within 1 h in a thermos flask. Avoiding blood vessels, the follicular fluid was collected from ovarian follicles ($$n = 300$$, 3–6 mm in diameter) [19] by using the injector (1 mL), washed, centrifuged (1000× g, 5 min), resuspended, and centrifuged again, and the pGCs were then harvested. The cells were cultivated at 37 °C and $5\%$ CO2 in Dulbecco’s modified Eagle medium/Nutrient Mixture F-12 medium (DMEM/F12, Gibco, Grand Island, NY, USA) containing $10\%$ fetal bovine serum (FBS) (Gibco, Carlsbad, CA, USA), 100 units/mL penicillin, and 100 mg/mL streptomycin (Gibco, Carlsbad, CA, USA) after being seeded into a 60 mm cell-culture dish (Corning, 430166, Somerville, MA, USA). 2,5-HD was purchased from Macklin (Shanghai, China), and its purity was determined to be greater than $99.5\%$. The 2,5-HD solution was dissolved in pure water to create a 100 mol/mL stock solution. The primary pGCs could be passaged at approximately $80\%$ confluence (the primary pGCs completely stretched and occupied approximately $80\%$ of the cell culture dish surface; about one week), and the pGCs were inoculated in a 12-well plate (Corning, 430166, USA) at a density of 8~10 × 105 cells as calculated by the cell count plates (Watson, 177–122c, Kobe, Japan) and allowed to attach for 12 h. Flow cytometry was used to detect the purity of pGCs (the cells’ purity degree was > $90\%$). Then, the cells were treated with 2,5-HD (0 mmol/L, 20 mmol/L, 40 mmol/L, 60 mmol/L) at 37 °C for 24 h, and the same growth cell culture medium was used to treat the control group (three biological repeats in both the treatment and control groups). The dose and reagent treatment time used in this experiment were based on previous studies that revealed the toxic effects on rat and sows’ ovarian granulosa cells [20,21] in vitro using this concentration and time. ## 2.2. Cell Morphological Observations After treatment with 2,5-HD (0 mmol/L, 20 mmol/L, 40 mmol/L, 60 mmol/L) for 24 h, we used a microscope (Leica Microsystems DM2500, Wetzlar, Hessen, Germany) to examine the cellular morphology photographs. ## 2.3. Cell Apoptosis Detection The pGCs were treated with 2,5-HD (0 mmol/L, 20 mmol/L, 40 mmol/L, 60 mmol/L) for 24 h and were collected according to the instructions of the cell flow kit (Annexin V-FITC/PI,BB-4101, Bestbio, Shanghai, China) [22] and pretreated. The pGCs were collected, pretreated, trypsinized for 1 min, centrifuged (1000× g, 3 min), washed twice with PBS, resuspended in 500 µL of binding buffer containing 5 µL Annexin V-fluorescein isothiocyanate (FITC) and 10 µL propidium iodide (PI) (Bestbio, Shanghai, China). Finally, a FACS Calibur flow cytometry device (FACSCalibur, BD, Franklin Lakes, NJ, USA) was used to calculate the quantity of stained cells. ## 2.4. Phalloidin Staining The pGCs were inoculated in a 12-well plate and allowed to attach for 12 h. Cells were then treated with 2,5-HD media (0 mmol/L, 20 mmol/L, 40 mmol/L, 60 mmol/L) at 37 °C for 24 h. After about 45 min of incubation at room temperature in a dark area, an antifade substance containing fluorescein isothiocyanate (FITC) was injected into the cells, which were then rinsed with PBS for 10 min. FITC-phalloidin (Solarbio CA1620, Beijing, China) was added for 30 min of re-staining, followed by 10 μL of anti-fluorescence quenching tablets containing 4′,6-diamidino 2-phenylindole (DAPI) to obtain FITC-phalloidin-labeled cytoskeleton and DAPI-labeled cellular nuclei. Finally, a fluorescent microscope (Leica Microsystems DM2500, GER) was used to view the cells. ## 2.5. EDU Staining EDU (5-ethynyl-2′-deoxyuridine) staining enables quick and effective cell proliferation assays to accurately measure the proportion of cells in the S phase. Therefore, using EDU staining in accordance with the manufacturer’s instructions, the proliferation of pGCs was determined. After treatment with 0 mmol/L, 20 mmol/L, 40 mmol/L, and 60 mmol/L 2,5-HD for 24 h, cells were cultured in phenol red-free DMEM/F12 with 50 μM EdU (RiboBio, Guangzhou, China) staining for 2 h [23,24]. Cells were then rinsed two times with 0.02 M PBS (pH = 7.2) at 5-min intervals before being immobilized for 30 min with $4\%$ paraformaldehyde (Biosharp, Hefei, China). Following that, cells were treated for 5 min with glycine (Biosharp, Hefei, China) (2 mg/mL) and rinsed for 5 min with PBS [23,24]. After 30 min of DAPI (0.5 μg/mL) (Biosharp, Hefei, China) staining [23], three rounds of PBS washing were conducted at 5-min intervals. Lastly, a Leica DM4000 BLED microscope (Leica Microsystems DM2500, GER) was used to observe the fluorescence in cells. ## 2.6. Total RNA Extraction, Library Construction, and Sequencing Analysis With the above results, we proceeded to extract RNA and performed transcriptome sequencing. pGCs were plated into a 55-cm2 cell culture dish and grown in DMEM/F12 with or without 2,5-HD (40 mmol/L) for 24 h. As stated in our previous report, the treatment and control groups’ total RNA was extracted [25]. Thereafter, the RNA was purified with the RNeasy Mini Kit (Qiagen, Hilden, Germany) and delivered to Majorbio (Shanghai, China). The Nanodrop2000 and Agilent 2100 systems were employed to determine total RNA concentration, purity, and integrity. RNA qualities were found to meet the requirements for database sequencing (Table 1). The mRNA was then fragmented with a fragmentation buffer after being enriched with oligo dT. The cleaved RNA fragments were then reverse-transcribed to create the final cDNA library. We connected an Illumina Hiseq. 4000 [23] (Illumina, San Diego, CA, USA) to an adaptor and carried out paired-end sequencing in accordance with the recommended procedure from the manufacturer. Using the DESeq R program (1.18.0), differentially expressed genes (DEGs) were found. Both values of a fold change (log2FC) and the FDR (FDR = p-value corrected for multiple hypothesis tests) were used to filter the significant or insignificant DEGs. These statistical procedures use a model based on the negative binomial distribution to identify differential expression among digital gene expression data. To reduce the rate of false discovery, Benjamini and Hochberg’s method was used to adjust the resulting p-values, and an adjusted $p \leq 0.05$ was deemed statistically significant. Gene ontology (GO; http://www.geneontology.org/, accessed on 28 October 2022) and the Kyoto Encyclopedia of Genes and Genomes (KEGG; http://www.genome.jp/kegg, accessed on 5 November 2022) were used to find the enriched pathways and the statistically enriched genes. ## 2.7. Quantitative PCR Quantitative real-time PCR was used as proof that high-throughput sequencing was accurate. To detect the expression trend of the sequencing results, 12 genes were chosen at random. TRIzol reagent (Invitrogen Corporation, Carlsbad, CA, USA) was used to extract the cells’ total RNA, and the Primer-Script RT reagent Kit (TaKara, Tokyo, Japan) was used to reverse-transcribe the extracted total RNA into cDNA. The CFX96 Touch Real-Time PCR Detection System (Bio-Rad, Hercules, CA, USA) was used for qRT-PCR analysis. Based on sequence data of the NCBI database (www.ncbi.nlm.nih.gov/genbank, accessed on 20 November 2022), the specific primers utilized for RT-PCR were designed or modified by Primer Premier 6.0 software (Premier Biosoft International, Palo Alto, CA, USA) [26] and are listed in Table 2. The thermal cycling program consisted of 95 °C for 30 s, followed by 40 cycles at 95 °C for 5 s and 60 °C for 30 s. The housekeeping gene glyceraldehyde-3-phophate dehydrogenase (GAPDH) was used to standardize the expression levels of the genes, and the changes in relative gene expression were computed by the 2−ΔΔCt method. Significant differences were evaluated by Student’s t-test using SAS software (version 9.0), and a value of $p \leq 0.05$ was considered to be significant, which was calculated at least three times from independent biological replicates. ## 2.8. CDKN1A Interference For interference of CDKN1A, small interfering RNA (siRNA) was purchased from Ribobio (Guangzhou, China) (Table 3). pGCs in the logarithmic phase were collected and inoculated at a density of 8~10 × 105 on a 6-well plate. According to the instructions of the transfection kit (Ribobio, Guangzhou, China) [27,28], siRNA-CDKN1A, negative control (siRNA-NC), and 12 μL riboFECT CP Reagent [29,30] (Ribobio, Guangzhou, China) were co-incubated with cells. Then, 48 h after transfection, the pGCs were collected. Thereafter, cells were used for RNA extraction, measuring the cell apoptotic rate and cell cycle detection. Transfection was carried out utilizing the Lipofectamine 3000 reagent (Invitrogen, Waltham, MA, USA). ## 2.9. Statistical Analysis All experiments were performed in triplicate, and all data were expressed as mean ± standard deviation (SD)with Student’s t-test. One-way ANOVA was carried out to determine significant differences in the experiment data in triplicate. The statistical analyses were performed with SAS software Version 8.01 (SAS Institute Inc.; Cary, NC, USA). Statistical significance was defined as $p \leq 0.05$, with very significant findings classified as $p \leq 0.01$ and extremely significant findings as $p \leq 0.001.$ ## 3.1. Effect of 2,5-HD on pGC Morphology We randomly selected five regions to obtain the cell morphology results. As shown in Figure 1, the granulosa cells of the control group were fusiform or irregularly polygonal, fully stretched, tightly arranged, translucent, and displayed adequate adhesion. The cells displayed dendritic connections with an increase in the mass concentration of 2,5-HD (24 h, 40 mmol/L). When the concentration of 2,5-HD was increased to a certain degree (24 h, 60 mmol/L), the pGCs grew spherically, and some cells were detached and suspended. After that, actin skeletons were stained with FITC-phalloidin (green), and cell nuclei were stained with DAPI (blue). The control group granulosa cells were attached and spread, accompanied by discrete bundles of actin fibers. Less prominent expansions to neighboring cells that remained clustered and an unorganized cytoskeleton were present in the 2,5-HD-treated group of cells (Figure 2). ## 3.2. Effect of 2,5-HD on Apoptosis of pGCs The results of Annexin V-FITC/PI double staining and flow cytometry showed that the effect of 2,5-HD treatment on the apoptotic rate of pGCs was dose-dependent, and the 20 mmol/L (24 h) treatment group had a significantly higher rate of pGC apoptosis than that the control ($p \leq 0.05$). The difference in the apoptotic rate became even more pronounced when the 2,5-HD concentration was at 40 mmol/L (24 h) and 60 mmol/L (24 h) ($p \leq 0.01$) (Figure 3). ## 3.3. Effect of 2,5-HD on pGC Proliferation Cellular and chromatin ultrastructures that have been maintained well can be stained with EDU to identify cell proliferation. We randomly selected five regions to obtain the staining results. Images were first captured, and the results obtained with the images were used to perform a difference analysis. As shown in Figure 4, the percentage of EDU-positive cells was significantly lower in the 2,5-HD-treated group (20 mmol/L, 24 h) than in the control group ($p \leq 0.01$). Proliferation-free cells were discovered in the randomly selected fields of the 40 mmol/L (24 h) group and the 60 mmol/L (24 h) group. These results demonstrated that a 40 mmol/L (24 h) 2,5-HD treatment inhibited the proliferation of pGCs. After pGCs were exposed to 2,5-HD, chromatin condensation and a larger nucleus were discovered, as shown in Figure 5 by DAPI staining. Analysis of cell morphology, proliferation, and apoptosis revealed that a treatment period of 24 h at a dose of 40 mmol/L (2,5-HD) was ideal for further study. In fact, after 24 h of treatment, the pGCs also displayed dendritic connections with an increase in the mass concentration of 2,5-HD, the apoptotic rate changes reached very significant levels between the 2,5-HD-treated group (40 mmol/L, 24 h) and the normal control group ($p \leq 0.01$), and no proliferating cells were found in the 2,5-HD-treated group (40 mmol/L, 24 h). Finally, we chose 0 mmol/L and 40 mmol/L for the RNA-seq analysis experiments that followed (three biological replications). ## 3.4. Gene Expression Profiling The sequencing results showed 8,262,103,500 and 11,571,998,400 bp raw reads in each group. Q20 (base sequencing error probability < $1\%$) > $97\%$ and Q30 (base sequencing error probability < $0.1\%$) > $94\%$ were achieved for each group, indicating good data quality (Table 4). Six sample gene expression patterns were used for principal component analysis (PCA), and sample correlations were projected onto the first two principal components (Figure 6). Three biological replicates of gene expression showed a consistent pattern, and the sequencing quality turned out to meet the standards for additional analyses. ## 3.5. Analysis of DEGs According to the DEGs discovered in the 2,5-HD (0 mmol/L and 40 mmol/L for 24 h) treatment group of pGCs, gene and pathway analyses were conducted. A total of 22,955 genes were obtained from the RNA-seq results by comparing them to the reference genome from Scrofa11.1 of Ensembl (http://www.ensembl.org/, accessed on 16 October 2022). The significant DEGs’ relative transcription levels were shown by a fold change \|log2FC\| > 1 and FDR < 0.05 (Figure 7A); a fold change \|log2FC\| ≤ 1 and FDR ≥ 0.05 was regarded as insignificant. Nonetheless, the analysis showed up to 4817 DEGs (Table S1). Of these, 2423 were up-regulated, while 2394 were down-regulated (Figure 7B).To verify the reliability of sequencing data, six genes (IRAK2, SLC7A11, SPP1, CDKN1A, CASP3 and MDM2) that were significantly up-regulated in the treatment group (2,5-HD 40 mmol/L, 24 h) and six genes (MYCL, RENBP, DKK2, F3, MYH11 and BCLAF1) that were significantly down-regulated in the normal control group (2,5-HD 0 mmol/L, 24 h) were randomly selected for RT-qPCR verification. These qRT-PCR results aligned with the sequencing results, indicating the reliability of RNA-Seq data (Table 5 and Figure 8). ## 3.6. KEGG and GO Analysis For a more in-depth view of the identified DEGs, we conducted GO and KEGG pathway enrichment analyses. The three GO categories—biological process, cellular component, and molecular function—were used to group together all of the GO terms associated with DEGs. The results of the enriched analysis revealed that, for the biological process, cellular component, and molecular function categories, 67, 26, and 13 GO terms were significantly enriched ($p \leq 0.05$) (Table S2), respectively. The DEGs were mainly involved in different developmental processes, including intracellular, organelle, and binding. The top 20 enriched GO terms are shown in Figure 9A, which demonstrates that the majority of the biological process are linked to cell activity, such as the cell cycle (Tables S2 and S3). In KEGG enrichment, we found the p53 signal pathway was one of the important metabolic pathways with the smallest Q value (Q value= p-value following corrections from multiple hypothesis tests) (Figure 9B and Tables S4 and S5). The activation of the p53 signaling pathway is mainly induced by DNA damage, oxidative stress, and oncogene expression and plays a positive role in promoting cell apoptosis, regulating the cell cycle, and preventing tumorigenesis [31]. Moreover, the PI3K/Akt signaling pathway, with its ovarian-relevant functions of the recruitment of primordial follicles, the proliferation of granulosa cells (GCs), the formation of the corpus luteum, and oocyte maturation [32], was also significantly enriched (Q value < 0.05) (Figure 9B and Table S6). It should be noted that, through function analysis, we discovered that the CDKN1A gene was significantly up-regulated in 2,5-HD-exposed pGCs compared with the control group, which was involved in apoptosis, the regulation of the cell cycle, and follicular development. Then, we used interference of CDKN1A for transfection to reduce its expression to further demonstrate the regulation of CDKN1A gene on pGCs. ## 3.7. Effect of CDKN1A on Apoptosis of pGCs RNA interference was utilized to reduce CDKN1A expression in pGCs cultivated in vitro to investigate the role of CDKN1A in the apoptosis of pGCs. By qPCR analysis, CDKN1A expression was significantly lower in pGCs transfected with the CDKN1A-siRNA than it was in pGCs transfected with the NC-siRNA ($p \leq 0.05$) (Figure 10A). After transfection, the rate of apoptosis was lower in the CDKN1A-siRNA group than in the CDKN1A-NC group according to flow cytometry analysis and a quantitative histogram; nevertheless, the difference was not statistically significant ($p \leq 0.05$) (Figure 10B,C). ## 3.8. Effect of CDKN1A on the Cycle of pGCs To investigate the periodic distribution of cells in the transfected and control groups, pGCs were measured by flow cytometry for 48 h after transfection. As shown in Figure 11, the G1 phase had a significantly lower number of cells ($p \leq 0.05$), while the S phase had a very significantly higher number of cells compared to the control group ($p \leq 0.01$). These findings revealed that CDKN1A-siRNA could promote the transition of pGCs from the G1 phase to the S phase, decrease cell cycle arrest of pGCs in the G1 phase, and increase pGC proliferation. ## 4. Discussion pGCs are an important class of ovarian cells located outside the zona pellucida. Granulocytes play a vital role in the regulation of ovarian function, and prior research has demonstrated that granulosa cells perform a critical function in the regulation of follicular atresia [12,33]. As the apoptosis of granulosa cells may have a major impact on reproductive efficiency [34], the apoptosis of pGCs may play an important role in the study of follicular atresia and oocyte development. The toxicity of 2,5-HD has been extensively studied [21]. In fact, previous studies have revealed that it destroys female reproductive function and leads to a decrease in fertility [35,36]. 2,5-HD can significantly prolong the estrous cycle of female rats, with the ovary serving as one of the potential target gonads of n-hexane toxicity [37]. Through the present study, we demonstrated that treatment of pGCs with 2,5-HD can cause morphological changes. In particular, we revealed that it could increase the apoptotic rate of cells and inhibit cell proliferation. A previous study revealed an increase in the apoptosis of human neuroblastoma SK-N-SH cells exposed to 2,5-HD (3.3 +/− 10.1 mM) [38]. Additionally, other studies have demonstrated that HD (500 nM similar to 50 mM) dose-dependently suppresses the proliferation and viability of murine neural progenitor cells (NPCs) and increases the production of reactive oxygen species (ROS). HD (10 or 50 mg/kg for 2 weeks) inhibited hippocampal neuronal and NPC proliferation in male 6-week-old ICR mice, primary neuronal culture, and young adult mice [12]. The study findings indicated that 2,5-HD (5 and 10 mmol/L) could decrease the viability of pheochromocytoma cells (PC12) and promote apoptosis via oxidative injury in a concentration-dependent manner [39]. Mitochondrial-dependent apoptosis was also found to be induced by HD through NGF suppression, which occurs via the PI3K/Akt pathway, both in vivo and in vitro [40]. The results of the present investigation supported earlier findings about morphological alterations and the impacts of 2,5-HD on apoptosis and proliferation. According to the 2,5-HD cytotoxicity experiments with pGCs and RNA-seq, we obtained important information, including the ten genes with the highest differential expression (the 10 with the highest fold change value). Sulfiredoxin (SRXN1) was previously found to be associated with cerebrovascular disease in a Finnish cohort [41], and SRXN1 genetic polymorphisms were associated with breast cancer risk and survival [42]. SRXN1 is, therefore, necessary for resolving GnRH-induced oxidative stress and inducing gonadotropin gene expression [42]. Wang et al. [ 43] found that CCNG2 encoded an unconventional cyclin homolog, cyclin G2(CycG2), which is associated with growth inhibition and significantly correlated with lymph node metastasis, histological grade, and poor overall survival in numerous cancer types. The ANKRD1 mutations may cause DCM as a result of disruption of the normal cardiac stretch-based signaling [44]. The GREM1 gene is associated with diabetic nephropathy [45], while Id3 governs the downstream mitogenic processing via depressing p21(WAF1/Cip1), p27(Kip1), and p53 [46]. A previous study showed that CCL2 is an inflammatory mediator with proinflammatory activity in breast cancer [47]. These known functions support our conclusion of the effects of 2,5-HD. The GO enrichment results revealed that the DEGs were primarily connected to developmental processes, cellular developmental processes, cell proliferation, cell cycle, cellular component organization, and other important terms. Furthermore, 11 significantly enriched pathways were also found, including the p53 signaling pathway, MAPK signaling pathway, renin secretion, amino sugar and nucleotide sugar metabolism, PI3K-Akt signaling pathway, and other important metabolic pathways. The p53 signaling pathway, activated by DNA damage, oxidative stress, and proto-oncogene activity, plays important roles in promoting apoptosis, regulating the cell cycle, and preventing tumorigenesis [31,48,49]. N-hexane can induce or enhance the production of oxygen free radicals in organisms, damage lipid peroxidation, and induce DNA damage in rat hepatic cells [50]. Studies have shown that oxidative stress damage from exposure to n-hexane and its metabolite 2,5-HD can damage ovarian cells, which will affect the endocrine function of the ovary [51]. An earlier study found that 2,5-HD promoted apoptosis in mesenchymal stem cells and proposed that the activated mitochondria-dependent caspase-3 pathway may be involved in 2,5-HD-induced apoptosis [1]. The p53-induced Siva-1 gene expresses an effector molecule that plays a significant role in DNA damage-induced cell death [31]. High doses of 2,5-HD induce apoptosis by activating the p53 pathway through genetic toxicity and oxidative stress effects. The major up-regulated genes enriched in the p53 signaling pathway are activators of the apoptosis execution factors; the PMAIP1 gene directly binds to Bax or Bcl2 antagonist/killer 1 to increase human granulosa cell proapoptotic activity [52]. The overexpression of IGFBP3 can promote cell proliferation and migration [53]. The CASP3 gene can cause morphological and biochemical changes in the cells of the body, resulting in apoptosis [54,55]. The phosphatidylinositol 3-kinase (PI3K)-Akt signaling pathway can be activated by various types of cellular or toxic stimuli, thereby regulating basic cellular functions, including transcription, translation, proliferation, growth, and survival [56,57]. A prior study also showed that 2,5-HD down-regulates rat spinal nerve growth factor and induces neuronal apoptosis by inhibiting the PI3K-Akt signaling pathway [58]. In this study, the cell cycle-driving cyclin proteins (CCND1, CCND3) were significantly down-regulated and enriched within the PI3K-Akt pathway, which inhibited follicular development by inhibiting cell cycle progression and granulosa cell proliferation. The p53 signaling pathway was found to be significantly enriched in this study, and previous research indicated that it is the primary pathway involved in apoptosis. Interestingly, CDKN1A, also known as p21 (WAF1/CIP1), was demonstrated to be involved in the cell cycle [59]; such a finding attracted our attention in the current study. CDKN1A is implicated in the regulation of cell growth and cell response to DNA damage [60]. The p21 protein may function during development as an inducible growth inhibitor that contributes to cell cycle exit and differentiation [61]. circGRAMD1B plays an important role in GC progression by regulating miR-130a-3p-PTEN/p21 [62]. NeuroD1-silencing induces the expression of p21, a master regulator of the cell cycle, leading to G2-M phase arrest and the suppression of colorectal cancer cell proliferation and the potential of colony formation [63]. CDKN1A was also selected as an important candidate gene affecting cell cycle and apoptosis. Therefore, exogenous stimulation caused pGC DNA damage, and p21(CDKN-1A) was involved in apoptosis in a p53-dependent approach. CDKN1A modulates the cell cycle, apoptosis, senescence, and differentiation via specific protein–protein interactions with cyclins and cyclin-dependent kinase (Cdk) [64]. In the present study, CDKN1A was demonstrated to induce the apoptosis of pGCs and cell cycle arrest in G1. However, the apoptosis rate of pGCs after transfection was not significantly different compared to the control group ($p \leq 0.05$). According to the previous reports, it was found that cell cycle uncoupling occurred after the knockout of the p21 gene in the human colon adenocarcinoma cell line HCT116, which was treated with multiple DNA damage agents [65]. Therefore, we speculated that the insignificant difference between CDKN1A-siRNA and CDKN1A-NC in the apoptotic rate of pGCs may be due to the uncoupling of the cell cycle caused by the inhibition of p21 (CDKN1A) expression, which leads to polyploid giant cells returning to the S phase and, eventually, death. These results were consistent with our cell cycle experiment: CDKN1A interference promoted the percentage of cells in the S phase. Meanwhile, the relationship between exogenous p21 expression and apoptosis was controversial. P21 induced apoptosis in some cells, while resisting p53-induced apoptosis in others [66]; the specific mechanisms and principle need to be further studied. Moreover, a chemically induced fibrosarcoma model was utilized to demonstrate that p53 and CDKN1A cooperate in mediating cancer resistance [67]. Strong p21 accumulation suppresses the CDK inhibitory activity of E2F-dependent transcriptional processes and cell cycle arrest in G1 [68,69]. ## 5. Conclusions In conclusion, we demonstrated that 2,5-HD could affect the proliferation and apoptosis of pGCs in pigs. 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--- title: Advanced Oxidation Protein Products Contribute to Chronic-Kidney-Disease-Induced Adipose Inflammation through Macrophage Activation authors: - Nanaka Arimura - Hiroshi Watanabe - Hiromasa Kato - Tadashi Imafuku - Takehiro Nakano - Miyu Sueyoshi - Mayuko Chikamatsu - Kai Tokumaru - Taisei Nagasaki - Hitoshi Maeda - Motoko Tanaka - Kazutaka Matsushita - Toru Maruyama journal: Toxins year: 2023 pmcid: PMC10059001 doi: 10.3390/toxins15030179 license: CC BY 4.0 --- # Advanced Oxidation Protein Products Contribute to Chronic-Kidney-Disease-Induced Adipose Inflammation through Macrophage Activation ## Abstract Fat atrophy and adipose tissue inflammation can cause the pathogenesis of metabolic symptoms in chronic kidney disease (CKD). During CKD, the serum levels of advanced oxidation protein products (AOPPs) are elevated. However, the relationship between fat atrophy/adipose tissue inflammation and AOPPs has remained unknown. The purpose of this study was to investigate the involvement of AOPPs, which are known as uremic toxins, in adipose tissue inflammation and to establish the underlying molecular mechanism. In vitro studies involved co-culturing mouse-derived adipocytes (differentiated 3T3-L1) and macrophages (RAW264.7). In vivo studies were performed using adenine-induced CKD mice and AOPP-overloaded mice. Fat atrophy, macrophage infiltration and increased AOPP activity in adipose tissue were identified in adenine-induced CKD mice. AOPPs induced MCP-1 expression in differentiated 3T3-L1 adipocytes via ROS production. However, AOPP-induced ROS production was suppressed by the presence of NADPH oxidase inhibitors and the scavengers of mitochondria-derived ROS. A co-culturing system showed AOPPs induced macrophage migration to adipocytes. AOPPs also up-regulated TNF-α expression by polarizing macrophages to an M1-type polarity, and then induced macrophage-mediated adipose inflammation. In vitro data was supported by experiments using AOPP-overloaded mice. AOPPs contribute to macrophage-mediated adipose inflammation and constitute a potential new therapeutic target for adipose inflammation associated with CKD. ## 1. Introduction Chronic kidney disease (CKD) patients often experience metabolic diseases such as insulin resistance and dyslipidemia, which are a risk factor for cardiovascular disease and can shorten life expectancy [1,2]. Recently, fat atrophy, which is a decrease in whole-body adipose tissue, has been found to be associated with the pathogenesis of metabolic symptoms in CKD [3,4]. Adipose tissue plays an important role in maintaining the homeostasis of systemic energy metabolism by storing excess energy and generating free fatty acids through lipolysis as required. Therefore, adipose tissue dysfunction results in a reduced fat storage capacity and ectopic lipid deposition in tissues such as the liver and skeletal muscle. This ectopic lipid deposition contributes to the development of metabolic diseases [5,6]. Although decreased fat mass is associated with increased mortality in hemodialysis patients [7], the underlying mechanism through which fat atrophy occurs during CKD has not been determined. Fat atrophy occurs via increased lipolysis, which is related to dysfunctional adipose tissue. Inflammatory cytokines (TNF-α and IL-6) released from adipocytes are thought to be implicated in this lipolysis [8,9,10]. In general, macrophage infiltration is involved in the chronic inflammation of adipose tissue, and macrophage infiltration occurs with the increased expression of the monocyte chemotactic factors (MCP-1, etc.) associated with increased oxidative stress in adipose tissue [11,12]. The TNF-α released from infiltrating macrophages induce inflammatory cytokine production in adipocytes, causing chronic inflammation throughout the adipose tissue [13]. Macrophage accumulation in adipose tissue, adipose inflammation and ectopic lipid deposition in the liver and skeletal muscle have been reported in both CKD patients and CKD animal models [14,15]. However, the molecular mechanisms underlying the induction of adipose inflammation in CKD remain unclear. The level of serum advanced oxidation protein products (AOPPs), which are uremic toxins, increases during CKD pathology resulting in oxidative stress [16]. AOPPs are oxidatively modified proteins that are generated via a reaction with chlorinated oxidants such as the hypochlorous acid (HOCl) produced via myeloperoxidase in neutrophils. The HOCl oxidatively modifies serum proteins (mostly albumin) via carbonylation and the formation of dityrosine [17]. Previously, AOPPs have been reported to increase oxidative stress, which contributes to the pathogenesis of renal tubular disorders, osteoporosis, and Crohn’s disease [18,19,20]. Recently, we also reported that AOPPs are involved in the pathogenesis of CKD-induced sarcopenia through the enhanced production of reactive oxygen species (ROS) via the CD36/NADPH oxidase pathway in muscle cells [21]. However, the relationship between fat atrophy/adipose tissue inflammation and AOPPs has remained unknown. The purpose of this study was to determine the involvement of AOPPs in adipose tissue inflammation and to establish its molecular mechanism. First, using adenine-induced CKD mice, we evaluated fat atrophy, macrophage infiltration and the activity of AOPPs in adipose tissue. Next, using mouse-derived 3T3-L1 adipocytes and a mouse macrophage-like cell line (RAW264.7), we investigated the molecular mechanisms of adipose inflammation induced by AOPPs. Finally, we examined AOPP-induced adipose tissue inflammation using AOPP-overloaded mice. ## 2.1. Evaluation of Adipose Tissue in Adenine-Induced CKD Mice Figure 1A showed the experimental protocol for the evaluation of adipose tissue in adenine-induced CKD mice. Regarding the validity of CKD model mice, the renal function (blood urea nitrogen: BUN, serum creatinine: SCr) and body weight are shown in Table S2. As the representative fat tissue, epididymal white adipose tissue (eWAT) was evaluated. The weight of eWAT was significantly decreased in CKD mice by comparison with the control mice (Figure 1B). H&E staining revealed that the adipocyte diameter was significantly reduced in the CKD mice (Figure 1C). F$\frac{4}{80}$ immunostaining showed macrophage infiltration in the adipose tissue of CKD mice (Figure 1D). Next, we investigated whether AOPPs were involved in the observed adipose tissue loss and macrophage infiltration by evaluating AOPP activity in eWAT. A significant increase in AOPP activity was observed in the eWAT of CKD mice compared to the control mice (Figure 1E). These data suggested that AOPPs may be involved in the observed fat atrophy and macrophage infiltration in CKD. ## 2.2. Molecular Mechanisms of ROS Production and Macrophage Infiltration by AOPPs To determine the relationship between AOPPs and ROS production or macrophage infiltration, differentiated 3T3-L1 adipocytes were used in the study. Firstly, we evaluated the effect of AOPPs on ROS production. AOPPs significantly increased ROS production in adipocytes at a concentration of 100 μM AOPPs as observed in the serum of CKD patients (Figure 2A). In contrast, no significant increase in ROS was observed after treatment with HSA at the same protein level as that of AOPPs. Next, the mechanism of AOPP-induced ROS production was examined. NADPH oxidase and mitochondria are known to be the major sources of ROS production in adipocytes [22]. Therefore, we focused on NADPH oxidase and mitochondria using pharmacological inhibitors. AOPP-induced intracellular ROS was significantly suppressed by co-treatment with N-acetylcysteine (NAC), an antioxidant, diphenyleneiodonium chloride (DPI), an inhibitor of NADPH oxidase, and MitoTEMPO, a scavenger of mitochondria-derived ROS (Figure 2A). This observation suggests that AOPPs increase the level of ROS via NADPH oxidase and the mitochondria in adipocytes. It has been reported that the increase in ROS and monocyte chemotaxis factor (MCP-1) expression is involved in adipocyte inflammation [23]. Therefore, we evaluated the effect of AOPPs on MCP-1 expression. Our results showed that MCP-1 expression was significantly increased after treatment with 100 μM AOPPs (Figure 2B). Moreover, increased MCP-1 expression was suppressed by co-treatment with NAC (Figure 2B). These data indicate that AOPPs induce MCP-1 expression through ROS production in adipocytes. Next, we evaluated whether AOPPs promote the migration of macrophages into adipocytes using a co-culture system in a Transwell®. AOPPs were added to differentiated 3T3-L1 cells in the lower layer, and 48 h later, Transwell® inserts seeded with a mouse macrophage cell line (RAW264.7 cells) were introduced and co-cultured for a further 12 h (Figure 2C). MCP-1 protein level in the lower culture medium was evaluated. The results showed that MCP-1 protein expression in the lower culture medium was significantly increased by treatment with AOPPs (Figure 2D). Macrophages migrating to the lower membrane were subsequently immunostained with anti-F$\frac{4}{80}$ antibody. A significant increase in the F$\frac{4}{80}$ fluorescence intensity was observed after incubation with AOPPs by comparison with the control culture or culture that underwent HSA treatment (Figure 2E). These results suggested that AOPPs enhance macrophage migration into adipose tissue by stimulating adipocytes to release MCP-1. ## 2.3. Molecular Mechanisms of AOPP-Induced Adipose Inflammation To evaluate the adipose inflammatory state, the effects of AOPPs on inflammatory cytokine (TNF-α and IL-6) expression in differentiated 3T3-L1 cells were examined. No significant differences in TNF-α and IL-6 expression were observed at 12 and 24 h after HSA and AOPP treatment compared to the control (Figure 3A,B). Given that adipose tissue–macrophage interactions have been reported to contribute to adipose inflammation, we focused on the effect of AOPPs on adipose tissue–macrophage interactions. Firstly, we evaluated the effect of AOPPs on macrophage polarity. Specifically, AOPPs were added to RAW264.7, and then the expression of iNOS was evaluated using an M1 macrophage (pro-inflammatory) marker, with CD206 evaluated using an M2 macrophage (anti-inflammatory) marker. The results showed that iNOS mRNA expression was significantly increased after AOPP treatment compared to control cells or cells that underwent HSA-treatment (Figure 3C). By contrast, however, CD206 mRNA expression was significantly decreased in cells treated with AOPPs (Figure 3D). Treatment with AOPPs also significantly increased TNF-α mRNA expression in RAW264.7 cells and TNF-α protein expression in the culture medium (Figure 3E,F). These results indicate that AOPPs directly affect macrophages. Moreover, incubation with AOPPs enhances TNF-α production by inducing a polarity shift toward inflammatory M1-type macrophages. Secondly, we investigated whether AOPPs induce adipose inflammation via macrophages. Here, AOPPs were added to RAW264.7 cells, and 12 h later, the conditioned medium (CM) was added to differentiated 3T3-L1 cells. After a further 12 h, the expression of inflammatory cytokines (TNF-α, IL-6) in adipocytes at the mRNA level was evaluated (Figure 3G). The results showed that AOPP-treated CM increased TNF-α and IL-6 expression in differentiated 3T3-L1 cells compared to the control CM or HSA-treated CM groups (Figure 3H,I). Furthermore, TNF-α mRNA expression in adipocytes was up-regulated by the presence of TNF-α (Figure 3H). By contrast, no significant increase in IL-6 mRNA expression was observed in the TNF-α-treated group. These results suggested that AOPPs contributed to adipose inflammation via adipose tissue–macrophage interactions. ## 2.4. Effects of AOPP Overload on Mouse Adipose Tissue To verify the above results in vivo, we evaluated adipose tissue of AOPP-overloaded mice. Here, 4-week-old healthy ICR mice were intraperitoneally injected with AOPPs on a daily basis (150 mg protein/kg/day) for 7 weeks (AOPP-overloaded mice). The comparison group comprised PBS-treated mice (control) or HSA-treated mice with the same protein concentration as that of AOPPs (150 mg protein/kg/day) (Figure 4A). Plasma biochemical parameters for renal function (BUN and SCr) at 7 weeks after AOPP loading were not significantly different from those of the control and HSA-treated groups (Table S3). Although AOPP overload did not alter body weight, epididymal fat mass tended to decrease (Figure 4B). Moreover, AOPP activity in adipose tissue was significantly increased in the AOPP-overloaded group compared to the control or HSA-treated groups (Figure 4C). The effect of AOPP overload on adipose tissue inflammation was also evaluated. MCP-1 mRNA expression was significantly elevated in the eWAT of AOPP-overloaded mice (Figure 4D). Indeed, mRNA expression levels of TNF-α and IL-6 were also significantly elevated in the eWAT of AOPP-overloaded mice (Figure 4E,F). These results indicate that AOPPs induced adipose tissue inflammation in vivo. ## 3. Discussion In this study, we found that AOPPs induced MCP-1 expression in adipocytes through the production of NADPH-oxidase-derived and mitochondria-derived ROS. Moreover, AOPPs were also found to induce the migration of macrophages to adipocytes. AOPPs also up-regulated TNF-α expression by polarizing macrophages to an M1-type polarity, leading to macrophage-mediated adipose inflammation (Figure 5). A previous report demonstrated that uremia resulted in macrophage-mediated adipose inflammation [24]. However, to date, which uremic toxins increase macrophage-mediated adipose inflammation has not been clarified. The results from this study suggest that the uremic toxin AOPPs contribute to macrophage-mediated adipose inflammation. Based on experiments using co-cultured adipocytes and macrophages, we found that AOPPs up-regulated MCP-1 expression in adipocytes and this was involved in macrophage migration (Figure 2D,E). We also showed that AOPPs induced adipocyte inflammation via macrophages in a series of experiments using a culture medium (CM) of macrophages (Figure 3H,I). Indeed, AOPPs were found to act on macrophages to induce M1-type polarity changes and enhance the release of TNF-α (Figure 3C–F). The addition of TNF-α to adipocytes also increased TNF-α mRNA expression in adipocytes (Figure 3H). It was previously demonstrated that increased MCP-1 is involved in obesity-related adipose tissue inflammation by acting on macrophage migration and inducing the local proliferation of macrophages [25], which contribute to metabolic abnormalities such as persistent adipose inflammation and insulin resistance [26]. Suganami et al. also reported that TNF-α is a major macrophage-derived paracrine mediator involved in adipose tissue inflammation [27]. During obesity, adipose tissue macrophages polarize to M1-type macrophages, which then release inflammatory cytokines such as TNF-α [28].The infiltrating macrophages interact with adipocytes in a paracrine fashion to further increase the secretion of proinflammatory cytokines [12].This crosstalk between adipocytes and macrophages causes a vicious cycle in obese adipose tissue [29].Taking these previous reports and the present study into consideration, increased AOPPs in CKD could contribute to macrophage migration to adipocytes and its changing polarization then induces adipose tissue inflammation. Recently, Liao et al. reported that AOPPs induced autophagy impairment in macrophages by suppressing the nuclear translocation of transcription factor EB (TFEB) through the activation of the PI3K-AKT-mTOR pathway [30]. Autophagy impairment in macrophages has been shown to induce M1 polarization [31,32]. These findings suggest that the induction of M1-type macrophages by AOPPs may involve autophagy impairment. Previously, AOPPs were reported to promote ROS production in adipocytes via the activation of NADPH oxidase [33]. Mitochondria as well as NADPH oxidase are known to be intracellular sources of ROS production related to adipose inflammation [34]. However, the effect of AOPPs on mitochondria-derived ROS in adipocytes has not been determined. In this study, we found that in addition to the involvement of NADPH oxidase, mitochondria-derived ROS also contributed to AOPP-induced ROS production (Figure 2A). Mitochondria-derived ROS in adipocytes enhance lipolysis by inducing excessive mitophagy via the NF-κB pathway and increasing inflammatory cytokine expression. Elevated free fatty acids in the blood contribute to hepatic insulin resistance and the progression of type 2 diabetes mellitus [35]. Therefore, AOPPs may also affect systemic metabolic abnormalities during CKD via increased ROS production in adipocytes. For the cellular uptake of AOPPs, the involvement of CD36 and the receptor for advanced glycation end products (RAGE) have been suggested. Specifically, in renal tubular cells, AOPPs are taken up by CD36, and then mitochondria-derived ROS are released via PKC signaling activation [36]. In chondrocytes, AOPPs induced chondrocyte apoptosis by increasing NADPH-oxidase-derived ROS production after being taken up via RAGE [37]. Adipocytes also express CD36 and RAGE. Kuniyasu et al. reported that oxidized LDL promoted ROS production after being taken up via CD36 in adipocytes, resulting in enhanced PAI-1 expression [38]. Feng et al. reported that RAGE deficiency suppressed MCP-1 expression and macrophage infiltration in adipocytes in a high-fat-diet (HFD)-induced obesity model, indicating that RAGE-mediated signaling might be involved in adipose inflammation and the development of insulin resistance during obesity [39]. Based on these previous findings, it is suggested that CD36 and RAGE could be involved in the uptake of AOPPs into adipocytes. Further investigation is required to verify the involvement of CD36 and RAGE on AOPP-induced adipose inflammation. To this end, experiments using neutralizing antibodies and siRNA will be conducted. In the present study, AOPPs did not affect the expression of inflammatory cytokines in adipocytes without macrophages (Figure 3A,B). However, Qin Gen Zhou et al. reported that AOPPs induce inflammatory cytokine expression via the NF-κB pathway in adipocytes [36]. These conflicting results may be due to either differences in the albumin (mouse- or human-derived albumin) used in the experiments, or the different oxidants (hypochlorous acid or chloramine-T) employed in AOPP preparation. As a consequence, the properties of the resulting AOPPs may differ between the two studies. ## 4. Conclusions Here, we show that AOPPs induced oxidative stress and inflammation in adipose tissue via interaction with adipocytes and macrophages. As such, AOPPs represent a promising new therapeutic target for fat atrophy associated with CKD. ## 5.1. Chemicals and Materials Human serum albumin (HSA) was purchased from the Japan Blood Products Organization (Tokyo, Japan). Diphenylene iodonium (DPI), MitoTEMPO, insulin, dexamethasone and isobutylmethylxanthine were purchased from Sigma-Aldrich (St Louis, MO, USA). Anti-F$\frac{4}{80}$ monoclonal antibody was purchased from eBioscience (San Diego, CA, USA). Potassium iodide, chloramine T, acetic acid and N-acetyl-L-cysteine (NAC) were purchased from Nacalai Tesque (Kyoto, Japan). 5-(and 6)-chloromethyl-2′,7′-dicholorodihydrofluorescein diacetate (CM-H2DCFDA) and Dulbecco’s phosphate-buffered saline (D-PBS) were purchased from Invitrogen (Grand Island, NY, USA). Dulbecco’s modified eagle medium (DMEM)-high glucose and DMEM-low glucose were purchased from FUJIFILM Wako Pure Chemical Co. (Osaka, Japan). All methods were carried out in accordance with approved guidelines. All experimental protocols were approved by Kumamoto University. ## 5.2. Cell Cultures Mouse 3T3-L1 fibroblasts were maintained in DMEM-low glucose containing $10\%$ bovine calf serum (GE Healthcare, UK Ltd., Amersham, UK) and supplemented with $1\%$ penicillin/streptomycin. The differentiation of mouse 3T3-L1 fibroblasts to mature adipocytes was performed by exposing post-confluent cells for 2 days to an induction medium. The induction medium consisted of DMEM-high glucose containing $10\%$ FBS (Capricorn Scientific, Ebsdorfergrund, Germany), $1\%$ penicillin/streptomycin, 10 µg/mL insulin, 2.5 µM dexamethasone and 0.5 mM isobutylmethylxanthine. After 2 days, the medium was changed to a maturation medium. The maturation medium consisted of DMEM-high glucose containing $10\%$ FBS, $1\%$ penicillin/streptomycin and 10 µg/mL insulin. The mature medium was exchanged every other day until day 12. Cells were serum-starved for 12 h prior to starting the experiment. RAW264.7 cells were obtained from the RIKEN BRC Cell Bank (Ibaraki, Japan), and were grown in DMEM-high glucose containing $10\%$ FBS and $1\%$ penicillin/streptomycin. ## 5.3. Assay Procedure for AOPPs The protocol used to determine the level of AOPPs was described in a previous report [16]. In brief, a 200 μL aliquot of the sample was diluted 10-fold in 67 mM phosphate buffer (pH 7.4) and added to a 96-well plate. To each well was added 25 μL of $20\%$ acetic acid and 10 μL of 1.16 M potassium iodide. A standard curve was prepared using chloramine T solution. Absorbance readings at 340 nm were measured immediately after the solution addition using a microplate reader. ## 5.4. Preparation of AOPPs AOPPs were prepared as described in a previous study [40]. HSA was defatted via treatment with activated carbon. Defatted HSA (300 μM) was incubated with 100 mM chloramine T in 67 mM phosphate buffer (pH 8.0) for 1 h at 37 °C. The oxidation reaction was stopped by dialysis with phosphate-buffered saline (PBS). After dialysis, samples were freeze-dried to prepare AOPPs (194.4 μmol/g protein). ## 5.5. Animal Experiments All animals were purchased from Japan SLC (Shizuoka, Japan). Animals were housed in a temperature controlled room (21–23 °C) with a 12 h light/dark cycle (light 8 am to 8 pm) and given ad libitum access to food and water. All animal experiments were conducted using procedures approved by the experimental animal ethics committee at Kumamoto University (approval number A2021-021). Adenine-induced renal failure mice (CKD mice) were established using a protocol described in a previous report [41]. C57BL/6NCrSlc mice (male, 6 weeks) were fed CE-2 (normal diet) for 1 week for pre-rearing, and then switched to an adenine powder mixed diet (normal diet supplemented with $0.2\%$ adenine) for 4 weeks. The mice were then switched to CE-2 to rule out any direct adipose tissue effects of adenine, and evaluated after 4 weeks of feeding. For AOPP-overloaded mice, AOPPs were administered intraperitoneally on a daily basis to 4-week-old male ICR mice for 7 weeks. As a control, PBS or defatted HSA (150 mg protein/kg/day: the same amount of protein as AOPPs) was also administered to male ICR mice (4-week-old) for 7 weeks. ## 5.6. ROS Measurements 3T3-L1 cells were seeded on 96-well plates at 1.0 × 104 cells per well and differentiated into mature adipocytes. After cell differentiation, the cells were washed with PBS and starved with serum-free medium for 12 h before being treated with CM-H2DCFDA for 30 min in D-PBS. After removing the supernatant, cells were incubated with AOPPs, HSA or D-PBS (control) for 1 h. Fluorescence intensity was then measured using a fluorescence plate reader (Synergy H1, Agilent BioTek, Santa Clara, CA, USA) with an excitation and emission of 485 nm and 535 nm, respectively. In the study using inhibitors, cells were incubated with CM-H2DCFDA for 30 min, and then the supernatant was replaced with D-PBS. After the addition of the various inhibitors and incubation for 30 min, AOPPs, HSA or D-PBS was added in the presence of each inhibitor. Fluorescence intensity was then measured as described earlier. ## 5.7. Quantitative RT-PCR Total RNA was isolated from differentiated 3T3-L1 cells, RAW264.7 cells or adipose tissue using RNAiso Plus (Takara, Tokyo, Japan). The concentration and purity of the extracted RNA was determined from absorbance readings at 260 and 280 nm. A master mix was used to prepare the cDNA from the extracted RNA. Quantitative RT-PCR measurements were then performed. Sequences of the primers used for mRNA detection are given in the supporting information (Table S1). The threshold cycle (Ct) values for each gene amplification were normalized by subtracting the Ct value calculated for GAPDH. ## 5.8. Histological Analysis Adipose tissues were harvested from the mice and fixed for 48 h with $10\%$ neutral buffered formalin solution at 4 °C. Each tissue sample was processed via paraffin infiltration using a fully automated sealed tissue processor (ASP300S, Leica) and then embedded with paraffin. Sections were cut at a thickness of 5-μm and mounted on glass slides. For the measurement of adipocyte size, sections were stained with hematoxylin and eosin. Quantification was performed from 5 fields of image per sample. Adipocyte size was calculated from the long diameter obtained via microscopy (BZ-X710 microscope; Keyence, Osaka, Japan). For F$\frac{4}{80}$ staining, the deparaffinized sections were antigen-activated with Histo VT One (Nacalai Tesque) and incubated with anti-F$\frac{4}{80}$ antibody (1:50) overnight at 4 °C. The sections were then reacted with peroxidase-conjugated anti-rat IgG antibody (Histofine Simple Stain MAX-PO; Nichirei Biosciences, Tokyo, Japan) at room temperature for 30 min, followed by reaction with DAB solution at room temperature for 1.5 min. After counterstaining with hematoxylin, the sections were dehydrated and permanently mounted. Crown-like structures (CLS) were counted with a microscope at a ×20 magnification from 6 images per sample, as described previously [42]. All images were randomly acquired using a BZ-X710 microscope. ## 5.9. Transwell® Assays Transwell assays were used to detect macrophage migration. 3T3-L1 cells were seeded on 12-well Transwell® plates at 2.0 × 105 cells per well and differentiated into mature adipocytes. After cell differentiation, AOPPs (100 μM) or HSA (protein concentration equivalent to 100 μM of AOPPs) were added to differentiated 3T3-L1 cells, and 48 h later, Transwell® inserts (3-μm pore size) seeded with RAW264.7 (1.0 × 104 cells per well) were inserted and co-cultured for 12 h. Macrophages migrating to the lower layer of the semipermeable membrane of the Transwell® inserts were evaluated via fluorescent immunostaining with anti-F$\frac{4}{80}$ antibody. The semipermeable membrane was washed once with PBS and cells present in the upper layer of the semipermeable membrane were removed. After cutting the semipermeable membrane along the edges, the cells were fixed by incubating them in $4\%$ paraformaldehyde for 20 min at room temperature. Cells were washed once with PBS, blocked for 1 h at room temperature, and then incubated with rat anti-F$\frac{4}{80}$ antibody (1:50) overnight at 4 °C. After washing three times with PBS, a secondary antibody reaction was performed with Alexa Fluor647 anti-rat IgG antibody at room temperature for 1 h. The cells were washed three times with PBS and treated with vectashield antifade mounting medium prior to observation under a fluorescence microscope (BZX-710). F$\frac{4}{80}$ positive areas were quantitated from 5 fields of view randomly selected from each slide. Analysis was performed using a BZ-X Analyzer. ## 5.10. Preparation of RAW264.7-Conditioned Medium (CM) RAW264.7 cells were cultured in DMEM-high glucose containing $10\%$ FBS and $1\%$ penicillin/streptomycin. 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--- title: Oxygen-Releasing Hyaluronic Acid-Based Dispersion with Controlled Oxygen Delivery for Enhanced Periodontal Tissue Engineering authors: - Lena Katharina Müller-Heupt - Nadine Wiesmann-Imilowski - Sofia Schröder - Jonathan Groß - Pablo Cores Ziskoven - Philipp Bani - Peer Wolfgang Kämmerer - Eik Schiegnitz - Anja Eckelt - John Eckelt - Ulrike Ritz - Till Opatz - Bilal Al-Nawas - Christopher V. Synatschke - James Deschner journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10059003 doi: 10.3390/ijms24065936 license: CC BY 4.0 --- # Oxygen-Releasing Hyaluronic Acid-Based Dispersion with Controlled Oxygen Delivery for Enhanced Periodontal Tissue Engineering ## Abstract Periodontitis is a chronic biofilm-associated inflammatory disease of the tooth-supporting tissues that causes tooth loss. It is strongly associated with anaerobic bacterial colonization and represents a substantial global health burden. Due to a local hypoxic environment, tissue regeneration is impaired. Oxygen therapy has shown promising results as a potential treatment of periodontitis, but so far, local oxygen delivery remains a key technical challenge. An oxygen (O2)-releasing hyaluronic acid (HA)-based dispersion with a controlled oxygen delivery was developed. Cell viability of primary human fibroblasts, osteoblasts, and HUVECs was demonstrated, and biocompatibility was tested using a chorioallantoic membrane assay (CAM assay). Suppression of anaerobic growth of Porphyromonas gingivalis was shown using the broth microdilution assay. In vitro assays showed that the O2-releasing HA was not cytotoxic towards human primary fibroblasts, osteoblasts, and HUVECs. In vivo, angiogenesis was enhanced in a CAM assay, although not to a statistically significant degree. Growth of P. gingivalis was inhibited by CaO2 concentrations higher than 256 mg/L. Taken together, the results of this study demonstrate the biocompatibility and selective antimicrobial activity against P. gingivalis for the developed O2-releasing HA-based dispersion and the potential of O2-releasing biomaterials for periodontal tissue regeneration. ## 1. Introduction Periodontitis, a biofilm-associated inflammatory disease of the periodontal tissues [1,2], is one of the most prevalent global diseases. Indirect costs related to periodontitis in the United States and Europe were estimated to exceed EUR 300 billion in 2018 [3]. Periodontitis is strongly associated with anaerobic bacterial colonization and represents a substantial global health burden due to its epidemiologic associations with other chronic inflammation-driven diseases such as cardiovascular disorders and diabetes [4,5]. Although periodontitis can be successfully treated, restoration of the original form, structure, and function of the periodontal tissues lost due to the disease, i.e., periodontal regeneration, is possible only in certain cases. In addition, the results after periodontal regenerative therapy are only partially predictable. This shows that the treatment of periodontitis is still a challenge. Due to the chronic inflammation, the vasculature in the periodontal tissues is severely impaired by periodontitis, resulting in a hypoxic microenvironment [6]. On the other hand, the hypoxic milieu within periodontal pockets seems to play a critical role in the disruption of the host–immune hemostasis, periodontal tissue remodeling, and inflammation of periodontal tissues [7,8,9], and is furthermore coupled with overgrowth of anaerobic subgingival microorganisms [10]. At sites where a chronic inflammatory response could be detected, oxygen consumption is increased, and blood flow is stimulated. This change in the partial pressure of oxygen (pO2) in the affected tissue is due in part to increased oxygen (O2) consumption, including oxygen consumption by resident cells and infiltrated defence cells, and in part to decreased oxygen availability due to endothelial damage and vasoconstrictive microcirculation, as well as facultative anaerobic bacteria. Local hypoxia in periodontitis, in turn, favors the survival of anaerobic Gram-negative pathogens and further lowers the oxygen partial pressure in the environment. Tissue hypoxia in periodontal disease is characterized by an increase in hypoxia-inducible factor 1-alpha (HIF-1α) protein levels, which is detectable in tissue biopsies affected by periodontitis. A hypoxic environment can upregulate the expression of proinflammatory cytokines and matrix metalloproteinases (MMPs) by host cells during periodontal disease [11]. To positively influence the dysbiotic oral microbiota, there are various approaches such as probiotics, parabiotics, and postbiotics as an adjunct to nonsurgical periodontal therapy treatment provided as toothpastes or lozenges, which seem to be beneficial to suppress specific periodontopathogens [12,13,14,15,16]. Another therapeutic strategy involves the use of oxygen. The oxygen content in healthy periodontal tissue ranges from $2.9\%$ to $5.7\%$ [17], but many causes can lead to local hypoxia of the microenvironment in periodontal tissues, such as severe periodontitis [7]. The oxygen content in periodontal tissues with a mean pocket depth of 6.9 mm is $1.8\%$ [18]. Oxygen is involved in various biological processes such as cell metabolism and signal transduction. In particular, in the wound healing process, the transient oxidative stress induced by oxygen is beneficial for increasing cellular activities, secretion of growth factors, and promotion of neovascularization. Periodontal ligament stem cells (PDLSCs) possess multipotent, highly proliferative, and self-renewing capacities. Furthermore, they exhibit the ability to differentiate into cementoblasts or osteoblasts [19]. The periodontal ligament (PDL), a connective tissue between bone and teeth, composed of multiple cells, such as fibroblasts, PDLSCs, and osteoblasts, provides an oxygen-enriched ecologic microenvironment crucial for healthy periodontal tissues and normal cell functions [20]. Thus, the regeneration of the PDL is a crucial factor for the regeneration of the other periodontal structures also damaged by periodontitis. [ 21,22,23]. However, it has been shown that the growth rate of PDL fibroblasts in in vitro studies decreases with the reduction of oxygen levels. Moreover, PDL fibroblasts were found to migrate significantly faster—at $21\%$ and $5\%$, rather than at $1\%$ O2 [17]; in addition, a reduction of pO2 from $20\%$ to $2\%$ decreased the formation of bone nodules, while it almost disappeared at $0.2\%$ pO2 [24]. For the abovementioned reasons—in addition to its ability to inhibit the growth of anaerobic bacteria—hyperbaric oxygen therapy (HBOT) has been tested as adjuvant treatment of subgingival instrumentation for periodontitis, with promising results regarding the reduction of anaerobic bacteria and periodontal parameters [25,26,27]. Nevertheless, HBOT is a time-consuming and expensive procedure. Therefore, topical oxygen therapies may be an interesting therapeutic option to use in dental practice. For the development of a local O2-releasing therapeutic agent for periodontal tissues, the use of a hyaluronic acid (HA)-based biopolymer matrix appeared to be particularly interesting in the case of periodontal adjuvant treatment, since HA is biocompatible, biodegradable, and has wound-healing properties. HA is a biological molecule found in different tissues of the human body. It occurs naturally in the gingiva, periodontal ligaments, dental cementum, and alveolar bone, and unstimulated saliva concentrations range from 148 to 1270 ng/mg [26,27]. Furthermore, HA is an important component of the extracellular matrix and plays an important role in cell migration and proliferation, contributing to wound healing and tissue regeneration [28]. The concentration of hyaluronic acid is tissue-dependent, and its properties are determined by its molecular weight. In general, high molecular weight (MW) HA (MW > 106 Da) has immunosuppressive and antiangiogenic properties, intermediate size HA (MW from 2 × 104 to 106 Da) positively influences wound healing and regeneration, and small HA molecules (MW from 6 × 103 Da to 2 × 104 Da) contribute to proinflammatory and angiogenic processes. HA is one of the local substances used in the past decade as an adjuvant to nonsurgical periodontal treatment, and most of the HA-based gels used in periodontal therapy contain high-MW HA [27]. It has been reported that high MW HA products do not prolong inflammatory processes, impair the healing process, or induce excessive metalloproteinase (MMP) expression at the repair site in gingival tissue [27]. Other studies found that high MW hyaluronic acid increased the proliferation of human periodontal ligament (PDL) cells and maintained their high viability [29]. Clinical studies in patients with periodontitis have shown a decrease in the proliferation index of gingival epithelium (expression of the Ki-67 antigen) and of the inflammatory process, and improved periodontal lesions [28], bleeding on probing [29,30], the sulcus fluid flow rate [31], plaque index, pocket probing depth [32,33], and clinical attachment level [30,33,34]. Oxygen-releasing biomaterials have been developed with a primary focus on application in tissue engineering, i.e., in large 3D tissue constructs, to overcome insufficient oxygen supply due to a lack of vascularization [35,36,37,38]. Typically, inorganic compounds, such as percarbonates and peroxides, provide a source for oxygen through a chemical decomposition reaction, but fluorinated compounds that can dissolve molecular oxygen have also been reported. Various polymers such as polycaprolactone [39], poly(lactic-co-glycolic acid) [40], and polydimethylsiloxane were used to encapsulate oxygen-producing materials, where their hydrophobic nature improves long-term release of oxygen, necessary for tissue regeneration. There are very few examples of oxygen-releasing materials outside of tissue engineering applications. To the best of our knowledge, there have been no previous reports on the use of such materials to control the growth of anaerobic bacteria. For the abovementioned reasons, the goal of our research was to develop a biocompatible and biodegradable O2-releasing HA-based dispersion suitable for topical periodontitis therapy. To avoid excessive and rapid oxygen generation (burst release), which may lead to oxidative stress and the production of reactive oxygen species (ROS—key signaling molecules for the progression of tissue inflammation and endothelial dysfunction) [41], we aimed to develop a biomaterial with slow and sustained oxygen release. ## 2.1. Oxygen Release Kinetics of the O2-Releasing HA-Based Dispersion We prepared an oxygen-releasing HA material by first dispersing CaO2 particles in MilliQ water and slowly adding high MW HA (MW = 1.5–2.5 MDa) under continuous stirring to form a viscous slurry. The ratio between HA and CaO2 was optimized to produce a macroscopically homogeneous mixture. The oxygen-release behavior was then evaluated. Delayed oxygen release and an increased amount of available oxygen, as indicated by a larger area under the curve (AUC), was observed when CaO2 was enclosed in an HA matrix at different pH levels (Table 1, Figure 1A–C). The greatest AUC, of 98.52, was observed for CaO2 and HA in H2O at pH 6 (Table 1). The oxygen release was increased as compared to the release of oxygen from CaO2 in H2O only. This increase was observed at all pH levels (2, 6, and 8), which is important for the therapeutic use of the dispersion because the pH can vary at different periodontal pocket sites due to inflammation and bacterial metabolites. The release was particularly enhanced at pH 6. Furthermore, the O2 release time was increased up to 3.6-fold when CaO2 was enclosed in an HA matrix (Figure 1B) compared to free CaO2 in solution, which showed a much more rapid burst release when used as single substance without an HA matrix. ## 2.2. Detection of Calcium Peroxide Particles in HA-CaO2 Dispersions To confirm the presence of CaO2 particles in the HA-based dispersion, scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDX) were performed on dried samples of the material (Figure 2). Particles with a diverse size range (appr. 4–30 µm) could be observed. EDX spectra (Figure 2C) confirmed the presence of calcium ions in these particles but not in the surrounding matrix, indicating that the CaO2 particles were dispersed in the polymer, but did not fully dissolve. ## 2.3. FTIR of the O2-Releasing HA-Based Dispersion Next, the stability of the HA-based dispersion was investigated by FTIR spectroscopy. When HA is oxidized by strong oxidizing agents (e.g., NaIO4), a C–C bond in a glucose unit breaks, and two aldehyde groups are formed. The presence of the latter can be qualitatively proven by a characteristic vibrational excitation band at 1735 cm−1 in the IR spectrum. To prove that HA is stable towards oxidation in the dispersion, a freshly prepared sample was compared with a two-month-old sample as well as a seven-month-old sample (each stored at ambient temperature in the absence of light). None of the samples exhibited this characteristic vibration band (Supplementary Materials, Figure S1), indicating that the HA is not degraded during storage. ## 2.4. Biocompatibility of the O2-Releasing HA-Based Dispersion Since the main goal of our study was to develop a dispersion suitable for the treatment of periodontitis, the biocompatibility of the O2-releasing dispersion is a key challenge due to the highly reactive nature of CaO2. Therefore, we investigated the effect of the O2-releasing HA-based dispersion on the cellular viability of human primary fibroblasts obtained from human oral mucosa, human primary osteoblasts, and human primary umbilical vein endothelial cells (HUVECs), since biomaterials incorporating CaO2 may negatively affect cell viability. All cells are crucial for periodontal regeneration. In this context, all cells were treated with HA, CaO2, or a combination of CaO2 and HA to examine their cytotoxicity. In accordance with ISO 10993-5, cell viability under $70\%$ was regarded as cytotoxicity. Neither HA alone nor in combination with CaO2 was cytotoxic to human primary fibroblasts obtained from different patients (Figure 3A). In contrast, fibroblasts treated with 0.256 mg/mL CaO2 showed a reduction in cell viability by more than $30\%$, indicating the cytotoxicity of CaO2 as single substance. Furthermore, none of the substances were cytotoxic for endothelial cells at the tested concentrations, but HA slightly decreased their cell viability (Figure 3B). Finally, none of the substances were cytotoxic for osteoblasts; however, both CaO2 and the combination of CaO2 and HA slightly decreased cell viability (Figure 3C) compared to HA alone. In contrast, the addition of HA as a single substance increased cell viability compared to the control group. Furthermore, biocompatibility and capacity to induce angiogenesis of the O2-releasing material were investigated using a chorioallantoic membrane assay (CAM assay). The vascularized tissue surface area, measurable as vascularized surface of the sponge, increased using HA, CaO2, or a combination thereof compared to untreated CAM tissue (Figure 4A). Nevertheless, the results were not significant due to high standard deviations. Furthermore, none of the tested substances had a cytotoxic effect on the CAM. The degradation of the sponge to which the different substances were applied did not differ from that of an empty sponge, and no adverse tissue reactions to the substances were observed on the CAM (Figure 4B). ## 2.5. Broth Microdilution Assay The minimum inhibitory concentration (MIC) for P. gingivalis was determined using the broth microdilution assay. The MIC for CaO2 dispersions amounted to 256 mg/L. ## 3. Discussion The aim of this study was to develop a biocompatible and resorbable O2-releasing biomaterial for the therapy of periodontitis, which results in tissue hypoxia and consecutively impaired tissue regeneration due to chronic low oxygen supply. In brief, our study revealed that a novel combination of CaO2 enclosed into an HA matrix released more oxygen, as indicated by a larger area under the curve, with a sustained release rate, compared to pure CaO2, which showed a rapid and high oxygen burst. Materials with similar properties, but used for purposes other than periodontal therapy, have been described in the literature [35]. In general, similar materials are targeted for use in tissue regeneration, especially in large-tissue models that are vascularly undersupplied and therefore hypoxic. This typically requires a low-threshold release of oxygen, ideally lasting for weeks to months. Approaches used so far to achieve a long-lasting oxygen release are the incorporation of inorganic peroxides such as CaO2 into mostly hydrophobic polymers such as polycaprolactone [42], poly(lactide-co-glycolide) [43], human keratin, silk, or gelatin [44]. To enable tissue growth on these materials, the polymers are spun, for example, into nanofibers, which provide a large surface area. While such hydrophobic polymers are well suited for growing cells in culture media, it is often difficult to adapt the materials to complex and small-defect structures, such as those found in periodontal pockets, because the materials are usually not injectable and are difficult to deform. HA can be oxidatively degraded by adding sodium metaperiodate [45]. Oxidized HA has been reported to contain multiple aldehyde groups, resulting in the formation of dispersions for tissue engineering. However, as confirmed by FTIR spectroscopy, the incorporation of CaO2 into the HA matrix did not cause oxidative cleavage of the HA. Our study, furthermore, revealed that the novel O2-releasing HA-based dispersion is not cytotoxic and shows good biocompatibility. Peroxides in high concentrations, such as $35\%$ hydrogen peroxide (H2O2), are known to cause oxidative stress and promote gingival tissue inflammation and damage in vivo [46]. In vitro, H2O2 was reported to induce senescence in different cell lines [47]. H2O2 exerted oxidative injury to primary human osteoblasts [48] and has been reported to induce senescence due to an increase of ROS in HUVECs [49] and in fibroblasts [47]. Nevertheless, the oxidative injury depends on the concentration of H2O2 and other peroxides seem to be more biocompatible, such as CaO2 [43]. To ensure biocompatibility of our biomaterial enclosing CaO2, cell viability was tested with different cell lines present in the periodontal pocket. At a concentration of 256 mg/L—a concentration creating a sufficient amount of oxygen in the dispersion—no cytotoxicity was observed against fibroblasts, osteoblasts or HUVECs. Regarding fibroblasts and HUVECs, the combination of CaO2 enclosed in HA increased the cell viability compared to HA respectively CaO2. Furthermore, a concentration of up to 512 mg/L CaO2 was shown to be biocompatible and induce angiogenesis in the CAM assay. The oxygen release not only affects periodontal tissues but also increases the amount of locally available oxygen. Thus, it impairs the ecologic niche of the periodontitis-associated anaerobic bacteria and blocks their growth [50]. Therefore, oxygen-generating biomaterials may be capable of disrupting the circulus vitiosus of chronic inflammation, resulting in a hypoxic environment coupled with the overgrowth anaerobic bacteria, resulting in more inflammation. Novel approaches that constitute an adjunct to nonsurgical periodontal therapy involve the development of selective antimicrobial agents, such as oxygen or plant extracts or probiotics, parabiotics, and postbiotics to support eubiosis [12,13,14,15,16,51]. Furthermore, host modulation is an effective adjunctive therapy and the combination of host modulation and the recovery of oral eubiosis is key to the development of targeted microbial peptides, antimicrobial peptides, and inhibitors of inflammasomes [52,53]. Taken together, the findings of this study suggest that O2-releasing dispersions are promising materials for the topical adjuvant therapy of periodontitis, such as a sustained oxygen release without any cytotoxic side effects. Further studies are needed to evaluate the tissue regenerating capacity of O2 -releasing HA. ## 4.1. Preparation of O2-Releasing HA-Based Dispersion An amount of 2.56 mg CaO2 (200 mesh, Sigma Aldrich, St. Louis, MO, USA) was weighed into a sealable vessel. Subsequently, phosphate-buffered saline (PBS) was added, and the mixture was shaken vigorously. The desired amount of HA sodium salt (HERRLAN-PSM e.K., Alpen, Germany) was added during vigorous stirring. An amount of 300 mg of sodium hyaluronate (HA15M, Lifecore Biomedical Inc., Chaska, MN, USA) was slowly added under continuous stirring. The mixture was allowed to dissolve overnight under continuous stirring. ## 4.2. Energy-Dispersive X-ray Analysis (EDX) EDX measurements were performed using a Hitachi SU 8000 microscope coupled with a Bruker XFlash 5010 detector. This combination of devices was applied at 8 kV, in order to acquire an elemental map of the deposits on the surfaces. Pt sputtering (7 nm) of the air-dried sample was used to avoid charging artifacts due to high probe currents needed for EDS. ## 4.3. Fourier-Transform Infrared Spectroscopy (FTIR) The infrared (IR) spectra of lyophilized samples were recorded by a Tensor 27 FTIR spectrometer equipped with a diamond ATR unit and are reported in terms of frequency of transmission. The data were collected in a spectral range of 4000–400 cm−1, 16 scans, and a resolution of 4 cm−1. ## 4.4. Oxygen Release Measurements An amount of 50 mg CaO2 ($75\%$ 200 mesh, Sigma Aldrich) was suspended in 5 mL deionized water (millipore grade). An amount of 115 mg of hyaluronic acid sodium salt (1.5–2.5 MDa: Herrlan-PSM e.K., Alpen, Nordrhein-Westfalen, Germany) was added under vigorous stirring. The mixture was stirred for at least 4 h and then inserted into a syringe without bubbles. The concentration profile of dissolved oxygen was determined by means of a benchtop dissolved oxygen meter HI 5421 (Hanna Instruments, Vöhringen, Germany). The sensor was placed in a thermostated beaker immediately above a magnetic stirring bar. The beaker was filled with 200 mL of 0.1 M citric acid (≥$99.5\%$: Carl Roth, Karlsruhe, Germany) in 0.9 wt% NaCl aqueous solution. The pH was adjusted by means of 1 M NaOH (Carl Roth). A cellulose filter bag was placed into the solution to enable free migration of dissolved substance and prevent the free migration of the hyaluronic acid matrix or undissolved CaO2 particles. A baseline reading was acquired in the solution in the absence of the oxygen-releasing material for 50 min. Then, 5 mL of the test solution were added into the cellulose filter bag within 30 s. The concentration profile of the dissolved oxygen was detected for several hours at baseline and with 50 mg CaO2 in 5 mL water, either with or without hyaluronic acid sodium salt. The concentration of the dissolved oxygen was normalized to the concentration of the dissolved oxygen at the time when samples were added. ## 4.5. Cell Isolation Primary human cells were obtained from patients who underwent surgery at the University Medical Center Mainz, Germany. The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of the University Medical Center of the Johannes Gutenberg University, Mainz, Germany, according to the general terms and conditions, §14 “further use of human material” of the contract of the University Medical Center Mainz. All patients provided written consent. ## 4.5.1. Fibroblasts Fibroblasts were obtained from human oral mucosa. Tissue samples were cut into small pieces of approximately 2 × 2 mm with a sterile disposable scalpel. Prior to cell isolation, the tissue pieces were stepwise sterilized in $70\%$ ethanol, in sterillium® classic pure (Bode Chemie GmbH, Hamburg, Germany), and again in $70\%$ ethanol. Then, they were transferred to 5–10 mL (depending on the amount of tissue) $0.5\%$ protease solution (P6141, Sigma-Aldrich, St. Louis, MO, USA) in phosphate-buffered saline (PBS; Sigma-Aldrich, St. Louis, MO, USA) and incubated overnight at 4 °C. The next day, the protease solution was incubated for further 15 min at 37 °C with shaking. The sample was then passed through a cell sieve (EASYstrainerTM 70 µm sterile, Greiner bio-one, Kremsmünster, Austria) with the help of a cell scraper (Falcon®, Corning Inc., Corning, NY, USA). Cells were pelleted by centrifugation (1500 rpm, 5 min), transferred to cell culture medium, and seeded into small cell culture flasks with a grow area of 25 cm2. Cells were characterized morphologically and were used at most until passage 10 to ensure primary identity. Cells were maintained in DMEM/Ham’s F12 (Gibco, ThermoFisher Scientific, Waltham, MA, USA) supplemented with $10\%$ fetal calf serum and antibiotics (10,000 U/mL penicillin and 10 mg/mL streptomycin; Sigma-Aldrich, St. Louis, MO, USA) at 37 °C in $5\%$ CO2. ## 4.5.2. Osteoblasts Primary human osteoblasts were isolated according to the following protocol. Human bone specimens were obtained during hip or knee joint replacement surgeries. Cancellous bone fragments were removed with bone rongeurs from bone specimens. The isolated fragments were washed several times with PBS (Sigma-Aldrich, St. Louis, MO, USA) until a clear supernatant was achieved. The supernatant was discarded and 15 mL collagenase type I solution (1 mg/mL in medium 199, Gibco, ThermoFisher Scientific, Waltham, MA, USA) was added. Collagenase digestion was carried out under mechanical stirring in a water bath at 37 °C. After 45 min, the fragments were washed again several times with PBS (Sigma-Aldrich, St. Louis, MO, USA). The washed bone pieces were transferred into 6-well tissue culture plates with sterile forceps, followed by addition of DMEM/F-12 medium supplemented with $20\%$ fetal calf serum (FCS) and $1\%$ penicillin/streptomycin (PS). After the first passage, human osteoblasts were cultured in DMEM/Ham’s F12 (Gibco, ThermoFisher Scientific, Waltham, MA, USA) supplemented with $10\%$ fetal calf serum and antibiotics (10,000 U/mL penicillin and 10 mg/mL streptomycin; Sigma-Aldrich, St. Louis, MO, USA). The medium was changed twice a week. For osteoblast differentiation, the medium was supplemented with 10 nM dexamethasone, 3.5 mM b-glycerophosphate, and 50 μg/mL ascorbic acid. ## 4.5.3. Primary Human Umbilical Vein Endothelial Cells (HUVEC) Primary human umbilical vein endothelial cells (HUVEC) were isolated from the vein of the umbilical cord. The umbilical cord was flushed with PBS (Sigma-Aldrich, St. Louis, MO, USA) until the buffer was clear and blood clots in the vein were removed. Then, collagenase was injected into the umbilical cord, and it was placed in PBS and incubated for 12 min at 37 °C. After incubation, the collagenase solution containing endothelial cells was flushed from the cord perfusing the vein with PBS (Sigma-Aldrich). The effluent was collected and centrifuged for 10 min at room temperature with max. 420× g. Cells were kept in culture dishes coated with 3 mL $0.1\%$ gelatine at 37 °C and supplemented with EBM (PromoCell, Heidelberg, Germany) with the addition of $10\%$ fetal calf serum (FCS; PAA, Linz, Austria). Cells were incubated overnight at 37 °C and washed with PBS (Sigma-Aldrich, St. Louis, MO, USA) the next day. Endopan 3 with $3\%$ fetal blood serum (PAN Biotech, Aidenbach, Germany) was used as culture cell medium. ## 4.6. Cellular Viability Assays To investigate the cytocompatibility of the O2-releasing HA-based dispersions, the substances were added to human primary fibroblasts, osteoblasts, and human umbilical vein endothelial cells (HUVEC) in vitro and compared to untreated cells and a dead control. For this purpose, cytotoxicity tests were performed according to ISO 10993-5 by measuring the cell viability quantitatively and calorimetrically. In all tests, 30 mg/mL sodium hyaluronate and 0.256 mg/mL CaO2 were used. According to ISO 10993-5, cytotoxicity is defined by more than $30\%$ reduction of the viable cells by the substance. Cells were seeded into a 24-well plate and allowed time to adhere overnight. The cell number per well was 50,000 for fibroblasts and HUVECs and 40,000 for osteoblasts with 1.5 mL medium per well. After 24 h, cell culture medium was replaced by 400 µL fresh medium. Cells were treated with 0.256 mg/mL CaO2 (Sigma Aldrich, St. Louis, MO, USA), 30 mg/mL hyaluronic acid (Herrlan-PSM e.K., Alpen, Nordrhein-Westfalen, Germany), or a combination thereof. Untreated cells served as control. The substances were applied into inserts with a 10 μm-thick translucent polycarbonate membrane (Corning Inc., New York, NY, USA) with 0.4 μm pores. Those inserts then were inserted in the 24-well plate and were thus in direct contact with the cell culture medium of the cells and incubated overnight. The inserts were removed after 24 h, the cell culture medium was exchanged for 1 mL of medium with $10\%$ AlamarBlue™ Cell Viability Reagent (ThermoFisher Scientific, Waltham, MA, USA) and the cells were incubated for 4 h at 37 °C. After 4 h, the liquid (200 µL per well) was transferred from the 24-well plate to a black 96-well plate (Greiner bio-one GmbH, Frickenhausen, Germany) for measurements. The AlamarBlue assay is based on the change of the blue color of the nonfluorescent indicator dye (resazurin) to a fluorescent pink reduced compound after acceptance of electrons. Fluorescence was measured on a Fluorescence Microplate Reader (Fluoroskan Ascent Microplate reader, ThermoFisher Scientific, Waltham, MA, USA). Results were provided as relative fluorescence using a 538 nm excitation filter and a 600 nm emission filter, normalized to untreated control. ## 4.7. Chorioallantoic Membrane Assay (CAM Assay) Fertilized white Leghorn chicken eggs (LSL Rhein-Main GmbH, Dieburg, Germany) were incubated at 38 °C with constant humidity of 55rH in an incubator (Type 3000 digital and fully automatic, Siepmann GmbH, Herdecke, Germany). For the first three days, eggs were placed horizontally on one side to ensure that the CAM would detach from the upwards-pointing eggshell. On embryonic development day (EDD) 3, eggs were prepared by removing 5–6 mL of the albumen in order to enlarge the space between eggshell and CAM. A small window of 3 × 2 cm was cut into the upwards-pointing part of the eggshell. The window was covered with Parafilm® (Sigma-Aldrich, St. Louis, MO, USA) to prevent evaporation. On EDD-8, Gelaspon Strips (Bausch & Lomb Inc.; New York, NY, USA) were cut in slices of 1 × 0.5 × 2 mm. An amount of 20 µL of each substance (512 mg/L CaO2, 10 mg/mL sodium hyaluronate, combination thereof) was added to the sponge. An amount of 20 µL of water was used as control. The further assessment of potential tissue adverse events was performed blinded. After 3 h, on EDD-10, and EDD-12, photographs were captured with a digital intravital fluorescence microscope (Olympus BXFM, Olympus Deutschland GmbH, Hamburg, Germany) at 100-fold magnification using the cellSens Dimension software package. ## 4.8. Broth Microdilution Assay MIC for P. gingivalis (DSM No. 20709, ATCC 33277) was determined by serial microdilution as described in a previous study [54]. P. gingivalis was cultivated on Schaedler agar (Becton-Dickinson, Heidelberg, Germany) for 48 h under anaerobic conditions ($90\%$ N2, $10\%$ CO2, $10\%$ H2) in an anaerobic jar system (Anoxomat Mart II, Mart Microbiology BV, Lichtenvoorde, the Netherlands). An amount of 1 mL of bacterial suspensions of 1 × 107 colony-forming units (0.5 McFarland standard) was added to 9 mL Wilkins Chalgrens broth (Merlin GmbH, Bornheim-Hersel, Germany). Broth microdilution was performed with a test volume of 100 μL per well using sterile 96-well plates (Greiner Bio-One GmbH, Frickenhausen, Germany). Column one served as negative control (sterile broth only), whereas column two served as positive control (bacterial suspension only). A serial dilution of 2048 mg/L CaO2 was performed, starting in column four. After serial dilution, 50 µL of the standardized bacterial suspension was added to each well. After an incubation period of 48 h for P. gingivalis at 37 °C, the plates were inspected. The MIC was determined as the lowest concentration where no visible growth was seen in the wells. Each test was repeated three times. ## 4.9. Statistical Analysis Graphic processing and statistical analysis was performed using the GraphPad Prism software 8.4 (GraphPad Software Inc., San Diego, CA, USA). To determine whether the data were normally distributed, the Kolmogorov-Smirnov normality test was applied. If data were normally distributed, ordinary one-way ANOVA with Dunnett’s correction for multiple comparisons was used for to determine statistically significant differences of treated samples compared to the controls. If data did not match the normal distribution assumption, the Kruskal–Wallis test with Dunn’s correction for multiple comparisons was used instead. The significance level was set to $p \leq 0.05$ for all comparisons. ## 5. Conclusions Taken together, our data showed that the O2-releasing HA was not cytotoxic for fibroblasts, osteoblasts, and HUVECS while anaerobic growth of P. gingivalis was inhibited, thereby demonstrating a therapeutic potential for topical oxygen-releasing biomaterials and demonstrating their potential for use in a preventive approach for the maintenance of oral eubiosis. ## 6. Patents On 16th of February 2022, the patent “Compositions and Kits for the Prevention or Treatment of Gum Diseases” was filed at the European Patent Office in Munich and has received the official file number EP 22 157 021.1. ## References 1. Papapanou P.N., Sanz M., Buduneli N., Dietrich T., Feres M., Fine D.H., Flemmig T.F., Garcia R., Giannobile W.V., Graziani F.. Periodontitis: Consensus report of workgroup 2 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. J. Periodontol. 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--- title: Comparative Gut Microbiome Differences between High and Low Aortic Arch Calcification Score in Patients with Chronic Diseases authors: - Yi-Hsueh Liu - Po Peng - Wei-Chun Hung - Ping-Hsun Wu - Cheng-Yuan Kao - Pei-Yu Wu - Jiun-Chi Huang - Chih-Hsing Hung - Ho-Ming Su - Szu-Chia Chen - Chao-Hung Kuo journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10059004 doi: 10.3390/ijms24065673 license: CC BY 4.0 --- # Comparative Gut Microbiome Differences between High and Low Aortic Arch Calcification Score in Patients with Chronic Diseases ## Abstract Gut dysbiosis can induce chronic inflammation and contribute to atherosclerosis and vascular calcification. The aortic arch calcification (AoAC) score is a simple, noninvasive, and semiquantitative assessment tool to evaluate vascular calcification on chest radiographs. Few studies have discussed the relationship between gut microbiota and AoAC. Therefore, this study aimed to compare the microbiota composition between patients with chronic diseases and high or low AoAC scores. A total of 186 patients (118 males and 68 females) with chronic diseases, including diabetes mellitus ($80.6\%$), hypertension ($75.3\%$), and chronic kidney disease ($48.9\%$), were enrolled. Gut microbiota in fecal samples were analyzed by sequencing of the 16S rRNA gene, and differences in microbial function were examined. The patients were divided into three groups according to AoAC score, including 103 patients in the low AoAC group (AoAC ≤ 3), 40 patients in the medium AoAC group (3 < AoAC ≤ 6), and 43 patients in the high AoAC group (AoAC > 6). Compared to the low AoAC group, the high AoAC group had a significantly lower microbial species diversity (Chao1 index and Shannon index) and increased microbial dysbiosis index. Beta diversity showed that the microbial community composition was significantly different among the three groups ($$p \leq 0.041$$, weighted UniFrac PCoA). A distinct microbial community structure was found in the patients with a low AoAC, with an increased abundance at the genus level of Agathobacter, Eubacterium coprostanoligenes group, Ruminococcaceae UCG-002, Barnesiella, Butyricimonas, Oscillibacter, Ruminococcaceae DTU089, and Oxalobacter. In addition, there was an increased relative abundance of class Bacilli in the high AoAC group. Our findings support the association between gut dysbiosis and the severity of AoAC in patients with chronic diseases. ## 1. Introduction Atherosclerosis is a systemic process involving lipid accumulation and inflammation of arterial beds and thickening of arterial walls. It is a major cause of cardiovascular disease (CVD), which has been a leading cause of death worldwide for many years [1]. Vascular calcification is a complication of advanced atherosclerosis, and it can be detected using imaging techniques such as computed tomography (CT), radiography, echocardiography, and vascular ultrasound [2,3]. Among them, CT is still considered the gold standard for quantifying coronary or aortic calcification [4,5]. However, CT is expensive and exposes the patients to high doses of radiation and the risk of cancer [6]. The aortic arch calcification (AoAC) score is a simple, noninvasive, semiquantitative assessment tool used to evaluate vascular calcification on chest radiographs [7]. The AoAC score has also been highly correlated with the AoAC volume as determined by multidetector CT [7]. AoAC detectable on chest X-rays has been strongly associated with coronary artery calcification [8] and cardiovascular events [9], and also with the severity of coronary artery disease as evaluated by the SYNTAX score in patients with acute coronary syndrome [10]. Previous studies have demonstrated that AoAC could predict renal function progression in chronic kidney disease (CKD) patients [11,12], and be independently associated with cardiovascular and all-cause mortality in both CKD and end-stage renal disease patients [12,13,14,15]. In addition, AoAC assessed by chest X-ray has been shown to be an independent risk factor for all-cause mortality and CVD in the general population, with a dose–response relationship in a large cohort study with 27,166 Chinese participants aged ≥ 50 years and free of CVD [16]. Taken together, AoAC is an effective modality to detect the severity of vascular calcification, and it plays an important role as a risk factor and prognostic marker in older populations and in those with chronic diseases. The gut microbiota comprises trillions of microbes, including bacteria, archaea and viruses, that colonize the entire gut [17]. The microbiota is a virtual organ in humans that moderates homeostasis and disease. In a healthy host, these effects are mostly symbiotic and influence immunity, nutrition, metabolism, and energy [18]. Changes in the composition of the gut microbiota, called gut dysbiosis, have been associated with the development of atherosclerosis-related CVD via various pathways [19]. The development of modern molecular techniques has allowed taxonomically heterogeneous microbial communities to be examined more comprehensively. The importance of some species in CVD has also been demonstrated [20]. Even though associations of specific bacterial taxa with atherosclerosis have been shown, many questions remain with regards to how the microbiome contributes to atherosclerosis [21]. Previous studies have demonstrated associations between changes in gut microbiota composition with coronary artery disease, carotid artery disease, arteriosclerotic plaque, and pulse wave velocity [20,21,22,23,24,25,26,27,28]. However, no studies have discussed the relationship between the gut microbiota and AoAC. Therefore, this study aimed to compare the intestinal microbiome composition between patients with chronic diseases and high or low AoAC scores. ## 2.1. Patient Characteristics A total of 186 individuals (118 males and 68 females), where the average age was 65.7 years, with chronic disease, including diabetes mellitus ($80.6\%$), hypertension ($75.3\%$), and chronic kidney disease ($48.9\%$), were enrolled in the study. The patients were divided into three groups according to AoAC score, including 103 patients in the low AoAC group (AoAC score ≤ 3), 40 patients in the medium AoAC group (3 < AoAC score ≤ 6), and 43 patients in the high AoAC group (AoAC score > 6), were enrolled in this study. The baseline characteristics of the enrolled patients with chronic disease are reported in Table 1. The mean age was 61.6 years in the low AoAC group and 71.6 years in the high AoAC group. Compared to the low AoAC group, the high AoAC group had an older age, higher diastolic blood pressure, higher hypertension prevalence with more Beta-blocker and calcium channel blocker medication use, lower hemoglobin level, and lower eGFR. There was no significant difference between the high and low groups in sex, BMI, systolic blood pressure, diabetes mellitus, CKD, CVD, cerebrovascular disease, and other medication use (including angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, diuretic, statins, fibrate, oral hypoglycemic agents and insulin). For clinical laboratory data, the high and low AoAC groups had no significant difference between albumin, HbA1c, triglycerides, total cholesterol, HDL-cholesterol, LDL-cholesterol, total calcium and phosphorous level. ## 2.2. Gut Microbiota Profile Differs among Different AoAC Severity The alpha diversity analysis showed that microbial community richness differed among groups (Kruskal–Wallis test for all groups using Chao1 index: $H = 6.577$, $$p \leq 0.037$$; Kruskal–Wallis test for all groups using Shannon index: $H = 6.497$, $$p \leq 0.038$$). Pairwise results are summarized in Figure 1 and Table 2 (alpha diversity), where the alpha diversity indices were significantly lower in the high AoAC group (Chao1 index: 96.89 ± 36.168; Shannon’s index: 4.133 ± 0.601) than that at the low AoAC group (Chao1 index: 114.313 ± 36.902; Shannon’s index: 4.428 ± 0.617), with no significant difference between the low AoAC and medium AoAC groups (Chao1 index: 109.361 ± 34.525; Shannon’s index: 4.336 ± 0.626). The beta diversity analysis showed that the microbial community composition was significantly different among the groups (ANOSIM for overall significance using unweighted UniFrac: $R = 0.0297$, $$p \leq 0.146$$; ANOSIM for overall significance using weighted normalized UniFrac: $R = 0.0599$, $$p \leq 0.041$$). Specifically, while the results of pairwise ANOSIM tests using unweighted UniFrac matrices did not reach significance (Figure 2a, Table 3a), adopting weighted normalized UniFrac dissimilarities revealed the distinct clustering patterns of the low AoAC and high AoAC groups (Figure 2b, Table 3b). In addition, the high AoAC group had higher MDI than the low AoAC group (Figure 2c). ## 2.3. Specific Microbial Taxa Are Associated with Different AoAC Severity We analyzed the relative abundance of taxa to identify the taxa differences between AoAC severities using LEfSe (Linear discriminant analysis Effect Size) to discriminate features associated with AoAc levels (Figure S1a,b). Based on the logarithmic LDA (Linear discriminant analysis) score > 2 and Kruskal–Wallis test $p \leq 0.05$, we identified 47 taxa among the three groups at different taxonomic levels, including 15 genera and 10 species. At the genus level, the low AoAC group presented an increased relative abundance of Agathobacter, Eubacterium coprostanoligenes group, Ruminococcaceae UCG-002, Barnesiella, Butyricimonas, Oscillibacter, Ruminococcaceae DTU089, and Oxalobacter (Figure 3). As for the high AoAC group, we found an increased relative abundance of class Bacilli. MaAsLin2 results reconciled the consistency in those biomarkers at genus level after adjusting for the covariates (age, sex, HTN, and CKD), whereas it failed to detect the significance at class level (the statistical results are presented in supplementary information Table S1 and Figure S2). Further analysis of the KEGG module also revealed a difference in gut microbiota pathway in low AoAC group compared with high AoAC group (Figure S3). ## 3. Discussion The aim of this study was to investigate the relationship between microbiota composition and AoAC in patients with chronic diseases. We found structural differences in the stool microbial communities between the high and low AoAC groups, with reduced alpha diversity (Chao1 index and Shannon index) and increased MDI in the high AoAC group. Beta diversity analysis showed that the microbial community composition was significantly different among the three different AoAC severity groups ($$p \leq 0.041$$, weighted UniFrac PCoA). A distinct microbial community structure was found in the patients with a low AoAC score, with increased abundances at the genus level of Agathobacter, Eubacterium coprostanoligenes group, Ruminococcaceae UCG-002, Barnesiella, Butyricimonas, Oscillibacter, Ruminococcaceae DTU089, and Oxalobacter. In addition, there was an increased relative abundance of class Bacilli in the high AoAC group. The microbiota may influence atherosclerosis by promoting plaque development via direct and distant infection, activation of the immune system, alteration of cholesterol metabolism, and production of bacterial metabolites [29]. Emerging data have demonstrated strong associations between the gut microbiota and risk factors for the development of CVD, including atherosclerosis, inflammation, obesity, insulin resistance, platelet hyperactivity, and plasma lipid abnormalities [30,31,32]. Several studies of humans and animal models have demonstrated associations between gut microbial metabolites such as trimethylamine-N-oxide (TMAO), short-chain fatty acids (SCFAs), and bile acid metabolites (amino acid breakdown products) with CVD [30,33,34]. TMAO has been shown to increase the risk of CVD by altering cholesterol and bile acid metabolism, activating inflammatory pathways, and promoting foam cell formation and platelet hyperactivation, whereas SCFAs have been shown to contribute to atherosclerosis and hypertension by different mechanisms [32,35]. Several studies have reported the presence of genetic material from a wide range of bacteria in atherosclerotic plaque [23,24,25,26]. In a study conducted in Moscow, enterotyping identified two clusters according to the alpha diversity, and the cluster with lower diversity was associated with higher intima-media thickness [27]. In addition, in a Chinese study, the severity of coronary artery disease was significantly associated with changes in the composition of both gut microbiota and metabolites, represented by Roseburia, Klebsiella, Clostridium IV and Ruminococcaceae [22]. In a Swedish study, greater enrichment of the genus Collinsella was found in patients with carotid artery stenotic atherosclerotic plaque, whereas in healthy controls, greater enrichment of Roseburia and Eubacterium was found [21]. In a study of the TwinsUK cohort, the association of carotid–femoral pulse wave velocity (PWV) and gut microbiome composition was studied in 617 middle-aged women, and the results showed that PWV was negatively correlated with gut microbiome alpha diversity after adjusting for covariates [28]. Growing evidence suggests that higher alpha diversity, a measure of bacterial richness or evenness, is linked to a better health status and temporal stability of the gut microbiome [36], whereas a relative lack of alpha diversity is linked to poor health. Reduced gut microbial alpha diversity has been found in individuals with a variety of chronic illnesses, including obesity, inflammatory bowel disease, hypertension, and type 2 diabetes, as well as older subjects with frailty [37,38,39,40,41]. In our study, the high AoAC group had lower alpha diversity and a higher MDI than the low AoAC group, and there was a significant difference in alpha diversity between the two groups. Thus, our findings demonstrate that the degree of AoAC detectable on chest X-rays is associated with the alpha diversity and composition of the gut microbiota. We also found that several butyrate-producing bacteria were markedly increased in the low AoAC group, including genus Agathobacter, Ruminococcaceae UCG-002, Ruminococcaceae DTU089, Oscillibacter and Butyricimonas. Butyrate is a main SCFA and a primary colonocyte energy source, and it also maintains the integrity of the gut barrier and homeostasis of the intestine by anti-inflammatory processes [42,43,44]. Several studies have reported an association between butyrate and reduced appetite, potentially due to increases in glucagon-like peptide-1 (GLP-1), leading to reduced energy intake and a decrease in body weight [45,46,47]. Moreover, the administration of butyrate has been shown to improve metabolic disorders, including hepatic lipogenesis and hyperglycemia through glucose transporter type 4, GLP-1, and AMP-activated protein kinase [48,49]. Our results support a link between specific butyrate-producing bacteria and low AoAC in patients with chronic diseases. Bacteria have been associated with many chronic diseases in previous studies, and they may play a specific role in reducing AoAC. Agathobacter is a member of the Lachnospiraceae family, which can produce butyrate through dietary fiber fermentation [50]. Agathobacter has been reported to be more prevalent in normoglycemic subjects than in those with prediabetes [51]. Ruminococcaceae UCG-002, Ruminococcaceae DTU089, and Oscillibacter all belong to the Ruminococcaceae family. Ruminococcaceae are less abundant in hypertensive patients than in normotensive patients [52], and they were negatively correlated with PWV in the TwinsUK cohort [28]. Ruminococcaceae have been negatively correlated with metabolic disease in humans [53]. Jiant et al. demonstrated an association between Ruminococcaceae UCG-002 with a lower risk of metabolic syndrome, type 2 diabetes mellitus, and dyslipidemia, and also a significantly inverse association with BMI [54]. Ruminococcaceae DTU089 have been shown to be more abundant in subjects with lower protein intake [55]. Oscillibacter have been shown to be significantly enriched in healthy subjects, and to be reduced in patients with non-alcoholic fatty liver disease [56] and hypertension [57]. A Mendelian randomization analysis demonstrated that Oscillibacter had a causal effect on reducing blood triglyceride concentrations, and lowering BMI and waist-hip ratio [58]. Previous studies have reported decreased abundances of the Lachnospiraceae and Ruminococcaceae families in patients with nonalcoholic steatohepatitis [56,59] and coronary artery disease [22]. Butyricimonas is a Gram-negative anaerobic bacterial genus of the family Odoribacteraceae. Treatment of metabolic disorders with metformin and statins has been shown to significantly increase the relative abundance of Butyricimonas in the gut, and this has been significantly associated with metabolic parameters [60,61]. Lee et al. reported that Butyricimonas could prevent high fat diet-induced diabetes and metabolic disorders in mice via the GLP-1 receptor [62]. Butyricimonas has also been negatively correlated with insulin resistance and obesity in humans [63,64]. We also found that some non-butyrate-producing bacteria may be involved in certain metabolic pathways that are associated with a low AoAC. The Eubacterium coprostanoligenes group play a major role in the metabolism of coprostanol, leading to a hypocholesterolemic effect [65,66]. Greater cholesterol absorption has been reported in the gut of patients with atherosclerotic CVD [67,68]. Alterations in the gut microbial community have been directly related to the rate of cholesterol conversion to coprostanol, and highly efficient cholesterol transformation to coprostanol has been associated with a lower risk of CVD [67,69]. Karlsson et al. reported that Eubacterium were enriched in healthy controls, and significantly negatively correlated with known risk factors for atherosclerosis including white blood cell count, low-density lipoprotein, and cholesterol in patients with atherosclerosis [21]. Barnesiella have been shown to induce the production of SCFAs in the gut and to indirectly or directly have an anti-inflammatory effect through an increase in SCFAs in the intestinal tract [70]. Barnesiella have also been associated with the fermentation of carbohydrates, pathogenic bacteria inhibition, and regulation of immunity [70,71,72]. Oxalobacter have been shown to play a key role in the degradation of oxalate in the intestinal tract, and to potentially have the ability to reduce the risk of calcium oxalate kidney stones [73,74]. Oxalate induces reactive oxygen species, which promote inflammation and cause systemic oxidation and vascular endothelial cell injury [75,76]. Li et al. reported that calcium oxalate calculi were significantly associated with abdominal aortic calcification after adjusting for confounding factors related to vascular calcification [74]. However, further studies are needed to investigate the specific pathophysiological mechanisms between oxalate and aortic calcification. Several limitations should be mentioned. First, a cross-sectional study can only provide data of relative bacteria abundance at a single point in time, and therefore we could not make causal inferences. Further follow-up studies are needed to confirm our results. Second, we used fecal samples to assess the microbiota, and this may differ from the microbiota from other parts of the intestine. In addition, 16s rRNA sequencing is limited as it cannot differentiate viable from unviable bacteria. Therefore, a significant portion of the taxa identified by sequencing may not be metabolically active. Third, several butyrate-producing microbes were associated with low AoAC in our study; however, butyric acid was not investigated in this study. Fourth, as healthy individuals were not included in our study, a comparison between the control group and participants with chronic disease was not feasible. We will include more healthy individuals as the control group and other chronic disease patients in the future to analyze the role of gut microbiota in vascular calcification with a larger dataset. Fifth, the high AoAC group was older and had a higher proportion of hypertension and CKD than the low AoAC group, which may have affected the distribution of AOAC severity, although we had used MAsLin2, where age, sex, hypertension, and CKD were included as random effects to adjust for possible confounding impacts. Finally, the study was performed in Asian patients with chronic diseases, and they may have had a different diet compared to other populations. Therefore, the effect of diet on the gut microbiome should be interpreted with caution. In conclusion, our findings support the association between gut dysbiosis and the severity of AoAC in patients with chronic diseases. A distinct microbial community structure and taxa features were found in the patients with a low AoAC score. However, it is still not clear how these particular gut bacteria prevent vascular calcification. Further in-depth studies are needed to investigate the relationship between these specific bacteria and AoAC. ## 4.1. Study Participants From March 2020 through July 2020, 186 participants (118 males and 68 females) with chronic diseases were recruited from the outpatient department of Kaohsiung Municipal Siaogang Hospital. In this study, chronic diseases were defined as hypertension, diabetes or CKD that had been treated for more than 3 months. Eligible participants were aged between 35 and 99 years. Patients with active malignancies, abdominal cancer, radiation therapy to the abdomen, acute or chronic inflammation, and those who were prescribed antibiotics within 3 months before enrollment were excluded. The Institutional Review Board of Kaohsiung Medical University Hospital approved this study (KMUHIRB- G(II)-20190014; 28 May 2019), and all participants provided written informed consent. All methods were performed in accordance with relevant guidelines. ## 4.2. Demographic, Medical, and Laboratory Data Demographic data, age, sex, body mass index (BMI), medical history, medications, and biochemical data were obtained from electronic medical records. Hypertension was defined as systolic blood pressure/diastolic blood pressure ≥$\frac{140}{85}$ mmHg or the use of antihypertensive drugs. Diabetes was defined as a glycated hemoglobin (HbA1c) level ≥$6.5\%$ or the use of antidiabetic agents. CKD was defined as kidney damage or estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 for ≥3 months. Overnight fasting blood samples were obtained for biochemical data including hemoglobin, albumin, fasting glucose, HbA1c, eGFR (calculated using the 4-variable Modification of Diet in Renal Disease study equation [77]), triglycerides, total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, uric acid, total calcium and phosphorous. ## 4.3. Evaluation of AoAC by Chest Radiography A single experienced radiologist who was blinded to the clinical information of the patients reviewed all chest radiographs. Calcification of the aortic arch was assessed by dividing the aortic arch on chest radiographs into 16 sections according to their circumference [7]. The AoAC score was determined as the number of sections with vascular calcification. ## 4.4. Fecal Sample Collection and Bacterial 16S rRNA Amplicon Sequencing and Processing Each patient received a small cylindrical receptacle enclosed in a zippered bag and wrapped in a small brown paper bag. The receptacle was hermetically sealed and sterile. The receptacles were used by the patients to collect their own feces, which were then frozen at home before being brought to the hospital. Fecal samples were collected on the same day as or the night before biochemical data were collected. The fecal samples were sent to the laboratory immediately at room temperature. Prior to deoxyribonucleic acid (DNA) extraction, the samples were frozen in a laboratory freezer at −20 °C. Bacterial genomic DNA from the samples was extracted using a QIAamp PowerFecal DNA Kit (Qiagen), with the concentration adjusted to 5 ng/ul. The16S rRNA gene V3-V4 region was amplified by specific primers (341F: 5′-CCTACGGGNGGCWGCAG-3′, 806R: 5′- GACTACHVGGGTAT CTAATCC -3′) and sequenced on an Illumina MiSeq platform for paired 300-bp reads. Paired-end raw FASTQ reads were processed using Trimmomatic [78], in which adapter trimming and low-quality (average QV < 20) read filtering were performed. Subsequently, primer removal was achieved using Cutadapt [79], in which the minimum length was set to 150 kb. The DADA2 [80] pipeline was used for error modelling and ASV (amplicon sequence variant) construction per sample, in which read pairs were merged with ≥20 bp overlap (allowing for 0 mismatches), resulting in 868 ASVs with a total frequency of 10,413,122 and an average of 55,984.527 ± 8090.5082 per sample. ## 4.5. Statistical and Bioinformatics Analyses of the Microbiota As uneven sampling depth may increase the probability of false conclusions [81], we rarified the ASV dataset to 27,919 reads per sample (the minimum library size among all samples) and then used it for alpha and beta diversity estimation. For alpha diversity, we calculated the Chao1 [82] and Shannon [83] indices. Pairwise Kruskal–Wallis tests, where p values were corrected following the Benjamini–Hochberg procedure [84], were used to compare the alpha diversity indices among groups. Between-group (beta) diversity was assessed with principal coordinate analysis (PCoA) using unweighted and weighted normalized UniFrac [85] distance matrices. To investigate the impact of AoAC on microbial community composition, we used pairwise ANOSIM (analysis of similarity) tests [86], with 999 permutations applied to unweighted and weighted normalized UniFrac dissimilarity measures, followed by Benjamini–Hochberg correction [84]. Additionally, the microbial dysbiosis index (MDI) [87] was calculated to assess the association between the AoAC level and degree of dysbiosis. Differences among groups were examined using the non-parametric Kruskal–Wallis test and post-hoc Dunn’s all-pairs comparison test. Taxonomy classification was performed using the q2-feature-classifier plugin in QIIME 2 [88], with a confidence threshold of 0.7 (default) to search the SILVA reference database (release v132, L7 taxonomy), resulting in 111 taxa. To identify the potential microbial biomarkers associated with AoAC, we analyzed relative abundances of taxa using LEfSe (linear discriminant analysis effect size) [89], where logarithmic LDA scores for discriminative features and the significance level for the on-parametric factorial Kruskal–Wallis test were set to 2 and 0.05, respectively. In addition, significant taxa identified by LEfSe were tested using pairwise Dunn’s test with Holm’s procedure [90], to examine the association between a given biomarker and AoAc level. To validate the findings of LEfSe analysis, we further compared abundances at the genus level between low and high AoAC groups using Multivariate Association with Linear Models 2 (MaAsLin2) [91], where age, sex, hypertension, and CKD were included as random effects to adjust for possible confounding impacts. With arcsine square-root transformation, taxa with relative abundances of at least $20\%$ of all samples were tested. ## 4.6. Functional Annotation To predict functional profiling of the microbiota, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States version 2 (PICRUSt2) [92] was used to estimate KEGG [93] pathway abundances across samples. 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--- title: Ketoprofen-Based Polymer-Drug Nanoparticles Provide Anti-Inflammatory Properties to HA/Collagen Hydrogels authors: - Norbert Halfter - Eva Espinosa-Cano - Gloria María Pontes-Quero - Rosa Ana Ramírez-Jiménez - Christiane Heinemann - Stephanie Möller - Matthias Schnabelrauch - Hans-Peter Wiesmann - Vera Hintze - Maria Rosa Aguilar journal: Journal of Functional Biomaterials year: 2023 pmcid: PMC10059015 doi: 10.3390/jfb14030160 license: CC BY 4.0 --- # Ketoprofen-Based Polymer-Drug Nanoparticles Provide Anti-Inflammatory Properties to HA/Collagen Hydrogels ## Abstract Current limitations of wound dressings for treating chronic wounds require the development of novel approaches. One of these is the immune-centered approach, which aims to restore the pro-regenerative and anti-inflammatory properties of macrophages. Under inflammatory conditions, ketoprofen nanoparticles (KT NPs) can reduce pro-inflammatory markers of macrophages and increase anti-inflammatory cytokines. To assess their suitability as part of wound dressings, these NPs were combined with hyaluronan (HA)/collagen-based hydro- (HGs) and cryogels (CGs). Different HA and NP concentrations and loading techniques for NP incorporation were used. The NP release, gel morphology, and mechanical properties were studied. Generally, colonialization of the gels with macrophages resulted in high cell viability and proliferation. Furthermore, direct contact of the NPs to the cells reduced the level of nitric oxide (NO). The formation of multinucleated cells on the gels was low and further decreased by the NPs. For the HGs that produced the highest reduction in NO, extended ELISA studies showed reduced levels of the pro-inflammatory markers PGE2, IL-12 p40, TNF-α, and IL-6. Thus, HA/collagen-based gels containing KT NPs may represent a novel therapeutic approach for treating chronic wounds. Whether effects observed in vitro translate into a favorable profile on skin regeneration in vivo will require rigorous testing. ## 1. Introduction In Western civilizations, there is an increasing number of chronic skin wounds as the population ages [1]. The consequences are a reduced quality of life and high costs for the health care system. Diseases, such as diabetes and obesity, cause a further rise in chronic skin wounds due to detrimental pre-existing conditions, leading to a higher likelihood of treatment failure and recurrence, which further increases discomfort and costs [2]. Although various therapies are available for chronic wound treatment and care, their effectiveness is somewhat limited, and relapse occurs in many patients [2,3,4]. As a result, the development of novel materials for improved treatment of chronic skin wounds is needed. One promising strategy for promoting the healing chronic wounds is an immune-centered approach [5]. Here, the mechanisms of the immune system are to be modulated for healing to occur. Besides danger signals from damaged cells, neutrophils and macrophages play an important role in this respect. In chronic wounds, pro-inflammatory M1-like macrophages are persistent, resulting in prolonged inflammation [6]. However, restoring pro-regenerative and anti-inflammatory M2-like macrophages can help to improve the healing process [7,8]. For the treatment of chronic wounds, films, foams, hydrocolloids, and hydrogels (HGs) are used as dressings that are made from polyurethanes, alginate, collagen (coll), pectin, carboxymethyl cellulose, and propylene glycol [9,10]. All of them create the moisture balance that allows wounds to heal faster. Depending on the material used, other beneficial properties for wound healing may also be present. There are a large number of wound dressings from various manufacturers that fall into the abovementioned material categories [3,9,10,11,12,13,14,15,16,17]. However, studies in the clinic show that repair via scar formation predominates, with no physiological regeneration of the skin [18]. Furthermore, adhesive dressings can take off a large portion of healthy or newly formed skin during removal [19]. In addition, extensive clinical studies to evaluate the effectiveness of available wound dressings are limited, and the superiority of particular wound dressings is indistinguishable [20]. In the past, components of the extracellular matrix (ECM) have proven to be suitable building blocks for an immune-centered approach, as they are involved in the process of wound healing through interaction with cells, growth factors, and cytokines [21,22,23,24,25,26]. One major component of the ECM of skin is hyaluronan (HA), a glycosaminoglycan composed of repeating disaccharide units of D-glucuronic acid and N-acetyl-D-glucosamine [(-4GlcUAβ1-3GlcNAcβ1-)n]. The role of HA in wound healing is emphasized by its involvement in all stages of wound healing, e.g., blood clotting, cell migration and infiltration, as well as inhibition of neutrophil migration, gap filling, and structural organization for the newly forming ECM, as summarized elsewhere [8,27,28]. HA-based wound dressings are also available commercially but face the same problems as other dressings. Generally, there are only a small number of participants in clinical trials, and the dressing may be insufficient for the complex real-life situations that the clinicians have to handle (e.g., different ages, depth of the wound, and wound position). Nevertheless, Gravante et al. show the potential of HA dressings, as $74\%$ of all patients achieved wound closure within 39 days [29]. However, at least $7\%$ of the patients showed only partial re-epithelialization after the same time period, which makes further improvements for these dressings desirable. In vitro studies have shown that HA/coll-based HGs were a suitable growth environment for endothelial cells, keratinocytes, and fibroblasts [30,31]. A recent study demonstrated that the same HGs, releasing chemically sulfated HA (sHA) as an immunoregulatory component, improved tissue repair in chronic wounds of diabetic db/db mice, i.e., by enhancing pro-regenerative M2-macrophage activation [32]. Compared to the HGs without sHA, wound closure increased from $30\%$ to $50\%$ of the cases investigated. Although this is already a marked improvement, the results still indicate that further measures need to be taken, which could be the combination with further anti-inflammatory agents. The use of non-steroidal anti-inflammatory drugs (NSAIDs) offers an additional anti-inflammatory treatment by influencing macrophage polarity and improving the healing of chronic wounds [33,34]. The NSAIDs are effective because of their inhibition of cyclooxygenase-2 (COX-2), which is responsible for the synthesis of prostaglandins (PG) in pathological processes, such as inflammation [35]. Furthermore, NSAIDs have COX-independent mechanisms of action that contribute to their anti-inflammatory properties [36]. Unfortunately, most NSAIDs are hydrophobic, which results in low bioavailability. To address this problem, hydrophilic nanoparticles (NPs) with NSAID moieties have been developed [33,34]. Previously, in vitro experiments with ketoprofen (KT)-based NPs and macrophages showed low toxicity, as well as a reduction in nitric oxide (NO) and other pro-inflammatory markers, such as Il-12b and TNF-α in inflammatory conditions [34]. In addition, anti-inflammatory markers, such as VEGF and Il-10, were increased in expression. These results suggest that NSAID-containing NPs are a promising immunoregulatory component to be included in functional wound dressings for regulating macrophage activities in non-healing wounds. In this study, we combined HA/coll-based HGs and CGs with anti-inflammatory KP NPs for the first time. The aim was to assess the NP’s suitability in enhancing the anti-inflammatory properties of these HGs and, thus, to reveal the composite’s potential for application as an improved anti-inflammatory wound dressing. In this context, NP concentrations and loading technique for NP incorporation was expected to influence the efficacy of NPs. Thus, we designed different HA/coll-based HG and CG variants with NSAID-containing NPs. The loading capacity and NP distribution within the gels, NP release, HG and CG morphology, and mechanical properties were determined. Furthermore, cell viability, proliferation, NO release, multinucleated giant cell formation, and the production of inflammatory and anti-inflammatory markers were used to assess the cellular response of a murine macrophage cell line to NP-loaded gels. The outcome of this study was expected to clarify which gel variant and NP concentration will be the most suitable for prospective combinatory approaches with other anti-inflammatory compounds and in vivo experiments in an animal model for chronic skin wounds. ## 2.1. Hyaluronan Methacrylate Preparation For HA methacrylate (HA-MAC) synthesis, native HA (MW = 1400 kDa from Streptococcus, Kraeber & Co GmbH, Ellerbek, Germany) was processed as reported before [37]. In brief, HA was dissolved in borate buffer (pH 8.5, Sigma-Aldrich, Taufkirchen, Germany) and treated with a 15-fold molar excess of methacrylic acid anhydride (Sigma-Aldrich, Taufkirchen, Germany) at 5 °C for 24 h. To purify the product, it was precipitated in acetone (Sigma-Aldrich, Taufkirchen, Germany) and dialyzed against water (MWCO = 3500 g/mol). ## 2.2. Nanoparticle Synthesis NPs were synthesized using the previously described copolymer poly(HKT-co-VI) (48:52), obtained by free radical copolymerization of a methacrylic derivative of ketoprofen (HKT) and 1-vinylimidazole (VI) [34]. After analyzing the copolymer by 1H-NMR (Varian Mercury, 400 MHz, 25 °C), the NPs were obtained by the nanoprecipitation method (Figure 1). Briefly, an organic solution (acetone (Scharlau, Barcelona, Spain): ethanol (Scharlau), 80:20 (V:V)) of the copolymer (10 mg/mL) was added dropwise to an aqueous buffer solution at pH 4 (0.1 M acetic acid and 0.15 M NaCl, both Panreac, Barcelona, Spain). The remaining organic solvent was eliminated by evaporation under continuous stirring overnight, and the resultant NPs were stored at 4 °C until used. For binding and release studies and the visualization of the NPs in the HGs and CGs, the NPs were loaded with coumarin-6 (C6, Sigma-Aldrich, Lyon, France). For this, C6 ($1\%$ w:w with respect to the polymer) and the corresponding copolymer were dissolved in a mixture of acetone:ethanol (80:20, V:V) and slowly dropped into the aqueous buffer solution (0.1 M Acetic Acid, 0.1 M NaCl) at pH 4 under magnetic stirring. NPs were dialyzed against the same buffer for 72 h to eliminate remaining organic solvents and the soluble non-entrapped C6. The resultant NPs were filtered through 1 μm nylon filters (Whatman Puradisc, cytiva, Barcelona, Spain) to eliminate insoluble C6. ## 2.3. NP Characterization The mean hydrodynamic diameter (Dh) of NPs, size distribution, and polydispersity index (PDI) were studied by dynamic light scattering (DLS) using a Malvern Nanosizer Nano-ZS Instrument (Madrid, Spain) equipped with a 4 mW He–Ne laser (λ = 633 nm) at a scattering angle of 173°. The zeta potential (ξ) was determined by laser Doppler electrophoresis (LDE) using a Malvern Nanosizer Nano-ZS Instrument equipped with a 4 mW He-Ne laser at 25 °C. Experiments were performed in triplicate, and results were expressed as the statistical average ± standard deviation (SD). ## 2.4.1. Preparation of Hydro- and Cryogels HGs were prepared as previously described [30]. Briefly, a 1 mg/mL coll solution was prepared by mixing rat tail coll type I (Corning, New York, NY, USA) and 0.01 M acetic acid (Sigma-Aldrich, Taufkirchen, Germany). Before in vitro fibrillogenesis at 37 °C for 4 h, the coll solution was diluted with fibrillogenesis buffer (0.05 M Na2HPO4, Carl-Roth, Karlsruhe, Germany and 0.01 M KH2PO4, pH 7.4, Sigma-Aldrich, Taufkirchen, Germany) to a concentration of 0.5 mg/mL coll. After fibrillogenesis, HA-MAC was dissolved in fibrillated coll solution to reach concentrations of 10 or 30 mg/mL HA-MAC, followed by the addition of 10 mg/mL lithium phenyl-2,4,6-trimethylbenzoyl-phosphinate (LAP, TCI Deutschland GmbH, Eschborn, Germany) in a ratio of 1:10 (V:V). Either 50 µL of this solution was pipetted between two cover slides (Ø = 12 mm, VWR, Darmstadt, Germany) coated with Sigmacote (Sigma-Aldrich, Taufkirchen, Germany), or 200 µL was pipetted into mold casts (Ø = 7.5 mm, just for porosity experiments). HGs were photo-crosslinked by UV irradiation (365 nm, 0.17 W/cm2, for 10 min), frozen for 30 min at −80 °C, and then freeze-dried with a Martin Christ Epsilon 2–4 LSC device (freeze-dry steps: [1] pre-cooling to −15 °C, [2] reducing pressure to 1.030 mbar at −15 °C for 105 min, [3] heating to 20 °C in 150 min under 1.030 mbar, [4] drying at 1.030 mbar and 20 °C for 720 min, [5] pressure reduction to 0.001 mbar and 20 °C in 10 min, [6] heating to 30 °C under 0.001 mbar in 50 min, and [7] drying at 30 °C and 0.001 mbar for 120 min). CGs were obtained similarly to HGs, except that they were frozen at −80 °C for 30 min before UV irradiation. More details about the fabricated gels can be found in Table 1. ## 2.4.2. Loading of the Gels with NP NPs were loaded into the gels via different methods, i.e., by soaking of freeze-dried scaffolds or by incorporation during the fabrication process. To determine the concentration of NPs needed to achieve a particular loading level, first loading studies were performed with 1 mg/mL NP solution (max NP; Table 1; Supporting Material, Table S1). Based on this, the adapted concentrations were used for subsequent loading of HGs and CGs with NPs (Table 1; Supporting Material, Table S1). In general, NP loading of HGs and CGs via soaking was carried out by incubating the scaffolds with 125 µL NP solution on the top and bottom sides separately for 24 h at RT to ensure even NP distribution. After soaking, the samples were washed twice with 500 µL phosphate buffered saline (PBS, Sigma-Aldrich, Taufkirchen, Germany). Subsequently, the gels were frozen for at least 30 min and freeze-dried before use. C6-loaded NPs were used for determining the NP release and concentration inside the gels, along with 3D visualization with confocal light scanning microscopy (CLSM). All HGs and CGs used for cell experiments were prepared from NPs without C6. The incorporation of NPs into HGs during the preparation process was carried out by adding the NPs before the chemical crosslinking reaction (CL-10HA 40NP sample, Table 1). Here, the procedure in Section 2.4.1. was followed, except for the step of dissolving the HA-MAC, which was performed in 0.5 mg/mL coll containing 0.8 mg/mL NPs. For this purpose, coll was diluted with deionized water and mixed with 10× fibrillogenesis buffer (0.5 M Na2HPO4, 0.1 M KH2PO4, pH 7.4) in a ratio of 1:9 (V:V) to obtain a 2.5 mg/mL coll solution. This was fibrillated first for 4 h and subsequently mixed with 1 mg/mL NP solution in a ratio of 1:4 (V:V) followed by dissolving of HA in this solution. After adding $\frac{1}{10}$th of the volume of 10 mg/mL LAP, 50 µL of the mixture was pipetted between two cover slides with subsequent UV crosslinking, freezing, and freeze-drying. Before use, CL-10HA 40NP and all other scaffolds not loaded with NPs by soaking were swollen in 500 µL PBS at RT for 1 h, washed twice with 500 µL PBS, and freeze-dried again. An overview of the different fabrication procedures can be found in Figure 2. ## 2.5. NP Release Studies from Hydro- and Cryogels Those HGs and CGs loaded with 1 mg/mL NPs (max NP) and subsequently washed with PBS were incubated in 500 µL PBS for either 1 d or 7 d at 37 °C. Gels for the NP release studies were used directly after washing without subsequent freeze-drying. Washing solutions, supernatants, and gels were stored at −20 °C prior to analysis. ## 2.6. Determination of NP Concentration The NP concentration in washing solutions, supernatants, and gels was determined by measuring the fluorescence (Tecan, Infinite® M200 PRO, λExc = 485 nm, λEmi = 528 nm). Gels were digested with 600 µL of 0.01 M acetate buffer (pH 5.35) containing 0.15 M NaCl (Sigma-Aldrich, Taufkirchen, Germany) and 1000 U/mL hyaluronidase (HYAL, EC 3.2.1.35, from bovine testes, Sigma-Aldrich, Taufkirchen, Germany) prior to the determination of the NP concentration (Hauck et al. 2021). For more details about the digestion conditions, see Table 2. Since CGs could not be digested completely, the remaining CGs were extracted twice with 150 µL EtOH. After the extraction, EtOH supernatants were centrifuged and measured. Prior to the determination of NP concentration, acidic solutions containing fluorescent NPs (NP-stock solution and digestion solutions) were made basic by adding $\frac{1}{10}$th volume of 1 M NaOH. Subsequently, all solutions containing NPs were centrifuged at 10,000× g RCF for 5 min, and the supernatants were discarded. Next, pellets (NPs) were resuspended in 150 µL ethanol absolute (EtOH, VWR, Fontenay-sous-Bois, France), and centrifuged again at 10,000× g RCF for 5 min before the fluorescence was measured. In the next step, the obtained NP amounts were used to calculate the NP concentration incorporated in the gels. ## 2.7. NP Distribution in Hydro- and Cryogels CLSM was used for the visualization of NPs in gels. For this purpose, freeze-dried samples were swollen for up to 30 min in PBS and measured on an upright Axioscop 2 FS mot microscope equipped with a LSM 510 META module (Zeiss, Jena, Germany) using an argon+ laser for excitation of C6 at 488 nm. ## 2.8. Hydro- and Cryogel Morphology Scanning electron microscopy (SEM, Philips ESEM XL 30, FEI) using a secondary electron detector was used to assess the morphology of freeze-dried gels. The HG and CG scaffolds were cut with a scalpel and mounted on the SEM stage, followed by sputter coating (MED 010, Balzers, Balzers, Liechtenstein) with carbon (Plano, Wetzlar, Germany). The images were taken at different magnifications using an acceleration voltage of 3 kV and a spot size of 3. ## 2.9. Mechanical Characterization of the Hydro- and Cryogels The elastic modulus of the swollen samples was determined using the CellScale Microsquisher (Waterloo, ON, Canada). After swelling freeze-dried samples for 1 h in PBS, uniform HGs and CGs with a 3 mm diameter were obtained with a biopsy punch. After measuring the height of the gels with the integrated digital camera, force–displacement curves were obtained at a velocity of 1.67 µm/s in a range below $15\%$ displacement. The linear area of the stress–strain curve was used to determine the elastic modulus. To reveal significant differences, one-way ANOVA was performed for $p \leq 0.05$ ($$n = 3$$). ## 2.10. Porosity of the Hydro- and Cryogels The porosity (Φ) was determined with a pycnometer and calculated using the following formula:[1]Φ=1−(m1−m2+m3)VT·PPBS where m1 is the mass of the pycnometer filled with PBS, m2 is the mass of the sample in the pycnometer filled with PBS, m3 is the mass of the freeze-dried sample, ΡPBS is the density of PBS (1.0047 g/mL) at RT (22.5 °C), and VT is the total volume of the swollen sample. VT was determined using the dimensions of the cylindrical 200 µL samples (HGs using a caliper, and CGs using the Microsquisher). ## 2.11. Cell Culture Cells were cultured using a murine macrophage cell line (RAW264.7, 91062702, Sigma-Aldrich, Gillingham, UK). Cells were maintained over permissive conditions in high-glucose Dulbecco’s modified Eagle’s medium (DMEM; D6546, Sigma, St. Louis, MO, USA) supplemented with $10\%$ fetal bovine serum (FBS; Gibco, Brazil, Thermo Fisher, Madrid, Spain), $2\%$ L-glutamine (2 × 10−3 M, Sigma, St. Louis, MO, USA), and $1\%$ penicillin G (100 U/mL, Sigma, St. Louis, MO, USA) at 37 °C in a humidified incubator with $5\%$ CO2. ## 2.12.1. Micro-Mass Cell Seeding Before cell seeding, HGs and CGs were pre-incubated with 500 µL of complete RAW264.7 culture media in 24-well plates for 1 h at 37 °C. Then, 50 µL of RAW264.7 (2 × 106 cells/mL) were micro-mass seeded on top of each gel (i.e., 10HA, 10HA 40NP, 10HA 120NP, CL-10HA 40NP, 30HA, 30HA 40NP, cryo 10HA, and cryo 10HA 40NP). After 40 min of incubation under permissive conditions (37 °C, $5\%$ CO2), 500 µL of culture media were added to each well, and cells were incubated overnight. ## 2.12.2. Cell Proliferation Cell proliferation was determined in the HGs and CGs using an AlamarBlue® (Bio-Rad Laboratories, Inc., manufactured by Trek Diagnostic System, Hercules, CA, USA) assay after 24 and 48 h. All gels were incubated with the AlamarBlue® reagent at $10\%$ (V:V) in medium without phenol red at 37 °C for 3 h. Fluorescence of reduced AlamarBlue® was determined at $\frac{530}{590}$ nm excitation/emission wavelengths (Synergy HT, BIO-TEK, Winooski, VT, USA). ANOVA was performed at a significance level of $p \leq 0.05.$ ## 2.12.3. Cell Viability Cell viability was determined after 48 h of incubation using a Live/Dead™ Viability/Cytotoxicity Kit (Invitrogen Inc., Grand Island, NY, USA). All HGs and CGs were incubated with PBS containing Calcein AM (2 µM, Sigma-Aldrich, Madrid, Spain) and ethidium homodimer (4 µM, Sigma-Aldrich, Madrid, Spain) at 37 °C for 30 min to stain live and dead cells, respectively. Gels were imaged with an inverted microscope (4-fold magnification, Nikon Eclipse TE 2000-S, Tokio, Japan) and analyzed using Image J software [38]. Treatments were carried out in triplicates, and five different images of each replicate were analyzed. The percentage of viable cells is given as stated in Equation [2]. ANOVA was performed at a significance level of $p \leq 0.05.$ [ 2]Viable cells%=viable cellstotal cells×100 ## 2.13.1. Nitric Oxide Production Lipopolysaccharide (LPS)-induced NO release was evaluated using a Griess reagent kit (Sigma-Aldrich, St. Louis, MO, USA). Briefly, after 24 h on top of the gels, cells were treated with LPS (500 ng/mL; from Escherichia coli O111:B4; CAS Number: 297-473-0, Aldrich) and incubated overnight under permissive conditions. Then, medium from each well was collected, and NO released by RAW264.7 was determined using a Griess test according to the manufacturer’s instructions. Briefly, 75 µL of collected medium from each sample was mixed with 25 µL of Griess reagent and incubated in the dark at RT for 15 min. Then, absorbance at 540 nm was measured by a microplate reader. Treatments were carried out using four replicates. LPS-stimulated cells seeded directly on the well plate were used as a control, taking this result as the $100\%$ NO production (Equation [3]). ANOVA was performed at a significance level of $p \leq 0.05.$ [ 3]NO released%=NO released (LPS)−activated cells (hydrogels)NO released (LPS)−activated cells (well plate)×100 ## 2.13.2. Macrophages Spreading and Multinucleated Cells Evaluation by Fluorescence Microscopy HG and CG effect on RAW264.7 macrophage spreading and multinucleated cell formation after 48 h of incubation was investigated by fluorescence microscopy of actin filaments and nuclei. Macrophages attached to the surface, in the presence or absence of LPS (500 ng/mL), were fixed for 30 min with $37\%$ (V:V) paraformaldehyde (Sigma-Aldirch, Madrid, Spain) in distilled water. This was followed by permeabilization with $0.05\%$ (V:V) Triton X-100 (Sigma-Aldirch, Madrid, Spain) and washing with distilled water. Actin filaments and nuclei were stained with 10 ng/mL rhodamine phalloidin (red) (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) diluted 1:1000 with PBS, and Hoechst 33342 fluorescent dye (blue) (Invitrogen, Thermo Fisher Scientific, 2161855, Waltham, MA, USA) diluted 1:100 with PBS, respectively, for 30 min at RT. After repeated washing steps with distilled water, samples were incubated with 200 µL of Tween 20 ($10\%$w) for 5 min, washed with distilled water, and examined using an inverted microscope (20-fold magnification, Nikon Eclipse TE 2000-S). The macrophage surface area was quantified in µm2 using Image J software [38]. For statistical purposes, samples were evaluated in duplicates, 5–10 photos were taken, and the area of 20–50 cells was measured per sample. ## 2.13.3. ELISA for Anti- and Pro-Inflammatory Markers To assess the anti-inflammatory effect of 10HA and 10HA 120NP HGs further, ELISA assays were performed to quantify the release of six pro-inflammatory mediators by LPS-stimulated RAW264.7. Mouse TNF-α, IL-6, IL-10, IL-12p40, IL-23, and PGE2 ELISA kits were purchased from abcam (ab208348, ab222503, ab255729, ab236717, ab119545, and ab133021, Cambridge UK). In brief, cells were seeded on top of the HGs and CGs at a density of 2 × 106 cells/well and cultured for 24 h. Then, cells were exposed to medium containing LPS (500 ng/mL) and incubated overnight. Media were collected and stored at −20 °C until use. Levels of mouse TNF-α, IL-6, IL-10, IL-12p40, IL-23, and PGE2 in cell culture supernatants were determined by the corresponding ELISA kit according to the protocol recommended by the manufacturer. Experiments were performed using six replicates per formulation. ANOVA was performed at significance levels of $p \leq 0.05$, $p \leq 0.01$, and $p \leq 0.001.$ ## 2.14.1. Extract Collection from Hydrogels Cell proliferation and NO production were also assessed using indirect assays. Here, 10HA, 10HA 40NP, 30HA, 30HA 40NP, cryo 10HA, and cryo 10HA 40NP HGs were placed in Eppendorf tubes with 3 mL of complete RAW264.7 culture medium and kept at 37 °C under shaking. After 1, 2, 7, and 14 days, extracts were collected (3 mL) and stored at −80 °C. The volume of each tube was refilled with fresh medium. Three replicates were used per HG. ## 2.14.2. Indirect Cell Proliferation Assay RAW264.7 proliferation, when exposed to the extracts, was performed through an indirect test using the AlamarBlue® reagent. First, RAW264.7 cells were seeded in 96-well plates at a concentration of 2 × 105 cells/mL and incubated for 24 h at 37 °C and $5\%$ CO2. Then, the medium was removed, and 100 μL of the previous extract was added to each well and incubated overnight. Finally, the extracts were removed, and 100 μL of AlamarBlue® reagent at $10\%$ (V/V) in medium without phenol red were added per well and incubated for 3 h. The fluorescence intensity of reduced AlamarBlue® was determined at $\frac{530}{590}$ nm excitation/emission wavelengths. ANOVA was performed at a significance level of $p \leq 0.05.$ ## 2.14.3. Indirect Nitric Oxide (NO) Assay LPS-induced NO release was evaluated using a Griess reagent kit. In brief, cells were seeded into 96-wellplates at a concentration of 2 × 106 cells/mL and incubated for 24 h at 37 °C and $5\%$ CO2. Then, the medium was removed and 100 μL of the gel extracts and LPS (500 ng/mL) were added to each well and incubated overnight. The medium from each well was collected and the NO released was determined using a Griess test. Briefly, 75 µL of collected medium from each sample was mixed with 25 µL of Griess reagent and incubated in the dark at RT for 15 min. Then, absorbance at 540 nm was measured by a microplate reader. Treatments were carried out using four replicates. LPS-stimulated cells without extract exposure were used as a control. ANOVA was performed at a significance level of $p \leq 0.05.$ ## 2.15. Statistical Analysis The results are given as mean ± SD if not otherwise stated. One- or two-way analysis of variance (ANOVA) with additional Tukey’s multiple comparison tests, one sample, and unpaired t-test were considered significant for p values < 0.05. For statistics of the NP release experiment with an uneven number of samples, Mood’s median test was performed at a significance level of $p \leq 0.05.$ In biological assays, one-way ANOVA between controls was labeled with * $p \leq 0.05$, $p \leq 0.01$, * $p \leq 0.001$, and between samples with # $p \leq 0.05.$ ## 3.1. Hydrodynamic Characterization of Ketoprofen NP The synthesis of the copolymer poly(HKT-co-VI) was successful and was confirmed by 1H-NMR. KT NPs were successfully fabricated owing to the appropriate hydrophobic–hydrophilic balance of the copolymer poly(HKT-co-VI) that allows its self-assembly by the nanoprecipitation method [34]. As a consequence, NPs consist of a hydrophobic core made of covalently linked KT and a hydrophilic shell based on VI. NPs showed unimodal size distribution via light scattering, with a polydispersity index (PDI) below 0.1, a mean hydrodynamic diameter (Dh) of 161 nm, and a positive surface charge of +30 mV (Figure 3A). These results are in agreement with the ones obtained in previous work, where the suitability of these hydrodynamic properties for macrophage internalization was demonstrated [34]. ## 3.2. Binding and Release of Ketoprofen NP from HA/Coll Hydro- and Cryogels Controlling the NP concentration in the different HG types is necessary for studying dose-dependent effects. To determine the concentration of NPs needed to achieve a particular loading level, loading studies were performed via soaking with a 1 mg/mL NP solution (max NP) and incubating in PBS at 37 °C for one and seven days. Experiments revealed no significant differences in NP concentration between variants and time points (Figure 3B). However, there is a clear tendency for a lower NP content in 30HA HGs compared to cryo 10HA gels after one and seven days (~50 µg NP/gel compared to ~100 µg/gel). The NP concentration in the gels was determined after sample digestion with hyaluronidase (HYAL; 37 °C, pH 5.35). While digestion of 10HA and 30HA HGs was completed in two to six days, CGs could not be completely digested within this period. This means that the NP amount regarding the CGs cannot be accurately determined. Thus, there could be more NPs in the CGs than are actually shown in Figure 3B,D. The denser HA network in 30HA resulted in a prolonged digestion time by the enzyme compared to the 10HA HG. However, the incomplete digestion of the cryo 10HA samples within the analyzed time suggests a structural difference. Since the SEM images did not reveal a substantial difference between 10HA and cryo 10HA samples on the microscopic scale, the structural difference might be found on the molecular scale (Figure 5 and Figure S3). This might be due to the cryoconcentration effect. Generally, the freezing of the solvent led to the increased concentration of the precursor and the photoinitiator, resulting in denser pore walls and possibly a higher degree of crosslinking [39,40]. Additionally, the cryoconcentration could increase the physical entanglement of HA chains resulting in a stronger resistance against HYAL, as shown by Cai et al. in vitro and in vivo, comparing HA HGs made by a cryo-procedure with non-cryogenic HA HGs [41,42]. In line with the direct determination of the NP content in the gels, the NP release, determined in the supernatants over seven days, suggested a strong binding of the NPs with almost no release after one day in PBS. While there was some release from 10HA and 30HA HGs after seven days, there was none from cryo 10HA over the investigated period (Figure 3C). ## 3.3. Controlled Loading of Hydro- and Cryogels with NP In order to determine the most suitable NP concentration to be introduced into the HGs for a therapeutic effect, previous findings from Espinosa-Cano et al. were taken into account [34]. Here, NP concentrations ranging from 11 to 125 µg/mL significantly reduced NO production by LPS-stimulated RAW264.7. Consequently, 40 or 120 µg of NPs were added per HG. Figure 3D shows that the target concentration could be achieved for 30HA 40NP and 10HA 120NP HGs. However, 10HA 40NP, CL-10HA 40NP, and cryo 10HA 40NP HGs presented 23.8 ± 1.6, 11.8 ± 0.2, and 1.0 ± 0.5 µg NP/HG, respectively, resulting in statistically significant differences between the target concentration of 40 µg/HG and the obtained NP concentration. Nonetheless, the findings for loaded 10HA HG (40NP vs. 120NP) indicate that it is possible to control NP concentration in the HGs by choice of NP incubation concentration. For CL-10HA 40NP, it was assumed that all NPs were bound tightly in the organic matrix of the HGs and were not lost during the preparation procedure. However, the coumarin-6 (C6) bound to the NPs might have been destroyed during the photo-crosslinking procedure. As a result, lower fluorescence signals were detected, leading to a lower amount of calculated NPs. The very low amount of NPs found in the cryo 10HA 40NP samples might be related to the incomplete digestion of the CGs not releasing the NPs, or to the CG scaffold itself, holding back the fluorescence dye even after extraction with ethanol (Figure S1). ## 3.4. NP Distribution in Hydro- and Cryogels Furthermore, CLSM (fluorescent C6-loaded NPs) and SEM were used to study the NP distribution in the HGs (Figure 4 and Figure 5). HGs without NPs (10HA, 30HA, and cryo 10HA) showed no fluorescence in CLSM or NPs in SEM (Figure 4A,G and Figure S2). The HGs loaded via soaking (10HA 40NP, 10HA 120NP, and 30HA 40NP) displayed NPs only on their surface, as observed with CLSM and SEM alike (Figure 4H,I,K, and Figure 5A,B,D). In contrast, the CL-10HA 40NP sample also displayed NPs in zones of at least 100 µm below the surface (Figure 4J). In SEM, however, the NPs were rarely visible on the surface but were rather embedded in the polymeric matrix due to the subsequent mixing of all components before crosslinking (Figure 5C,H). A similar distribution could be seen for the cryo 10HA 40NP sample, which is loaded via soaking. In this case, NP distribution in CLSM also reaches zones that are at least 100 µm below the surface. SEM showed NPs in the cross-section, demonstrating an open and interconnected porous structure where NPs can easily diffuse into the CGs (Figure 4L and Figure 5J). The large amount of NPs found via CLSM within cryo 10HA 40NP was in contrast to the determined NP content in the same samples, with only 1.0 ± 0.5 µg NP per gel (Figure 3D). These results confirm the aforementioned challenges in correctly determining NPs in CGs due to an incomplete HYAL digestion and ethanol extraction (see Section 3.3). ## 3.5. Morphology and Mechanical Properties of Hydro- and Cryogels SEM images of the top view of all HGs showed a patterned but closed surface, while CGs displayed several open pores (Figure 5 and Figure S4). The cross-section of the freeze-dried gels revealed many pores, mostly smaller than 100 µm, and CG sample heights were higher in SEM than for HGs (Figure S4). Some of the HGs containing NPs shrank significantly during freeze-drying (Figure S4). However, there was no difference between the HG heights after swelling (Figure 6A). Similarly, freeze-dried CGs with NPs also displayed a decreased height in SEM compared to those without NPs. The loss in height after freeze drying can be attributed to the influence of salt residues from PBS and NPs, shielding the charge of carboxylic groups, allowing HA chains to move closer together. After swelling, the cryo 10HA samples were significantly higher than all other samples and the cryo 10HA 40NP samples were significantly higher than the 30HA 40NP samples, further highlighting the structural difference between CGs and HGs (Figure 6A). However, for the CGs, the NPs had a detrimental effect on the sample height, even in the swollen state. The elastic moduli of all HGs were lower than 30 kPa, which ranks the HGs in the range of soft cutaneous tissue (Figure 6B) [43,44]. The highest elastic moduli, with around 20 kPa, were found for the 30HA and 30HA 40NP HGs, followed by the 10HA HG with 2.0–3.9 kPa, which is in line with previous results for the same type of HG [30,32]. The lowest elastic modulus was found for the CGs with 0.5 kPa. Loading the gels with NPs did not significantly influence the elastic modulus for any HG variant. The CGs were expected to have at least an elastic modulus in the range of the 10HA gel, due to the cryoconcentration effect before crosslinking [39]. To investigate the contradiction of the CG properties compared to those of the HGs—higher stability towards HYAL, but lower elastic modulus—the porosity of the 10HA and cryo 10HA gels was determined (Figure 6C). At the same mass, the CGs have a significantly higher porosity of 89.7+/−$5.7\%$ than the HGs, with 73.6+/−$3.9\%$. Due to this, CGs generally have a lower material density, e.g., thinner pore walls, and, thus, a lower elastic modulus. On the other hand, the cryoconcentration increases the entanglement of the polymer chains and possibly the crosslinking, therefore, reducing the digestibility of the CGs by HYAL [41,42]. Figure 5: SEM images of HG and CG scaffolds after fabrication with NPs. (A–E) (magnification 40,000×): top view and (F–J) (magnification 20,000×): cross-section. The white arrows indicate NPs. Scale bar: 2 µm. Figure 6: Gel height after swelling (A), elastic modulus (B), and porosity of HGs and CGs (C). (A,B) are measured on 3 mm punches of 50 µL disc-shaped gels after swelling in PBS at room temperature. (C) is determined on 200 µL cylindrical gels in PBS at room temperature. One-way ANOVA (A,B) and unpaired t-test (C): statistically significant for p < 0.05, statistically significant difference: # against all 10HA HGs and CGs, + against all gels, ++ against 30HA 40NP and cryo 10HA, n = 3.* ## 3.6. Proliferation and Viability of a Macrophage Cell Line The proliferation of RAW264.7 on the HGs was studied through the assessment of the cell metabolic activity. As shown in Figure 7A, no significant differences were observed for NP-loaded HGs. Compared to 24 h, a significant increase ($p \leq 0.05$) in cell number was observed after 48 h for all gels. Moreover, a higher cell number was observed for CGs (cryo 10HA and cryo 10HA40NP) compared to HGs. This increased proliferation in the CGs can be related to their open pore structure that can promote cell growth and attachment to the gels (Figure S3, see I–K compared to A–H). On the other hand, RAW264.7 proliferation was unchanged compared to control samples when treated with the HG extracts, demonstrating the biocompatibility of the supernatants for the cells (Figure S6). Cell viability was evaluated by visualizing the presence of living and dead cells on gels after 48 h (Figure 7B). The quantitative analysis revealed no significant differences between unloaded and NP-loaded HGs, confirming that the introduction of the NPs in the HGs did not compromise the well-known biocompatibility of HA and coll [45,46,47]. Additionally, representative fluorescent microscopy images (Figure S5), showed the sparse appearance of dead compared to living RAW264.7 cells on top of the gels. ## 3.7. Anti-Inflammatory Effect Macrophages are key effectors in response to external material implantation, known as the foreign body reaction (FBR). Their direct contact with the material surface can induce the secretion of pro-inflammatory mediators. An extended unresolved inflammation then leads to the fusion of macrophages into foreign body giant cells (FBGCs) to phagocytose the material, inducing the recruitment of fibroblasts for fibrous encapsulation and scaffold failure [48,49]. During the initial phase of this FBR, pro-inflammatory M1-type macrophages lead to acute reactions to the implanted material, while anti-inflammatory M2-type macrophages control the resolution of inflammation and induce the subsequent healing stage [50]. In order to assess the presence of FBGC on the surface of the gels, the actin cytoskeleton and cell nuclei were visualized after 48 h of cell incubation, obtaining fluorescent images and quantitative measurements of macrophage surface area (Figure 8). In general, macrophages were predominantly round-shaped. However, HGs without NPs (30HA and 10HA) presented some multinucleated cells displaying a higher degree of spreading, and some were elongated with a spindle-shaped morphology. This morphology corresponds to activated pro-inflammatory M1-type macrophages. However, when NPs were loaded into the HGs, lesser multinucleated FBGC were observed, and smaller cell surface areas were measured (10HA 40NP, 10HA 120NP, and 30HA 40NP). For CL-10HA 40NP, this effect was slightly diminished. Importantly, CGs with and without NPs (e.g., cryo 10HA 40NP and cryo 10HA) showed a reduced number of FBGCs compared to HGs. During inflammation, multiple cellular inflammatory mediators, such as cytokines and chemokines, are produced by both immune and resident cells, creating a complex network of biochemical factors. These factors represent an important therapeutic target in the management of inflammatory diseases. In this sense, the anti-inflammatory effect of gels in LPS-stressed macrophages was evaluated by quantifying the release of representative inflammation-related factors when macrophages were seeded on the top of the gels. Several studies have shown that bacterial LPS induces macrophage polarization into a pro-inflammatory M1-type phenotype via binding to cellular Toll-like receptors. This binding leads to the activation of NF-κB signaling pathways, stimulating the release of pro-inflammatory mediators, such as NO, IL-1β, IL-6, and TNF-α [51]. Here, the levels of NO were measured (Figure 9A). Unstimulated macrophages produce a basal NO amount of $10\%$ with respect to the LPS-stimulated group without any gel. The 10HA, CL-10HA 40NP, and cryo 10HA gels showed no changes in the NO production by macrophages compared to the control. Moreover, this factor was significantly increased ($p \leq 0.05$) for the 30HA HG. Macrophages experience phenotypic changes dependent on the molecular weight of HA; low molecular weight HA (<5 kDa) leads to a pro-inflammatory response, while high molecular weight HA (>800 kDa) leads to a pro-regenerating response [52,53]. The increment in NO production for 30 HA gels might be related to a higher release of low molecular weight HA fragments due to an increased HA concentration used for gel fabrication and subsequent cell-mediated enzymatic degradation. On the contrary, HGs containing NPs reduced the release of NO in all cases, except for CL-10HA 40NP. The highest reduction in NO production ($75\%$) was achieved for the 10HA 120NP gel, demonstrating a concentration-dependent effect. Given that the NPs in the CL-10HA 40NP samples are hidden below the surface (Figure 5C,H), this hinders the access to and internalization of NPs by cells, thus, reducing their efficacy. Results on NO release were in good agreement with findings on macrophage area. Whereas gels without NPs showed a larger area and a higher NO release, gels with direct access to the NPs displayed reduced values for both (Figure 8B and Figure 9A). Importantly, the reduced number of FBGC and lowered NO levels alike confirm that the anti-inflammatory effect of the NPs is preserved when they are included in the gels. Of note, for these effects, a direct cell–NP contact is necessary. However, treatment of the RAW264.7 cells with gel extracts did not modify the NO production (Figure S7), confirming the low release of NPs from the gels (Figure 3B). The situation in vivo might be different due to the possible enzymatic degradation of the gels by HYAL that could result in a release of the NPs, reducing NO production. In order to substantiate the anti-inflammatory effect of 10HA and 10HA 120NP HGs, with the latter achieving the strongest reduction in NO production, the release of different pro- and anti-inflammatory mediators (TNF-α, IL-6, IL-10, IL-12p40, IL-23, and PGE2) was analyzed by ELISA (Figure 9B). When RAW264.7 cells seeded on 10HA were stimulated with LPS, an overproduction of all of these factors was evident. Here, the following mediator concentrations were determined: 11800, 2500, 1700, 360, and 220 pg/mL for PGE2, TNF-α, IL-6, IL-10, and IL-12 p40, respectively. A significant reduction was achieved for all factors when NPs were present in the HG (10HA 120NP), with 2520, 1580, 1460, 310, and 38 pg/mL for the same mediators. The reduction in cellular NO, TNF-α, and IL-12p40 levels when RAW264.7 cells were in contact with NP-loaded HGs is in agreement with previous results obtained with KT-based NPs [34]. In this previous work, a reduction in NO production was observed after 24 and 48 h of NP exposure. Moreover, real-time PCR revealed IL12b gene repression after 1 and 7 days and Tnfa gene repression after 1 day due to cell exposure to the NPs. In the present study, a significant reduction was observed as well after 24 h of exposure (Figure 9A). Likewise, a significant decrease in both TNF-α and IL-12p40 levels after 24 h on NP-containing HGs was detected (Figure 9B). On the other hand, a reduced anti-inflammatory IL-10 production by RAW264.7 cells was observed, opposing previous results indicating an induced Il10 gene expression after 1 and 7 days of NP exposure [34]. In the present work, NPs are embedded in the HGs. Consequently, more sustained and controlled effects of the NPs are expected in comparison to the direct exposure of cells to the NPs. This could explain the decreased amount of IL-10 found here. Analogous to previous work, IL-23 cytokine levels were also determined. However, the cytokine levels were not high enough to be detectable by ELISA. Furthermore, 10HA 120NP gels induced a significant reduction for two other important pro-inflammatory factors, i.e., PGE2 ($p \leq 0.001$) and IL-6 ($p \leq 0.01$). NSAIDs, such as KT, exert their activity mainly by inhibiting the action of COX enzymes involved in the biosynthesis of PG and thromboxane from arachidonic acid. PGE2 is one of the most abundant PG produced in the body, and its dysregulation has an important role in chronic inflammation [54]. In accordance with the KT mechanisms of action, PGE2 was the factor most significantly overexpressed by the LPS stimulus and reduced by the presence of the NPs in the HGs. In summary, these findings demonstrate the NPs’ suitability in enhancing the anti-inflammatory properties of HA/coll-based gels and, thus, the composite’s potential to act as an anti-inflammatory wound dressing. NP concentrations and loading technique for NP incorporation significantly influenced the efficacy of NPs, with higher NP concentrations being more effective. Importantly, direct contact of the cells with the NPs on the gel surface was mandatory for the effect. We recognize that our study has potential limitations, such as using a macrophage cell-line instead of primary cells, which should be additionally investigated in future studies. In order to enable a comparison with commercially available wound dressings, further studies should also consider analyzing NP-modified versions of those. ## 4. Conclusions In this study, different HA/coll-based HGs and CGs containing KT NPs were designed, which displayed preparation-dependent NP distribution, surface topography, and elastic moduli. All gels that allowed direct contact of the cells with the NPs on their surface showed a reduction in the pro-inflammatory marker NO, while maintaining high cell viability and proliferation. In addition, by directly comparing 10HA 40NP and 10HA 120NP HG, concentration-dependent cellular effects of NPs were demonstrated. The 10HA 120NP gels also markedly reduced cell-related production of the pro-inflammatory markers PGE2 (to $21\%$), IL-12 p40 (to $17\%$), TNF-alpha (to $63\%$), and IL-6 (to $84\%$) in inflammatory conditions. The presented in vitro findings on HA/coll-based gels containing KT NPs demonstrate their potential for reducing pro-inflammatory macrophage polarization. This could provide a promising asset in treating chronic wounds via the immune-centered approach, in particular when combined with other anti-inflammatory agents, such as sHA. The in vivo relevance of these findings should be addressed in future studies utilizing an animal model for chronic skin wounds. ## References 1. Wicke C., Bachinger A., Coerper S., Beckert S., Witte M.B., Königsrainer A.. 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--- title: 'Presence of Differences in the Radiofrequency Parameters Applied to Complex Pressure Ulcers: A Secondary Analysis' authors: - Miguel Ángel Barbas-Monjo - Eleuterio A. Sánchez-Romero - Jorge Hugo Villafañe - Lidia Martínez-Rolando - Jara Velasco García Cuevas - Juan Nicolás Cuenca-Zaldivar journal: Medicina year: 2023 pmcid: PMC10059019 doi: 10.3390/medicina59030516 license: CC BY 4.0 --- # Presence of Differences in the Radiofrequency Parameters Applied to Complex Pressure Ulcers: A Secondary Analysis ## Abstract Background: Pressure ulcers are a public health problem given the impact that they have on morbidity, mortality and the quality of life and participation of patients who suffer from them. Therefore, the main objective of this study was to evaluate the presence of differences in the radiofrequency parameters applied to complex pressure ulcers throughout the sessions and between the right and left leg. As a secondary objective, the subjective perceptions of the effects of the treatment by both the patients and the practitioner were analyzed. Methods: We performed a secondary analysis of data from a prospective study involving 36 patients from the Hospital de Guadarrama in Madrid, Spain, who presented ulcers in the lower limbs. Ten treatment sessions of radiofrequency were administered with a frequency of one session/week, collecting the data referring to the variables in each of the sessions. The main outcome variables were the radiofrequency parameters automatically adjusted in each session and that referred to the frequency (Hz), maximum and average power (W), absorbed energy by the ulcer (J/cm2) and temperature (°C) reached by the tissues. On the other hand, the subjective perception of the results was evaluated using the Global Response Assessment (GRA), a Likert-type scale that scores the treatment results from 1 (significantly worse) to 5 (significantly better). Likewise, the satisfaction of both the patients and the professional were evaluated using a 10-point numerical scale. Results: The ANOVA test showed significant differences ($p \leq 0.05$) throughout the sessions except in patient satisfaction. The ANOVA test showed significant differences ($p \leq 0.05$) between both legs and over time in all parameters except for frequency. The presence of significant differences ($p \leq 0.05$) was observed over time between legs compared to the initial values in the absorbed energy and in temperature, with higher final values in the absorbed energy in the left leg compared to the right (26.31 ± 3.75 W vs. 17.36 ± 5.66 W) and a moderate effect on both (R2 = 0.471 and 0.492, respectively). The near absence of changes in the satisfaction of both the patients and the professional was observed, while the score in the GRA decreased continuously throughout the sessions. Conclusions: Radiofrequency parameters are indicative of an improved clinical response to ulcers. In addition, higher radiofrequency exposure increases healing capacity. However, the subjective perception of treatment outcomes worsened, which may be related to the chronic nature of the ulcers, leading to patients’ expectations not being met. ## 1. Introduction Pressure ulcers are a public health problem given the impact that they have on morbidity, mortality and the quality of life and participation of patients who suffer with them [1]. The prevalence in Spain is around $7.9\%$ in adults, whereby $65.6\%$ of which are of nosocomial origin; in the United States, they are suffered by some 2.5 million individuals, with percentages ranging between $5\%$ and $15\%$ [1,2]. The classification of these injuries is based on tissue damage from level I with superficial red areas to level IV with significant skin damage that may involve bone, tendon or joint capsule [3]. These hospital-acquired pressure injuries (HAPIs) can lead to chronic wounds, contractures, osteomyelitis, loss of limbs and sepsis, and cause about 60,000 deaths per year [2]. The annual cost of this type of injury is between USD 3.3 billion and USD 11 billion per year and can be as high as USD 26.8 billion in the most advanced stages of HAPI, making the cost per patient about USD 10,708, and each hospital episode costs between USD 500 and more than USD 70,000 in the United States [2]. In diabetic patients, the prevalence of distal ulcers in the lower limbs is between $19\%$ and $34\%$, being one of the main complications of this pathology. These lesions account for one third of the diabetic patient’s expenses, reaching a total annual expenditure of USD 176 billion; however, despite this high cost, $20\%$ of patients continue to have ulcers after one year of treatment [4]. Given the impact on people’s lives and the cost that pressure ulcers and their complications represent for the healthcare system, prevention should be the most efficient method for dealing with them [1], considering taking measures to address risk factors such as limited movement, the elderly and prolonged embedding [5]. However, the high prevalence makes it necessary to develop and implement treatment methods that limit the process by accelerating recovery and avoiding the appearance of the complications. In healthy subjects without affectation of the sensory, motor and mental areas, the maintenance of static positions leads to posture modification; however, this does not happen in those patients with alteration of any of the mentioned spheres, causing pressures higher than the filling pressure of the arterial capillaries and higher than the outflow pressure of the venous capillaries to produce tissue hypoxia, resulting in ischemia, tissue damage and subsequent necrosis [6,7]. These lesions can take decades to heal or even fail to heal, which can have an impact on people’s lives, leading to the appearance of secondary diseases such as depression or family distress [8]; however, there are no studies on electrotherapy that analyze factors such as quality of life, depression or the perceived effectiveness of the treatment [3]. Although, it has been evidenced that patients understand that the improvement in the lesion is due to a collaborative approach where they feel more knowledgeable and empowered with tools to improve ulcer care [9]. The use of electrotherapy to address these lesions has been widely studied, especially using electrical stimulation with involvement in the four phases of healing (inflammatory, proliferative, epithelialization and remodeling phase); although the mechanism of action is not well understood, the evidence suggests that this practice increases the flow of blood and thus that of cells, promotes oxygenation, reduces edema and influences dermal growth factors and their receptors [3,10]. Although not as widely studied, radiofrequency has also been used as part of the treatment of HAPI; it began to be used in 1950 and continues to be used today with the aim of improving the remodeling of the injured tissue without causing damage to the surrounding healthy tissue [11]. According to the literature related to the use of radiofrequency in the treatment of chronic pressure ulcers, several studies reflect the use of pulsed radiofrequency as part of the multimodal treatment of these difficult lesions [10,12,13]. These show that this type of treatment, being non-invasive, relatively inexpensive, easy and safe to use and with good patient acceptance is an interesting tool to use as an adjuvant treatment [10]. In relation to multimodal therapy, radiofrequency is combined both with conventional therapy (care appropriate to the lesion) and with negative pressure devices and/or dermal replacement [10,12,13]. The evidence shows the usefulness of pulsed radiofrequency as part of the intervention, achieving progressive healing and thus avoiding amputation of the affected limb [12,13]. Other authors mention a variant of pulsed radiofrequency called pulse dose radiofrequency, where the constant is determined by the voltage and not by the time, as in pulsed radiofrequency, which ensures that the tissue temperature is maintained at 42 °C and allows standardizing a treatment method in relation to the dose and not the exposure time, where preliminary results in small samples show a better effectiveness in reducing pain and maintaining the results achieved [14]. Tecartherapy, included in this group, consists of endogenous thermotherapy using electric current through monopolar capacitive and resistive radiofrequency with the aim of producing heat in the most superficial tissues (capacitive electrode) and in the deepest ones (resistive electrode) [11]. The heat produced in the tissues generates a tissue damage that stimulates fibroblasts and growth factors favoring the production and remodeling of collagen and elastin and the deposition of hyaluronic acid de novo, obtaining as a final result a thickening of the subcutaneous tissue layer that avoids necrosis, fibrosis and damage to vascular and adnexal structures [15]. The main objective of this study was to evaluate the presence of differences between the radiofrequency parameters applied to complex pressure ulcers throughout the sessions and between the right and left leg. As a secondary objective, the subjective perception of the effects of the treatment by both the patients and the practitioner was analyzed. ## 2.1. Study Design We performed a secondary analysis of data from a prospective study. The previous study aimed to evaluate the effect that the application of radiofrequency at low intensity (frequency) and with non-thermal effects has on the different components of the mechanism of the healing process of hard-to-heal lesions. The methods and description of the study have been previously described [16]. The current study was approved by the Clinical Research Ethics Committee of the Puerta de Hierro Hospital, Madrid, Spain (approval number: 02.18, 6 February 2018). All patients provided informed consent prior to their enrollment. The most relevant parts of the design are summarized below. ## 2.2. Study Population The study included 36 patients from the Hospital de Guadarrama in Madrid, Spain, who presented ulcers in the lower limbs considering the following aspects of their case histories: age, height and weight, and 13 men and 10 women had diabetes mellitus. These patients came directly from the hospital admission service for ulcer consultation, where they were evaluated by a geriatrician with 20 years of experience (J.V.G.C.). The research team took into account the following inclusion criteria: male or female over or equal to 18 years old or under or equal to 90 years old with a diagnosis of a long-lasting complex wound, that admission was the first one for treatment at Hospital de Guadarrama and that the patient understood and voluntarily signed the corresponding informed consent sheet and information sheet prior to the performance of any evaluation or procedure related to the study. Patients with the following comorbidities were excluded from the study: cardiac pacemaker wearers, presence of local metallic implants, lesion infection, patients with cognitive impairment and patients with malnutrition or risk of malnutrition. ## 2.3. Outcome Measures The main outcome variables were the radiofrequency parameters automatically adjusted in each session and that referred to the frequency (Hz), maximum and average power (W), absorbed energy by the ulcer (J/cm2) and temperature (ºC) reached by the tissues. On the other hand, the subjective perception of the results was evaluated using the Global Response Assessment (GRA), a Likert-type scale that scores the treatment results from 1 (significantly worse) to 5 (significantly better) [11,17]. Likewise, the satisfaction of both the patients and the professional were evaluated using a 10-point numerical scale. Ten treatment sessions were administered with a frequency of one session/week, with all outcome measures measured at each treatment session. ## 2.4. Intervention Treatment was administered by M.A.B.M., a nurse specialist with 30 years of experience in ulcer treatment, using the CAPENERGY Vascular C200 (CE120) tecartherapy device with a C-Boot foot probe in the case of lesions on the sole of the foot, or with capacitive plates in the rest of the body areas. A total of 10 radiofrequency sessions were applied in the 36 patients with a periodicity of once a week, with a power of $60\%$ and a frequency of 1.2 MHz for 30 min, placing the treatment head on the lesion, and an athermal dose of up to 37 °C was administered (Figure 1). ## 2.5. Statistical Analysis Statistical analysis was performed using the program R Ver. 3.5.1 (R Foundation for Statistical Computing, Institute for Statistics and Mathematics, Welthandelsplatz 1, 1020 Vienna, Austria). The significance level was set at $p \leq 0.05.$ The distribution of quantitative variables was tested using the Shapiro–Wilk test which evidenced the absence of normality. Qualitative variables were described in absolute values and frequencies and quantitative variables were described using mean and standard deviation. Given that this is a single-group observational study, the sample size was not calculated a priori, but included patients who attended the ulcer consultation at Hospital Guadarrama (after signing the informed consent and meeting the eligibility criteria) during the period from September 2018 to June 2019. The final power of the study was calculated using the program R Ver. 3.5.1 (R Foundation for Statistical Computing, Institute for Statistics and Mathematics, Welthandelsplatz 1, 1020 Vienna, Austria), applying the Wilcoxon signed-rank test with Bonferroni correction with the PUSH scale scores between the first and last session. Changes over the sessions in subjective perception and radiofrequency parameters were analyzed and, in the case of radiofrequency parameters, the differences between the right and left legs over the sessions were also analyzed. In both cases, a repeated measures linear mixed model and restricted maximum likelihood (REML) and unstructured correlation (default) structure were used. The subjects were modeled according to random effect and time in the first case, or the group (leg): time interaction in the second as fixed effects, adjusting in the latter case the results with the baseline values. Due to the small sample size, the Kenward–Roger degrees of freedom correction was applied and confidence intervals were calculated via bootstrap. The Nakagawa and Schielzeth R2 was calculated for each model as a goodness-of-fit measure. Post hoc matched pair comparisons were applied using the Bonferroni correction. ## 3. Power Analysis Accepting a risk α of 0.05, the final power of the study was estimated at $100\%$ with a final mean PUSH score of 10.695 at the first session and 4.695 at the ending treatment session. ## 4. Results The sample was composed of 36 subjects of 63.31 ± 9.99 years, with a majority of women ($58.3\%$) and with risk factors such as diabetes mellitus ($66.7\%$), dyslipidemia ($72.2\%$) or high blood pressure ($75.0\%$) (Table 1). The recruited patients presented pressure ulcers with an average surface of 25 cm2 grade III-IV with an evolution time of approximately 2 months with venous vascular lesions in women and arterial lesions in men. ## 4.1. Comparisons across Sessions The ANOVA test showed significant differences ($p \leq 0.05$) throughout the sessions, except in patient satisfaction. It was verified that the presence of systematic differences between practically all of the measurement moments compared with the initial values and specifically between the final values and the initial ones, except in the satisfaction of the patients and the professional and in the frequency in the left leg ($p \leq 0.05$) (Table 2 and Supplementary Material Table S1). These differences were translated into a final increase in the values of the radio frequency parameters in both legs and a decrease in the Global Response Assessment score with very high effects on the latter (R2 = 0.874) and being greater than 0.5 in the parameters of the left leg (Supplementary Material Table S2). The pairwise comparisons showed systematic differences between practically all of the measurement moments, with significant differences being observed in all of the variables between the first and the last session ($p \leq 0.05$), except in the satisfaction of the patients and the professional (Supplementary Material Table S3). ## 4.2. Comparison of Radiofrequency Parameters between Both Legs The ANOVA test showed significant differences ($p \leq 0.05$) between both legs and over time in all parameters except for frequency. The presence of significant differences ($p \leq 0.05$) was observed over time between legs compared to the initial values in the absorbed energy and in temperature, with higher final values in the absorbed energy in the left leg compared to the right (26.31 ± 3.75 W vs. 17.36 ± 5.66 W) and a moderate effect on both (R2 = 0.471 and 0.492, respectively) (Table 3 and Supplementary Material Table S4). Pairwise comparisons showed differences in absorbed energy between both legs at the end, with no initial significant differences ($$p \leq 0.049$$), while significant differences in temperature occurred in the first treatment sessions (Supplementary Material Table S5). All radiofrequency parameters were found to increase progressively throughout the sessions and more markedly in the left leg, especially with regard to the absorbed energy where the confidence intervals barely overlapped (Figure 2). ## 4.3. Satisfaction of the Patients and the Professional A near absence of changes in the satisfaction of both the patients and the professional was observed, while the score in the Global Response Assessment decreased continuously throughout the sessions (Figure 3). ## 5. Discussion The results of the present study show that an increase in the radiofrequency parameters, including temperature and especially the absorbed energy, especially in the left leg, are indicative of an improvement in the clinical response of the ulcers. Furthermore, a greater exposure to radiofrequency increases the healing power [18,19,20]. It is important to detail that no relevant influences were found with respect to the differences in the results influenced by clinical variables and by sex or any other sociodemographic variables. These results also agree with the previous study [16] in which there was an average increase in temperature by thermography of 1.4 °C, as well as a healing rate percentage of $60\%$ with a progressive reduction in size and exudate of the ulcer measured using the Pressure Ulcer Scale for Healing (PUSH). However, it has not been possible to establish the reason as to why the clinical response of the ulcers in the left leg was better than in the right leg and there are no other studies that have studied the differences between a lower limb and the contralateral limb using tecartherapy. In addition, a review in other fields of electrotherapy such as electrostimulation concluded that there is no consensus on parameters such as frequency, duration and location of treatment [3]. Future studies are therefore needed to study the appropriate dose and whether the differences between one limb and another may be due to tissue factors. Likewise, for the subjective perception of the results by the patient (GRA), the scores were always higher in patients with dyslipidemia or arterial hypertension compared to those without. In the case of professional satisfaction, patients with renal failure reported higher scores than those without this pathology. We cannot establish hypotheses regarding these results for the moment, on the one hand due to the low sample size of the present study, and on the other hand due to the lack of studies on which to discuss these results. This is because, to the knowledge of the authors of the present study, this is the first time that such comparisons have been made using radiofrequency. This could certainly be a line of research, or at least parameters to be analyzed in future studies. To our knowledge, this is the first study that uses this type of therapy to address pressure ulcers and assesses parameters of subjective perception of outcomes as well as patient and professional satisfaction. A Cochrane review about electrical stimulation for the treating of pressure ulcers exposes the absence of studies evaluating parameters such as quality of life, depression or perception of treatment effectiveness, despite these being relevant outcomes for patients [3]. In this study, the subjective perception of the results of the treatment measured with the GRA scale worsened, which may be related to the chronic nature of the ulcers and the fact that they did not disappear completely and perhaps did not respond to the expectations of the patients. In this regard, Wood et al. [ 9], in a study on the collaborative management of pressure ulcers, concluded that patients felt that pressure ulcer care improved by using a collaborative, multidisciplinary approach because they felt more knowledgeable, empowered and more able to improve their pressure ulcer care. This issue was approached from a qualitative perspective by García Sánchez et al. [ 21], concluding that proximity, trust and effective and bidirectional communication between patients and health professionals are fundamental. Due to a scarcity of studies assessing factors as relevant to the patient as those described above and considering the importance of the patient’s perception in the treatment, future studies concerning these aspects are necessary. In this sense, Ballestra et al. [ 22] showed that certain patient expectations, such as the expectation of a tailored treatment with frequent follow-ups, the hope of obtaining the best possible results, realism or resignation regarding the alleviation of the health problem, good dialogue and communication, the need to be seen and confirmed as an individual and the desire to receive an explanation of their disease, could be related to better recovery results. However, it appears that the induction of different types of expectations (positive or negative) through verbal suggestion does not influence the perception of acute pain perceived during the performance of a technique that may be painful [23]. ## Limitations An important limitation of this study is the small sample size. Additionally important is the absence of a control group or a placebo group to compare with the evolution of the process or with other interventions. The authors also recognize as a limitation the fact that they did not measure the psychological and behavioral factors of the sample analyzed in the study, which is observed as a determinant in different chronic diseases [24,25]. Although there is an inherent bias in the type of research model, this has been minimized by using relevant and reliable human (accredited clinical experience of the researchers) and instrumental resources. ## 6. Conclusions It was observed that the radiofrequency parameters increased progressively throughout the sessions and more markedly in the left leg, but for the difference between legs it was not possible to establish the reason for this clinical response. This increase was indicative of an improvement in the clinical response to ulcers. In addition, higher radiofrequency exposure increases healing capacity. However, the subjective perception of treatment outcomes worsened, which may be related to the chronic nature of the ulcers, leading to patients’ expectations not being met. ## 7. Key Points In summary, considering the great clinical potential of radiofrequency, we can expect an increase in new techniques for tissue regeneration and wound healing in the near future. The increased power to accelerate the wound healing process can be explained by the anti-inflammatory effect caused by the changes that occur in the perilesional skin, and the improvement in microcirculation contributes to the increase in the reactivity of the different layers of the skin. The influence of the magnetic field on the microcirculatory system can be used to explain the often-cited fact that magnetic fields have anti-oedematous, analgesic and anti-inflammatory effects, which is one of the reasons for their wide application in the field of injury treatment. The subjective perception of treatment success may be influenced by the chronic nature of the ulcers, which leads to patients’ expectations not being met. ## References 1. Quiñoz Gallardo M.D., Gonzalo Jiménez E., Barrientos Trigo S., Porcel Gálvez A.M.. Implantación del programa “Centros Comprometidos con la Excelencia en Cuidados” en el Hospital Universitario Virgen de las Nieves. Rev. 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--- title: Phloretamide Prevent Hepatic and Pancreatic Damage in Diabetic Male Rats by Modulating Nrf2 and NF-κB authors: - Rasha Al-Hussan - Nawal A. Albadr - Ghedeir M. Alshammari - Soheir A. Almasri - Mohammed Abdo Yahya journal: Nutrients year: 2023 pmcid: PMC10059022 doi: 10.3390/nu15061456 license: CC BY 4.0 --- # Phloretamide Prevent Hepatic and Pancreatic Damage in Diabetic Male Rats by Modulating Nrf2 and NF-κB ## Abstract This study examined the effect of phloretamide, a metabolite of phloretin, on liver damage and steatosis in streptozotocin-induced diabetes mellitus (DM) in rats. Adult male rats were divided into two groups: control (nondiabetic) and STZ-treated rats, each of which was further treated orally with the vehicle phloretamide 100 mg or 200 mg. Treatments were conducted for 12 weeks. Phloretamide, at both doses, significantly attenuated STZ-mediated pancreatic β-cell damage, reduced fasting glucose, and stimulated fasting insulin levels in STZ-treated rats. It also increased the levels of hexokinase, which coincided with a significant reduction in glucose-6 phosphatase (G-6-Pase), and fructose-1,6-bisphosphatase 1 (PBP1) in the livers of these diabetic rats. Concomitantly, both doses of phloretamide reduced hepatic and serum levels of triglycerides (TGs) and cholesterol (CHOL), serum levels of low-density lipoprotein cholesterol (LDL-c), and hepatic ballooning. Furthermore, they reduced levels of lipid peroxidation, tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), mRNA, and total and nuclear levels of NF-κB p65, but increased mRNA levels, total and nuclear levels of Nrf2, as well as levels of reduced glutathione (GSH), superoxide dismutase (SOD-1), catalase (CAT), and heme-oxygenase-1 (HO-1) in the livers of diabetic rats. All of these effects were dose-dependent. In conclusion, phloretamide is a novel drug that could ameliorate DM-associated hepatic steatosis via its powerful antioxidant and anti-inflammatory effects. Mechanisms of protection involve improving the β-cell structure and hepatic insulin action, suppressing hepatic NF-κB, and stimulating hepatic Nrf2. ## 1. Introduction Type-1 diabetes mellitus (DM) is the most common endocrine disorder that results from a deficiency of insulin, mainly due to autoimmune destruction of the pancreatic beta-cells [1]. The disease is associated with several co-morbidities that raise the mortality rates among affected individuals [2]. Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease associated with T1DM [2]. The disease is caused mainly by metabolic disturbance, which leads to persistent hepatic de novo lipogenesis (DNL), impaired fatty acid (FA) oxidation, and sustained gluconeogenesis [3,4,5,6]. Although the disease is initiated as simple steatosis, an accumulative line of evidence has shown that locally induced oxidative stress, mediated by the overproduction of reactive oxygen species (ROS), is the leading mechanism responsible for the progression to non-alcoholic steatohepatitis (NASH) and liver injury by promoting inflammation, fibrosis, and apoptosis [7,8]. Major resources of such ROS in the livers of T1DM include endoplasmic reticulum (ER) stress, mitochondria dysfunction, activation of NADPH oxidase, and scavenging/reduced expression of endogenous antioxidants [7,8]. However, recent evidence has also shown that altered antioxidant signaling pathways contribute significantly to the development and progression of NAFLD in diabetic livers [9,10,11]. Among all, much focus has been given to the indispensable role of the nuclear factor erythroid 2-related factor 2 (Nrf2)/antioxidant axis in mediating and protecting against NAFLD in metabolically impaired and diabetic animals [12,13]. In general, Nrf2 is the major antioxidant transcription factor that stimulates cell survival by inducing phase II antioxidant enzymes such as heme oxygenase-1 1 (HO-1), catalase (CAT), superoxide dismutase (SOD), etc. [ 14]. In addition, Nrf2 has indirect antioxidant and anti-inflammatory effects and can increase insulin sensitivity by suppressing the nuclear factor kappa beta (NF-κB) [15,16]. In addition, experimental studies in HFD-fed animals have confirmed that Nrf2 can inhibit DNL and stimulate FA oxidation by promoting mitochondria biogenesis, suppressing the lipogenic sterol regulatory element-binding transcription factors (SREBPs), and activating FA oxidation [13,14,17,18]. In the cells, the transcriptional activity of Nrf2 is largely determined by a cytoplasmic inhibitor known as the Kelch-like ECH-associated protein 1 (Keap-1), which is tightly bound with Nrf2 [19,20]. In the presence of oxidative stress, ROS can modify keep-1, which results in the loss of this association and hence the nuclear translocation of Nrf2 [19,20]. The levels and nuclear activities of Nrf2 are significantly depleted in the livers of diabetic animals with T1DM and type 2 DM (T2DM), whereas the activation of this factor prevented oxidative liver injury by suppressing oxidative stress, inflammation, lipotoxicity, and apoptosis [9,10,11,20]. Hence, it seems reasonable that drugs that improve hepatic Nrf2 and antioxidant levels could protect against NAFLD [19,21]. Plant phytochemicals are natural activators for Nrf2, which has been largely studied for their potential to treat liver disorders [22,23]. Phloretin, a major flavonoid found in apple juice, has well-known anti-diabetic, hypoglycemic, hypolipidemic, antioxidant, and anti-inflammatory effects mediated mainly by activating the Nrf2/antioxidant axis [24,25,26]. Phloretamide [3-(p-Hydroxyphenyl) propionic acid] is a polyphenol derivative of phloretic acid, a major metabolite of phloretin metabolism, and acts as a growth hormone [27]. Until now, the pharmacological effects of phloetamide have not been well-characterized in rodents or animals, and such studies are still lacking. Interestingly, in a single old study, it has been reported that ex vivo treatment with phloretamide stimulates Nrf2 signaling in cultured hepatocytes [28]. Hence, it was worth targeting this molecule to characterize its potential to treat several metabolic and chronic disorders, which may provide a future novel therapy. Streptozotocin (STZ) is the best-known commercial drug that leads to features of T1DM by damaging the majority of pancreatic β-cell and reducing serum insulin levels [29]. Therefore, in this study, we tested the hypothesis that phloretamide could alleviate NAFLD in SZT-induced diabetic rats by attenuating oxidative stress and inflammation. In addition, we have tested if this protection involves hypoglycemic and hypolipidemic effects and modulates the hepatic Nrf2/antioxidant axis. ## 2.1. Animals Twelve-week-old male Wistar rats weighing 220–240 gm were obtained from the Experimental Animal Care Center, King Saud University (KSU), Riyadh, KSA. The animals were housed under environmentally controlled conditions (22 ± 5 °C, 55 ± $5\%$ humidity) with a 12 h light/dark cycle. The rats were acclimatized to their environment for 2 weeks. During the entire period of the study, all animals had free access to water and chow and were housed in pairs in plastic cages. The diet used in this experiment was a normal standard control diet (cat # D12450B, Research Diets, Newbrunswick, NJ, USA) containing $10\%$ fat (4.3 g%), $20\%$ proteins (19.2 g%), and $70\%$ carbohydrates (67.3 g%) with a total energy intake of 3.85 kcal/g). All experimental protocols included in this study were approved by the Research Ethics Committee (REC) at King Saudi University, Riyadh, Saudi Arabia, and all protocols were conducted according to the Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines. ## 2.2. Establishment of DM We have previously shown that Wistar rats are highly exposed to DM and significant depletion in insulin levels upon injection of STZ (50 mg/kg) [30]. This was the reason for selecting this species for this study. In accordance, DM was introduced to the rats of this study using a single intraperitoneal dose of STZ (50 mg/kg) which promotes an approximately $76\%$ loss of pancreatic β-cells with a minimal mortality rate [29]. In brief, rats were fasted overnight and then injected with STZ (#75221, Sigma Aldrich, St. Louis, MO, USA) at the selected dose (prepared in 0.5 M sodium citrate) (pH = 7.4). Two weeks later, the rats fasted, and drops of whole blood were withdrawn from the rats’ tails and used to measure fasting glucose levels using a glucometer (Accu-Chek II Boehringer, ON, Canada). Those rats discovered to have blood glucose levels of >320 mg/dL were diagnosed with insulin deficiency DM. In addition, some of those rats were euthanized using neck dislocation, and their pancreases were collected and processed at the pathology laboratory for hematoxylin and eosin (H&E) staining to confirm the pancreatic damage. ## 2.3. Experimental Design A total of 48 (control [24] and diabetic [24]) rats were selected randomly and divided into 6 groups ($$n = 8$$ rats/each) as follows: [1] control group: nondiabetic rats were orally administered the carrier, $0.5\%$ low viscosity carboxymethylcellulose (CMC) (#5678, Sigma Aldrich, MO, USA); [2] phloretamide (100 mg/kg)-treated group: nondiabetic rats were orally treated with phloretamide dissolved in $0.5\%$ CMC (phloretamide solution) at a dose of 100 mg/kg/day; [3] phloretamide (200 mg/kg)-treated group: nondiabetic rats were orally treated with phloretamide solution at a dose of 200 mg/kg/day; [4] STZ-diabetic model rats: diabetic rats were administered $0.5\%$ CMC; [5] STZ + phloretamide (100 mg/kg)-treated group: rats with pre-established DM were orally treated with phloretamide solution at a dose of 100 mg/kg/day; [6] STZ+ phloretamide (200 mg/kg)-treated group: rats with pre-established DM were orally treated with phloretamide solution at a dose of 200 mg/kg/day. Phloretamide was synthesized and purchased from Yangzhou Chemical Co., Ltd., Jiangsu, China, based on previously published reports and structures [27,31,32]. All treatments were conducted for 12 weeks. Treatment with phloretamide solution was conducted by gavage using a special stainless-steel feeding cannula. Food intake and body weight were monitored weekly. Dead rats in the diabetic groups were replaced with new rats. The selected doses of phloretamide were based on our preliminary data showing that 100 mg/kg was the minimum dose to reduce the fasting 24 h glucose levels in STZ-diabetic rats. In addition, we did not see any signs of renal, cardiac, or hepatic toxicities with these doses after 3 days of administration. ## 2.4. Serum Collection and Measurements By the end of the treatment period, all rats were fasted overnight and were anesthetized with a low dose of ketamine/xylazine (50:5 mg/kg) [33]. In brief, rats were placed on a heated blanket, and their blood temperature was monitored using a digital rectal thermometer. All rats were kept normothermic throughout the anesthetic period. The anesthesia was confirmed when the rat lost its righting and toe withdrawal reflex. Blood samples were withdrawn from the heart of all anesthetized animals into EDTA or plain tubes, which were centrifuged at 3000 rpm to collect plasma and serum samples, respectively. These samples were stored at −20 °C and used later when needed. ## 2.5. Tissue Collection After blood collection, all animals were euthanized using neck dislocation. Their livers were collected on ice, weighed, and washed with ice-cold phosphate-buffered saline (PBS, pH = 7.4). The liver of each rat was fractioned into smaller pieces, some of which were placed in $10\%$ buffered formalin, and the others were snap-frozen in liquid nitrogen and then frozen at −80 °C until use. All formalin-preserved sections were processed within 20 h of collection at the pathology laboratory of KSU, Riyadh, KSA. ## 2.6. Analysis of the Serum and Plasma The fasting glucose and insulin levels were assessed using commercially available kits formulated specifically for rats (#90010, Crystal Chem, Elk Grove Village, IL, USA and #DIGL-100, BioAssay Systems, Hayward, CA, USA) following each supplier’s instructions. In addition, we calculated the values from the homeostatic model assessment of β-cell function (HOMA-β) for each animal using the previously published equation [30]: HOMA-β = (Fasting insulin (ng/mL) × 20)/(Fasting glucose (mg/dL) − 3.5). Levels of total cholesterol (CHOL) and triglyceride (TG) serum levels were determined using multi-enzyme-based kits (#MBS726298, MyBioSource, San Diego, CA, USA, and #ECCH-100, BioAssay Systems, Hayward, CA, USA, respectively). Serum and hepatic levels of high-/low-density lipoprotein cholesterol (LDL-c/HDL-c were assayed using a special colorimetric kit (#E2HL-100 BioAssay Systems, CA, USA). Serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase were analyzed using assay kits (#EALT-100 and EASTR-100, BioAssay Systems, CA, USA). All procedures were performed according to the manufacturer’s instructions for each kit ($$n = 8$$ samples/group). ## 2.7. Extraction of Lipid from Frozen Livers This procedure followed the protocols published by our laboratories [30], which followed the method of Folch et al. [ 34]. Briefly, livers from each rat (125 mg) were soaked in a 2 mL methanol: chloroform mixture (1:2 v/v) for 4 h, followed by the addition of normal saline (0.25 mL). The whole mixture was centrifuged at 2000× g for 10 min. The lower layer was isolated, and the solvent was removed by evaporation in a rotatory evaporator. The dried lipids were then dissolved in 0.25 mL absolute isopropanol and then used while fresh for the measurement of lipid fraction via biochemical analysis using the same kits used to measure lipids in the serum and mentioned in the previous section above ($$n = 8$$ samples/group). ## 2.8. Preparation of the Tissue Homogenates and Nuclear Extraction Liver samples (0.1 g) were homogenized in 9 volumes (0.9 mL) of lysis buffer consisting of 30 mM phosphate buffer and 140 mM KCl (pH = 7.3) at a ratio of 1:10, followed by centrifugation at 600× g for 10 min [35]. The supernatants were isolated, stored at 80 °C, and used later to measure antioxidants and inflammatory marker levels. The cytoplasmic/nuclear extracts were prepared using the nuclear extract kit (#40010, ActiveMotif, Tokyo, Japan). All procedures and measurements were conducted according to each manufacturer’s instructions. ## 2.9. Measurements of the Tissue Homogenates and Nuclear/Cytoplasmic Extracts All kits used for this part were rat-specific. MDA ELISA kit for rats was used to measure levels of malondialdehyde (MDA) in the liver homogenates (#MBS268427, MyBioSource, CA, USA). GSH ELISA kit (#MBS265966; MyBioSource, CA, USA), SOD ELISA kit (#MBS036924, MyBioSource, CA, USA), CAT ELISA kit (#MBS726781, MyBioSource, CA, USA), IL-6 ELISA kit (#MBS269892, MyBioSource, CA, USA), HO-1 ELISA kit (MBS764989, MyBioSource, CA, USA) and TNF-αELISA kits (#MBS2507393, MyBioSource, CA, USA) were used to measure the levels of glutathione (GSH), superoxide dismutase (SOD), catalase (CAT), interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) in the liver homogenates. G6PC ELISA kit (#MBS097902 MyBioSource, CA, USA), FBP1 ELISA kit (#MBS931493, MyBioSource, CA, USA), and GLY ELISA kit (#MBS1600418; MyBioSource, CA, USA) were used to measure the levels of glucose-6 phosphatase (G-6-Pase), fructose-1,6-bisphosphatase 1 (PBP1), and glycogen in the liver homogenates. The TransAM Nrf2, NF-E2-related factor 2 (Nrf2 DNA binding ELISA) kit (#50296, ActiveMotif, Tokyo, Japan) and TransAM NF-κB p65 ELISA kits (#40096, ActiveMotif, Tokyo, Japan) were used to measure the total and cytoplasmic levels of Nrf2 and NF-κB p65 in the homogenates. All procedures were conducted according to each manufacturer’s instructions for 8 samples/groups. ## 2.10. Real-Time PCR (qPCR) Real-time PCR was conducted to measure the mRNA transcript levels of Keap-1, NF-κB, Nrf2, and β-actin (a reference gene). All primer sequences were designed and provided by ThermoFisher, Waltham, MA, USA (Table 1). The total RNA was isolated from 0.1 g frozen samples using 1 ml TRIzol reagent (#15596026, Invitrogen, Waltham, MA, USA) as per the manufacturer’s instruction. The first-strand cDNA was synthesized using a commercial kit (#GE27-9261-01, Roche Diagnostic Company, Indianapolis, IN, USA) as per the kit instruction. All amplifications were carried out using a CFX69 real-time PCR system (Biorad, Hercules, CA, USA) according to the amplification steps provided with the SsoFast EverGreen Master Mix kit (#172-5200, Biorad, CA, USA). In brief, the total amplification volume was 20 µL/well, containing the following ingredients: 2 μL cDNA (50 ng/well); 10 µL of the master mix reagent; 0.2 µL of the forward primer (500 nM/each), 0.2 µL of the reverse primer (500 nM/each); and 7.6 µL nuclease-free water. The steps of the amplification were: heating (1 cycle/98 °C/30 s), denaturation (40 cycles/98 °C/5 s), annealing (40 cycles/60 °C/5 s), and melting (1 cycle/5 s/60–95 °C). The relative expression of all targets was normalized to the expression of the reference gene, β-actin. ## 2.11. Hematoxylin and Eosin (H&E) Staining Formalin-preserved livers were deparaffinized in xylene with reduced levels of $100\%$, $90\%$, and $70\%$. After this, all samples were embedded in wax, cut in a rotatory microtome (3–5 µM), and stained with Harris hematoxylin (H)/glacial acetic acid solution. Next, the samples were de-stained with 1:400 v/v HCL/ethanol ($70\%$) solution and stained with one drop of eosin (E). All samples were then dehydrated with ethanol and xylene and covered with mounting media and a coverslip. The next day, all tissues were examined under a light microscope and photographed at 200×. ## 2.12. Statistical Analysis GraphPad Prism (v. 8) analytic software was used for the statistical analysis of all data. The Kolmogorov–Smirnov test was utilized to test the normality. Analyses were performed using the one-way ANOVA test. The levels of significance were determined using Tukey’s post hoc test ($p \leq 0.05$). All data were expressed in the results as means ± standard deviation (SD). ## 3.1. Changes in Rat Body Weights Final body weights were not significantly changed between the control and the phloretamide-treated rats for either dose (100 and 200 mg/kg) (Table 2). However, final body weights were significantly reduced in the STZ-diabetic rats compared to the control rats (Table 2). Body weights were significantly increased again in both the STZ + phloretamide (100 mg/kg) and STZ + phloretamide (200 mg/kg) rats compared to the STZ-diabetic rats (Table 2). The increment in body weights in the STZ + phloretamide (200 mg/kg)-treated rats was significant compared to the STZ + phloretamide (100 mg/kg)-treated rats, at levels which did not significantly vary from those of the control rats (Table 2). ## 3.2. Changes in the Markers of Glucose Homeostasis While the levels of fasting insulin were not significantly changed, fasting glucose and hepatic levels of G-6-Pase and FBP-1 were significantly reduced, and hepatic levels of hexokinase and glycogen were significantly increased in the control rats that were administered phloretamide at doses of 100 and 200 mg/kg (Table 2). On the other hand, levels of fasting insulin and hepatic hexokinase and glycogen were significantly decreased, but fasting glucose and hepatic levels of G-6-Pase and FBP-1 were significantly increased in STZ-diabetic rats compared to control and phloretamide (100 and 200 mg/kg)-treated rats (Table 2). These descriptors were significantly reversed in both the STZ + phloretamide (100 mg/kg) and STZ + phloretamide (200 mg/kg) groups compared to the STZ-diabetic rats (Table 2). In the control and STZ-diabetic rats, the effect of phloretamide on all of these markers was significantly more profound with the higher dose (200 mg/kg) compared to those observed with the lower 100 mg/kg dose (Table 2). Despite this, fasting glucose levels and hepatic levels of G-6-Pase and FBP-1 remained significantly higher, while the levels of fasting insulin, the hepatic levels of fructokinase, and the hepatic levels of glycogen in the STZ + phloretamide (200 mg/kg) group remained significantly varied, with the corresponding basal levels observed in the control rats (Table 2). ## 3.3. Histology of the Pancreas Pancreatic tissues obtained from the control, phloretamide (100 mg/kg)-treated, and phloretamide (200 mg/kg)-treated rats showed normally sized and round islets of Langerhans with abundant cell number. Pancreases obtained from STZ-diabetic rats showed shrinkage in the islets of Langerhans with reduced cell number and hemorrhage surrounding the islets (Figure 1D). An increment in the size of the islets as well as in the numbers of their cell content was observed in both the STZ + phloretamide (100 mg/kg)- and STZ + phloretamide (200 mg/kg)-treated rats (Figure 1E,F, respectively). The improvement in the structure of the pancreas was more obvious with the dose of 200 mg/kg. ## 3.4. Changes in the Serum and Hepatic Lipid Profiles Among all measured lipid-related parameters, treating the rats with phloretamide (100 and 200 mg/kg) resulted in a dose-dependent reduction in the serum levels of FFAs compared to the control rats (Table 3). The serum levels of FFAs, TGs, CHOL, and LDL-c, as well as the hepatic levels of TGs and CHOL were significantly increased, whereas serum levels of HDL-c were significantly reduced in the STZ-diabetic rats compared to the control or phloretamide (100 and 200 mg/kg)-treated rats (Table 3). An opposite picture is seen concerning all of these serum and liver lipid markers in the STZ + phloretamide (100 mg/kg)- and STZ + phloretamide (200 mg/kg)-treated rats compared to the STZ-treated rats (Table 3), an effect that was dose-dependent. Of note, serum and hepatic levels of TGs and CHOL and serum levels of LDL and FFAs remained significantly higher, and serum levels of HDL-c remained significantly lower in the STZ + phloretamide (200 mg/kg)-treated rats compared to the control rats (Table 3). ## 3.5. Changes in the Hepatic Markers of Oxidative Stress and Inflammation Hepatic levels of TNF-α and IL-6, as well as the mRNA of NF-κB, and total and nuclear levels of NF-κB p65 did not significantly differ between the control, phloretamide (100 mg/kg), and phloretamide (200 mg/kg)-treated rats, but they were significantly higher in the STZ-diabetic rats (Table 4 and Figure 2). In addition, the levels of MDA were significantly higher, but the levels of GSH, SOD, CAT, and HO-1 were significantly lower in the livers of the STZ-diabetic rats compared to the control and phloretamide (100 and 200 mg/kg)-treated rats (Table 4). The levels of MDA, TNF-α, IL-6, NF-κB mRNA, and total and nuclear levels of NF-κB p65 were significantly reduced, but levels of GSH, SOD, CAT, and HO-1 were significantly increased in the livers of both the control and STZ-diabetic rats which received phloretamide at either dose (100 and 200 mg/kg) compared to the control and diabetic rats to which we administered only the vehicle, respectively (Table 4 and Figure 2). However, the levels of all of the biochemical endpoints were improved with the higher dose of the drug, and those levels did not significantly return to their basal levels (Table 4 and Figure 2). ## 3.6. Changes in the Hepatic Keap-1/Nrf2 Axis The mRNA of both Keap-1 and Nrf2, as well as the ratios of Keap-1/Nrf2, were significantly increased, whereas total and nuclear levels of Nrf2 were significantly depleted in the livers of the STZ-diabetic rats compared to the control rats (Figure 3A–E). The mRNA levels of Keap-1 did not significantly vary between the control, phloretamide (100 mg/kg)-, and phloretamide (200 mg/kg)-treated rats (Figure 3A). Along those same lines, the mRNA levels of Keap-1 did not significantly vary between the STZ-diabetic, STZ + phloretamide (100 mg/kg), and STZ + phloretamide (200 mg/kg)-treated rats (Figure 3A). The mRNA levels, total, and nuclear levels of Nrf2 were significantly increased, whereas the ratios of Keap-1/Nrf2 were significantly reduced in both the control and the STZ-diabetic rats that were treated with either dose of phloretamide (100 or 200 mg/kg) compared to either the control or the STZ-diabetic rats that were administered only the vehicle (Figure 3B–E). Interestingly, and in both cases, the stimulatory effects of phloretamide on the mRNA, nuclear, and total levels of Nrf2 were higher in the STZ + phloretamide (200 mg/kg)-treated rats compared to those effects afforded by the lower dose (100 mg/kg). ## 3.7. Histological Findings for the Livers Livers obtained from the control, phloretamide (100 mg/kg)-, and phloretamide (200 mg/kg)-treated rats showed normal histological features, including central veins, sinusoids, and hepatocytes (Figure 4A–C). However, livers obtained from the STZ-diabetic rats showed increased cytoplasmic vacuolation of small, medium, and large size; dilated sinusoids; and immune cell infiltration (Figure 4D and Figure 5A). On the other hand, the livers of the STZ + phloretamide (100 mg/kg)-treated rats showed an improvement in the number of normal hepatocytes, but they still contained a large number of cells showing moderately sized fat vacuoles (Figure 4B). Almost-normal hepatic structures with almost no cytoplasmic vacuoles were seen in the livers of the STZ + phloretamide (100 mg/kg)-treated rats. Nonetheless, some damaged hepatocytes were still seen in this group of rats (Figure 5C,D). ## 4. Discussion Data from this study revealed a dose-dependent potential of phloretamide to alleviate pancreatic damage and NAFLD in STZ-induced DM in rats. In this study, treatment with phloretamide not only reduced fasting glucose and HBA1c levels, but also attenuated STZ-mediated pancreatic β-cell damage. In addition, it significantly inhibited the hepatic gluconeogenesis in the livers of STZ-diabetic rats by suppressing several key enzymes such as glucose-6 phosphatase (G-6-Pase) and fructose-1,6-bisphosphatase 1 (PBP1). Moreover, treatment with phloretamide ameliorated dyslipidemia and hepatic DNL in these STZ-diabetic rats that were concomitant with suppressing markers of lipid peroxidation and inflammation. However, the hepatic antioxidant and protective effect of phloretamide seem to be associated with activating the Nrf2/antioxidant axis, as well as suppressing the activation of NF-κB p65. Therefore, the overall protective effect of phloretamide against STZ-induced damage and NAFLD disease includes the regeneration of pancreatic beta cells and hypolipidemic, hypoglycemic, antioxidant, and anti-inflammatory effects. In this study, we utilized STZ, glucosamine–nitrosourea to induce DM in rats, as discussed by other authors, to promote hyperglycemia and hypoinsulinemia [36,37,38]. In general, STZ is a selective, toxic drug for pancreatic β-cells that promotes hyperglycemia and insulin deficiency by damaging these cells via the increased generation of free radicals, such as superoxide (O2−), hydrogen peroxide (H2O2), and nitric oxide (NO), as well as by depleting the pancreatic cell levels of NAD+ and ATP [39]. In addition, STZ-mediated DM is associated with a severe reduction in body mass due to increased muscle wasting and stimulated lipolysis in the adipose tissue [30]. In this study, STZ-treated rats showed a significant reduction in their body weights that coincided with a significant increase in serum levels of FFAs, indicating active adipose tissue lipolysis and muscle loss. In addition, their pancreas showed increased shrinkage and the loss of pancreatic β-cells, as well as fasting hypoinsulinemia, thus confirming the pro-oxidant damaging effect of STZ and its role in the development of the observed fasting hyperglycemia. On the other hand, treatment with phloretamide significantly improved rat body weights and reduced fasting glucose levels in both the control and STZ-diabetic rats in a dose-dependent manner. However, while it failed to modulate insulin levels in control rats, phloretamide slightly but significantly raised circulatory insulin levels in STZ-diabetic rats to levels that remained significantly lower than the basal levels observed in the control rats. These data indicate a potent hypoglycemic effect of phloretamide, which seems to be caused partially by stimulating insulin release from the damaged pancreatic cells, but it is also largely mediated by other mechanisms, such as improving peripheral and hepatic insulin action and regulating hepatic glucose homeostasis. Yet, such an increase in insulin levels in STZ-diabetic rats after phloretamide treatment could be explained by the antioxidant potential that other researchers have identified. However, we did not study the effect of phloretamide on pancreatic markers of oxidative stress to confirm this [27]. To further examine the potential hypoglycemic effect of phloretamide, we targeted key hepatic enzymes responsible for glucose homeostasis. In the liver, glucose stimulates glycogen synthesis and inhibits gluconeogenesis [40]. G-6-Pas and FBP-1 are key enzymes responsible for gluconeogenesis, whereas hexokinase is responsible for glucose degradation [41,42]. Glycogen stores are significantly depleted in the muscles and livers of T1DM animals and humans due to a lack of insulin [43,44,45,46]. This was also documented in the livers of the diabetic rats in this study, which also showed lower stores of hepatic glycogen. In addition, these rats had reduced hepatic hexokinase levels and showed a significant increment in G-6-Pase and FBP-1, which can also be attributed to insulin deficiency/action on the liver, and it explains such a reduction in glycogen stores in these diabetic rats. These data are also supported by the findings of many other authors [36,47]. However, phloretamide not only significantly reversed these events in the STZ-treated rats, but it also modulated the levels of these metabolic enzymes in the same way and in a dose-dependent manner in the livers of the control rats, too. As discussed above, and given that phloretamide did not affect insulin levels in the control rats but significantly reduced circulatory levels of FFAs, these data suggest that phloretamide suppresses hyperglycemia, mainly by regenerating the pancreatic-beta-cells, regulating hepatic glucose hemostasis and by increasing insulin sensitivity and signaling. Phloretamide is a metabolite that is produced from the metabolism of phloretin and its product, phloretic acid [27]. Although ours is the first experiment to describe this effect for phloretamide, the previously reported hypoglycemic effect of phloretin was attributed to its ability to stimulate the generation of β-cells, increase insulin release, improve peripheral insulin action, stimulate hepatic glycogen synthesis, suppress gluconeogenic enzymes, and upregulate hexokinase in the liver [24,25]. Hence, our data may suggest that phloretin produces its hypoglycemic effect indirectly by generating phloretamide. These data can be also comparable to other previous studies. Indeed, several plant herbal extracts and plant-derived compounds such as salidroside, puerarin, ginseng, vitexin, saponins, and geniposide attenuated fasting hyperglycemia and complications of DM by their potential to attenuate the oxidative damage of the pancreas and promoting regeneration [48]. On the other hand, other plant-derived compounds, fisetin, quercetin, morin, isoleucine, berberine, and berberrubine attenuated hyperglycemia in diabetic and obese animals by improving insulin sensitivity and/or inhibiting hepatic gluconeogenesis [49,50,51]. On the other hand, hyperlipidemia is the major hallmark of DM and NAFLD and occurs mainly due to lipotoxicity and increased influx of FFA from the impaired adipose tissue [5,6,52]. Statins remain the major golden therapy to treat hyperlipidemia in patients with DM and NAFLD [53]. Currently, several plant-derived flavonoids have been also shown to exert anti-diabetic effects and were able to attenuate hyperlipidemia and hepatic steatosis either directly by suppressing de novo lipogenesis or indirectly through increasing insulin sensitivity and adipose tissue lipogenesis [54]. Examples include quercetin, rutin, kaempferol, isorhamnetin, fisetin, hesperidin, naringenin, eriodictyol, curcumin, and apigenin [54]. In this examination, we have detected a significant increase in TGs, CHOL, FFAs, and LDL-c in the serum of STZ-treated rats, coinciding with low serum levels of HDL-c and higher levels of CHOL and TGs in their livers. In addition, the livers of the STZ-diabetic rats showed severe damage and hepatocyte ballooning, indicating the progression toward NASH. These data also support many other authors who have also shown similar results [55,56]. On the contrary, phloretamide, at both 100 and 200 mg/kg, significantly attenuated hyperlipidemia and hepatic steatosis in a dose-dependent manner in the STZ-diabetic rats. However, it failed to modulate the levels of all of these lipids in the serum and livers of the control rats, even at the higher dose. These data suggest that the hypolipidemic effect of phloretamide is not direct and is probably secondary due to its amelioration of fasting hyperglycemia. Yet, further examination is required to confirm this. However, the hypolipidemic effect of phloretin has been reported in the literature, where it was attributed to suppressing DNL via the activation of SIRT1/AMPK signaling, which can inhibit SREBP1c [57]. According to the multiple-hit hypothesis, oxidative stress and inflammation are the primary mechanisms that lead to hepatic damage and the progression to NASH in diabetic conditions [58]. Higher levels of oxidative stress and inflammation markers, as well as reduced levels of antioxidants, are common in the livers of animals and patients with NAFLD [19]. On the one hand, the increase in the metabolism of FFAs and the subsequent impairment in the process of oxidative phosphorylation, mitochondrial damage, and ER stress are the major pro-oxidant pathways that generate ROS in the livers of diabetic animals [3,4,8]. In addition, high glucose levels can promote liver damage, fibrosis, and apoptosis by generating high levels of ROS through several mechanisms, including auto-oxidation and the activation of the PKC, polyol, hexose amine, and advanced glycation end-product (AGE) pathways [8,30]. In addition, ROS and NF-κB are positively crossed with each other during tissue damage and can stimulate each other in a vicious cycle. Similar to these data, MDA, TNF-α, and IL-6 levels were significantly increased, while levels of the measured antioxidants (i.e., GSH, SOD, and CAT) were significantly reduced in the livers of the STZ-diabetic rats in this study. In addition, the STZ-treated rats showed a significant increase in the mRNA levels of NF-κB, as well as in the total and nuclear levels of NF-κB p65, which may explain the source of the increase in the levels of ROS. These findings are similar to those of many other authors [30,59,60]. On the contrary, these alterations were reversed by both dosage levels of phloretamide, with more profound results to be seen with the higher dose, thus illustrating the antioxidant and anti-inflammatory effects of this compound and supporting the previously reported hepatic antioxidant potential of phloretamide in vitro. Although these effects could be attributed to the improvement in glucose and FFA metabolism in diabetic rats post administration of phloretamide, phloretamide treatment in the control rats also reduced levels of MDA and increased the content of all measured antioxidant enzymes in a dose-dependent manner. Since no changes in the levels of TNF-α and IL-6, nor in the expression, total, or nuclear levels of NF-κB were observed in the livers of the control rats to which we administered phloretamide, it seems very reasonable that the silencing of the inflammatory response and the activation of NF-κB is mediated by the glucose-independent antioxidant potential of phloretamide. Supporting this, and independent of any other pathway, treating normally cultured hepatocytes with a physiological dose of phloretamide stimulated levels of glutathione S-transferase (GST) isoenzymes, NAD(P)H: quinone oxidoreductase-1 (NQO1), and heme-oxygenase-1 (HO-1) [27]. In addition, drugs that activated antioxidants or treatment with N-acetyl cysteine (NAC) attenuated hepatic inflammation by suppressing NF-κB [61,62]. Additionally, antioxidant therapy attenuated NAFLD in diabetic rats by suppressing NF-κB [30]. Nonetheless, the activation of Nrf2 is novel therapy to treat NAFLD by upregulating antioxidants, suppressing NF-κB, and regulating the activities of some genes involved in DNL and FA mitochondrial oxidation [18,19]. Associated with all of the abovementioned changes in the livers of the diabetic rats, there was a significant increment in the hepatic expression of both Keap-1 and Nrf2 in the livers of the STZ-treated rats. This was expected due to the role of ROS in upregulating Keap-1 and Nrf2 [19]. However, the ratio of Keap-1/Nrf2 in the livers of these diabetic rats was almost 1.5 times higher than the ratio in the control rats (<1). Such a higher ratio of Keap-1/Nrf2 may explain why the livers of these diabetic rats showed a significant reduction in the nuclear levels of Nrf2 despite the increment in its transcription. However, the significant progressive reduction in the expression ratio of Keap-1/Nrf2 after increasing the doses of the phloretamide treatment explains why the livers of these treated rats showed higher nuclear levels of NrfA, similar to the reduction in the activation of Nrf2 in the livers of STZ-diabetic rodents, with or without NAFLD [9,10,11]. Therefore, it seems reasonable that the reduced activation of Nrf2 is a key mechanism for developing hepatic steatosis and oxidative stress in the livers of these rats. In support of this theory, Nrf2-deficient rats that were fed a methionine- and choline-deficient (MCD) diet showed accelerated lipid accumulation, reduced levels of GSH and antioxidant enzymes, and increased expression of cytochrome P450 enzymes, with normal glucose metabolism compared to Nrf2+/+ rats fed the same diet [12,13]. On the other hand, several plant extracts and flavonoids also attenuated diabetic complications and prevented several tissue injuries in other animal models by activating the Nrf2/antioxidant axis [22]. The most interesting finding observed in this study is that treatment with phloretamide also increased the transcription of Nrf2 and stimulated its nuclear levels in a dose-dependent manner in both the control and diabetic rats, thus suggesting a regulatory role for this factor, irrespective of circular glucose levels. This effect was determined to be independent of modulations in the expression of Keap-1, as similar mRNA levels of Keap-1 were observed between the diabetic rats, with or without phloretamide treatment. Based on this observation in the model rats, we can conclude that phloretamide might attenuate hepatic steatoses and oxidative stress via its stimulatory role on Nrf2, and this pathway seems to be a major mechanism of action. Indeed, several plant flavonoids can upregulate Nrf2 in a ROS-independent mechanism by regulating their transcription and translation [22]. Similar to our findings, restoring Nrf2 in MCD mice alleviated the hepatic phenotype toward a reduction in hepatic steatosis, mainly by activating PPARα and suppressing SREBP1 [13]. Additionally, treating diabetic rats with phloretin attenuated diabetic cardiomyopathy by inhibiting the interaction between Nrf2 and Keap-1, independent of its hypoglycemic effect [63]. Moreover, phloretin attenuated several types of organ damage in other non-diabetic animal models by activating Nrf2/antioxidant/NF-κB signaling [23,24,25,26]. Although these data seem very interesting, they are still observations and have some limitations. Importantly, whether Nrf2 is the upstream mechanism of action of phloretamide that regulates oxidative stress, antioxidant levels, DNL, and the activity of NF-κB cannot be concluded based solely on these data. Therefore, it is highly advisable to repeat this work in cell cultures or animals lacking Nrf. This will enable us to further draw a direct conclusion. ## Study Limitations Despite these findings, the above current study still has some critical limitations. On the one hand, the basis of selection of the doses of the phloretamide was based on their hypoglycemic effect in our pilot studies. Until now, no studies have been available to show the optimum concentration of naturally produced phloretamide that can be found in vivo as the metabolite from phloretine. Hence, a more comprehensive approach targeting pharmacokinetics, absorption, availability, and tissue levels of phloretamide should be considered to minimize the dose of treatment. In addition, our data are still observational. Therefore, more well-designed studies using animals deficient with Nrf2 are highly recommended for a better understanding of the mechanism of action of this flavonoid. 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--- title: Secretory Phospholipase A2 and Interleukin-6 Levels as Predictive Markers of the Severity and Outcome of Patients with COVID-19 Infections authors: - Stanislav Urazov - Alexandr Chernov - Oleg Popov - Natalya Klenkova - Natalya Sushentseva - Irina Polkovnikova - Svetlana Apalko - Kseniya Kislyuk - Dragana Pavlovich - Andrey Ivanov - Sergey Shcherbak journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10059025 doi: 10.3390/ijms24065540 license: CC BY 4.0 --- # Secretory Phospholipase A2 and Interleukin-6 Levels as Predictive Markers of the Severity and Outcome of Patients with COVID-19 Infections ## Abstract Coronavirus disease (COVID-19) has become a global pandemic. COVID-19 patients need immediate diagnosis and rehabilitation, which makes it urgent to identify new protein markers for a prognosis of the severity and outcome of the disease. The aim of this study was to analyze the levels of interleukin-6 (IL-6) and secretory phospholipase (sPLA2) in the blood of patients regarding the severity and outcome of COVID-19 infection. The study included clinical and biochemical data obtained from 158 patients with COVID-19 treated at St. Petersburg City Hospital No. 40. A detailed clinical blood test was performed on all patients, as well as an assessment of IL-6, sPLA2, aspartate aminotransferase (AST), total protein, albumin, lactate dehydrogenase (LDH), APTT, fibrinogen, procalcitonin, D-dimer, C-reactive protein (CRB), ferritin, and glomerular filtration rate (GFR) levels. It was found that the levels of PLA2, IL-6, APTV, AST, CRP, LDH, IL-6, D-dimer, and ferritin, as well as the number of neutrophils, significantly increased in patients with mild to severe COVID-19 infections. The levels of IL-6 were positively correlated with APTT; the levels of AST, LDH, CRP, D-dimer, and ferritin; and the number of neutrophils. The increase in the level of sPLA2 was positively correlated with the levels of CRP, LDH, D-dimer, and ferritin, the number of neutrophils, and APTT, and negatively correlated with the levels of GFR and lymphocytes. High levels of IL-6 and PLA2 significantly increase the risk of a severe course by 13.7 and 2.24 times, and increase the risk of death from COVID-19 infection by 14.82 and 5.32 times, respectively. We have shown that the blood levels of sPLA2 and IL-6 increase in cases which eventually result in death and when patients are transferred to the ICU (as the severity of COVID-19 infection increases), showing that IL-6 and sPLA2 can be considered as early predictors of aggravation of COVID-19 infections. ## 1. Introduction Coronaviruses (CoV) are the causative agents of acute severe respiratory syndrome (SARS-CoV), which first caused a global epidemic in 2002 [1]. In December 2019, a new form of coronavirus (SARS-CoV-2) was recorded in China, which caused a global pandemic of coronavirus disease (COVID-19), which spread to 228 countries in 2020–2023 [2]. To date, the pandemic has caused more than 669 million infections and more than 6.7 million deaths worldwide [3]. Currently, there are more than 1000 different genetic lines of SARS-CoV-2. Most SARS-CoV-2 mutations do not manifest phenotypically. Epidemiological significance is characteristic only for individual lines. To analyze the prevalence, clinical significance, and biological properties (pathogenicity, contagiousness, and neutralizing activity of antibodies) of various variants of the virus, the WHO proposed to identify variants of concern (VOC) and variants of interest (VOI). VOC lines are characterized by biological properties that increase the contagiousness and pathogenicity or reduce the neutralizing activity of antibodies [4]. To date, there are several VOC lines: the α-line (PANGO B.1.1.7, clade 501.YV,1 69–70del, Y144del), first registered in the UK in September 2020 [5]; the β-line (PANGO B.1.351), first discovered in South Africa in May 2020, containing nucleotide substitutions N501Y, K417N, and E484K in the S-protein [6]; the γ-line (PANGO p.1, 484K.V2), containing the key mutation E484K in the S-protein, first isolated from samples of patients from the state of Rio de Janeiro (Brazil) in November 2020 [7]; the δ-line (PANGO B.1.617.2), containing mutations L452R and T478K in the S-protein, first discovered in India in October 2020 [8]; and the Omicron line (PANGO B.1.1.529), containing S477N mutations and first detected in South Africa and Botswana in November 2021 [9]. The clinical spectrum of COVID-19 manifestations varies from the asymptomatic form of the disease and the appearance of symptoms of acute respiratory viral disease: fever ($90\%$), cough ($80\%$ of cases), shortness of breath ($30\%$ of cases), fatigue ($40\%$ of cases), chest congestion ($20\%$), sore throat, runny nose, decreased sense of smell and taste, conjunctivitis, pneumonia, life-threatening complications (including acute respiratory distress syndrome (ARDS)), sepsis, septic shock, and multiple organ failure [4]. These pathological conditions most often lead to mortality in patients of working age (59.7 ± 13.3 years) with chronic diseases such as arterial hypertension (23.7–$30\%$), diabetes mellitus ($16.2\%$), metabolic syndrome, coronary heart disease ($5.8\%$), chronic obstructive pulmonary disease (COPD), nicotine addiction, inflammatory intestinal diseases, and oncological pathology [10,11,12]. The clinical picture in patients at risk is characterized by the development of a “mutual burden syndrome”, accompanied by progressive respiratory and heart failure, which ultimately aggravates their condition and leads to labor losses, early disability, and high mortality. The mortality rate of hospitalized patients ranges from $15\%$ to $20\%$, and is higher in those in need of intensive care [13]. Central to the pathophysiology of COVID-19 disease is immune dysfunction with a pronounced uncontrolled generalized systemic inflammatory reaction due to increased production of inflammatory cytokines, known as a cytokine storm (CS). A CS is accompanied by fever, cytopenia, hyperferritinemia, abnormal liver parameters, coagulopathy, and lung damage (including ARDS) [14]. In all these conditions, the cytokines IL-1β, IL-18, IFN-γ, and IL-6 are the main mediators of hyperinflammation. COVID-19-associated CS is a unique form of hyperinflammatory reaction requiring the development of criteria for its establishment [15]. In addition, lymphocytopenia and neutrophilia are common, with a significant decrease in the number of CD8+ T cells, CD4+ T cells, and natural killer cells (NK) [16]. Biomarkers of lipid metabolism occupy a key place among clinically significant analytes [17]. The most common markers include glucose; triglycerides; cholesterol; saturated and omega-polyunsaturated fatty acids; and high, low, and very low density lipoproteins and their enzymes [18]. Such lipid enzymes include sPLA2 [19]. sPLA2 is a family of lipolytic enzymes that perform diverse functions and are involved in the pathogenesis of a wide range of diseases, e.g., inflammatory arthritis [20], bronchial asthma [21], ARDS [22], atherosclerosis [23], cancer [24], obesity, [25], sepsis [26], and bacterial [27] and viral infections [28], as well as COVID-19 [29]. At the same time, the prognostic value of PLA2 as a biomarker of the severity and outcome of COVID-19 infection in patients remains debatable. In this regard, COVID-19 infected patients with chronic diseases are particularly in urgent need of immediate diagnosis and rehabilitation. It is extremely important to combat this pandemic to study the pathogenesis of this disease and identify new protein targets that may turn out to be highly sensitive and specific prognostic markers of the severity and outcome of the disease, which will allow personalizing medical rehabilitation and therapy programs. The definition of such new biomarkers should be accessible for clinical diagnosis, as cheaply and informatively as possible. The availability of biomarkers is determined by the possibility of their rapid detection in tissue samples or biological fluids of the patient using methods used in laboratory diagnostics. The aim of this work was to analyze the levels of interleukin-6 and secretory phospholipase in the blood of patients depending on the severity and outcome of the COVID-19 infection. ## 2. Results Initially, we studied the severity and outcome in 158 patients with COVID-19 infections. Depending on the severity of the COVID-19 infection, patients were divided into groups with mild $38.6\%$ ($$n = 61$$), average $23.4\%$ ($$n = 37$$), and severe $38.0\%$ ($$n = 60$$) severity. The survival rate (discharge) of patients was $80.4\%$ ($\frac{127}{158}$) and the mortality was $19.6\%$ ($\frac{31}{158}$). Survival among men was $81.6\%$, while among women it was $78.3\%$ (Table 1). Statistically significant differences depending on age among discharged and deceased patients and among men and women were not found. The results are presented as the arithmetic means ± standard deviations. Then, the influence of the cardiological history and some clinical indicators, such as transfer to the ICU, BMI, number of days from the onset of the disease from biobanking, and maximum CT on the severity of COVID-19 infection, was determined (Table 2). The results presented in Table 2 show that the transfer to the ICU, the number of days from the onset of the disease, and the CT index statistically significantly increased with an increased severity of the disease. The severity of COVID-19 infection was affected by pulmonary circulatory disorders, the incidence of patients with hypertension, coagulopathy, and iron deficiency anemia. A comparative analysis of IL-6 and Noas-2 levels was performed in patients with laboratory parameters such as APTT, AST, GFR, LDH, CRP, IL-6, sPLA2, D-dimer, procalcitonin, ferritin, hematocrit, lymphocytes, neutrophils, and eosinophils, depending on the severity of COVID-19 infection (Figure 1). The results shown in Figure 1 show that the levels of APTV, AST, CRP, LTK, IL-6, D-dimer, and ferritin, as well as the number of neutrophils, significantly increased in patients with mild and severe COVID-19 infections (Figure 1). On the contrary, hematocrit, GFR, lymphocyte, and eosinophil levels were statistically significantly reduced in these groups of patients compared to the values in patients with a mild infection. The PLA2 level also significantly increased in mild to moderate COVID-19 infections, but it did not change in patients with severe infections. These data on changes in the level of PLA2 in the blood show that this enzyme can be considered as an early marker of exacerbation of COVID-19 infection. IL-6 and PLA2 levels were also analyzed depending on the severity of the disease according to computed tomography (Figure 2). The results shown in Figure 2 show that the levels of IL-6 and PLA2 increase statistically significantly with an increase in the CT score. Moreover, the increase in PLA2 is almost 2 times higher than the increase in IL-6 at the beginning of the disease, when the CT score changes from 0 to 1. On the contrary, the level of IL-6 increases two-fold at the height of the disease, when the CT score increases from 2 to 3. In addition, the dependence of the PLA2 level on the severity of infection is also confirmed by the presence of a sufficiently high correlation coefficient between the two ($r = 0.311171$, $$p \leq 0.00069$$). An analysis of laboratory tests was carried out depending on the levels of IL-6 and sPLA-2. Patient samples were also divided into groups with high and low levels of IL-6 and PLA2. The criteria for dividing IL-6 and PLA2 into low- and high-level groups were the values of their first quartile (Q1); values below Q1 were assigned to the low-level group and all values above Q1 were assigned to the high-level group of analytes (Table 3 and Figure 3). The results shown in Table 3 show that the increased in the levels of APTT, AST, LDH, CRP, D-dimer, ferritin, and the number of neutrophils are statistically significantly different in groups with low and high concentrations of IL-6. On the contrary, hematocrit, GFR, lymphocyte, and eosinophil levels significantly decrease in the group of patients with medium and high concentrations of IL-6. The results shown in Table 3 show that the increase in the level of CRP and the decrease in lymphocytes are statistically significantly different in groups with low, medium, and high concentrations of PLA2. A statistically significant increase in LDH and D-dimer levels was observed between groups of patients with low and medium, and low and high concentrations of PLA2. An increase in APTT, ferritin, and the number of neutrophils and a decrease in GFR were statistically significantly observed between the groups of patients with low and high concentrations of PLA2. A statistically significant increase in AST levels was observed only between groups of patients with low and medium concentrations of PLA2. The number of eosinophils and hematocrit decreased between the groups of patients with low and high and medium and high severity of COVID-19 infection. Correlation coefficients were calculated between the levels of IL-6, sPLA2 concentrations, demographics, clinical parameters, and history of concomitant diseases (Table 4). The results in Table 4 show that the levels of IL-6 and PLA2 are statistically significantly correlated with the transfer of patients to the ICU, CT score, the presence in the anamnesis of uncomplicated diabetes mellitus, and iron deficiency anemia in patients. In addition, IL-6 showed a weak but significant correlation with weight. PLA2 also showed a weak but significant correlation with obesity, and the level of IL-6 correlates with the presence of pulmonary circulatory disorders, pulmonary artery pressure, peripheral vascular disorders, coagulopathy, renal insufficiency, rheumatoid arthritis, collagen, and vascular diseases. Correlations between the levels of PLA2 and IL-6 and the studied laboratory parameters were also analyzed (Table 5 and Figure 3). The results in Table 6 and Figure 3 show that the level of IL-6 is statistically significantly positively correlated with the levels of PLA2, ASIA, AST, DV, SKI, and the laboratory score, and is negatively correlated with the number of lymphocytes and the PAC index. The level of PLA2 also correlates positively with the level of IL-6, SKI, and the laboratory score, and negatively correlates with the number of lymphocytes and the PAC index. Moreover, the correlation values for IL-6 were higher than for sPLA2. At the final stage, the endpoint (outcome of COVID-19 infection) was analyzed depending on the severity, the levels of IL-6, PLA2, ARTT, AST, LDH, CRB, GFR, procalcitonin, D-dimer, ferritin, and hematocrit, the number of lymphocytes, leukocytes, neutrophils, and eosinophils, and the laboratory score (Table 6 and Table 7). The results presented in Table 7 show that the probability of death from a COVID-19 infection is greatly increased in patients with a severe course ($p \leq 0.0001$); high levels of IL-6, PLA2, ARTT, AST, LDH, CRB, d-dimer, ferritin, and neutrophil counts; and low levels of GFR, lymphocytes, and hematocrit. The dependence of the outcome of COVID-19 infections on the level of PLA2 is also confirmed by the presence of a sufficiently high correlation coefficient between them ($r = 0.310402$, $$p \leq 0.0000721$$). Finally, we calculated the odd ratio (OR) for the severity and the outcome of COVID-19 infections using our analytes (Figure 4). The results presented in Figure 4 show that increased levels of LDH, IL-6, and procalcitonin are the factors most predictive of the development of a severe or fatal COVID-19 infection in patients. Elevated levels of PLA2, ACT, D-dimer, APTT, and hemocrit also predicted a severe or fatal COVID-19 infection in patients, with odd ratios of 2.24, 5.46, 5.68, 4.71, 6.39 and 5.32, 4.14, 2.85, 4.51, 12.81, respectively. A combination of elevated levels of PLA2 and IL-6 increased the risk of a severe infection and death of the patients from COVID-19 by 20.0 and 9.68 times. ## 3. Discussion Secretion of PLA2-IIA aggravates damage to tissues and organs of the whole organism [17,22,30]. This may contribute to the severity and number of deaths due to COVID-19 infections [31]. Indeed, the results of [32,33] showed that in severe COVID-19 infections, plasma phospholipid levels decrease and the levels of lysophospholipids (lyso-PL), acylcarnitines, and non-esterified unsaturated fatty acids increase. These changes in the lipid profile indicate an increase in the activity of sPLA2 lysing membrane phospholipids in COVID-19 infections [31]. At the same time, increased levels of phosphatidylcholine 16:1_22:6 (AUC = 0.97), phosphatidylethanolamine 18:1_20:4 (AUC = 0.94), AK (AUC = 0.99), and oleic acid (AUC = 0.98) in 103 patients with COVID-19 infections correlated with the severity of the disease. There is a suppression of the biosynthesis of tyrosine, phenylalanine, tryptophan, and aminoacyl-tRNA [8]. In this study, it was found that sPLA2 levels increase in seriously ill patients, especially in the eventual case of death, and positively correlate with the severity and outcome of COVID-19 infections (Table 2, Table 5, Table 6 and Table 7, Figure 1, Figure 2, Figure 3 and Figure 4). These results are consistent with the data of a single study, which also showed that high levels of sPLA2-IIA in blood plasma correlate with its activity (r2 = 0.84, $$p \leq 1.2$$ × 10−13) and the severity of COVID-19 infection in 127 patients. In the group of patients who died from COVID-19, sPLA2-IIA levels could reach 1020 ng/mL, and were higher (89.3 ng/mL) than in those with severe (17.9 ng/mL) and mild (9.3 ng/mL) courses of the disease and those without coronavirus infection (8.9 ng/mL). Additionally, using a regression analysis model, sPLA2-IIA and urea nitrogen (BUN), at levels of 10 ng/mL and 16 mg/dL, respectively, were determined as the main clinical parameters for predicting mortality from COVID-19 infections with high accuracy (AUROC 0.93–1.0) and a sensitivity of $75.4\%$ [31]. In another study, sPLA2 levels were elevated (269 ± 137.3 ng/mL, $$p \leq 0.01$$) in the blood plasma of 14 children with severe COVID-19 infections compared with those with asymptomatic (2.0 ± 3 ng/mL) and mild (23.0 ng/mL) cases. At the same time, the level of sPLA2 was increased ($$p \leq 0.04$$) in patients in the acute phase of the disease (540 ± 510 ng/mL) compared with the recovery period (2 ± 1 ng/mL). No correlations were found between sPLA2 and CRB and D-dimer levels and the leukocyte count [34]. At the same time, positive correlations between sPLA2-IIA levels and NEWS2 indicators and glucose levels, and negative correlations between urea creatinine, glomerular filtration rate, hematocrit, and hemoglobin saturation were determined, which also confirms the dependence of sPLA2-IIA on the severity of COVID-19 infection [14,35]. In addition, the severity of COVID-19 infection is positively correlated with the level of viremia and the number of apoptotic cells expressing PS. Consequently, such cells will be destroyed by sPLA2, which further increases systemic inflammation [36]. Inhibition of sPLA2-induced cell damage can be considered as a new approach against uncontrolled inflammation and cytokine storms. This study also shows that the level of IL-6 increases in seriously ill patients and in the cases of unfavorable outcomes and it is correlated with the severity and death in patients (Table 2, Table 5, Table 6 and Table 7, Figure 1, Figure 2 and Figure 3). Our results are consistent with the research of other authors evaluating the prognostic significance of IL-6 in COVID-19 infections [37]. For example, in a retrospective single-center study conducted on 728 patients with COVID-19, the prognostic significance of elevated IL-6 levels for assessing mortality and a severe disease course was studied [38]. Using the logistic regression analysis of Cox in this study, the adjusted ratio of mortality risks and the severity of the disease in patients was evaluated. The authors concluded that elevated IL-6 levels may serve as an independent risk factor for severity and mortality in patients with COVID-19 [38]. A meta-analysis deserves attention, in which prognostic factors and the significance of elevated IL-6 levels in this pathology were determined in 1426 patients infected with COVID-19 [39]. It was shown that the best predictor of mortality or severe COVID-19 infection in patients is IL-6 (OR = 11.6460, $95\%$CI = 2.8123–48.2277), which predicts the onset of endpoints (outcomes) with an accuracy of $80.8\%$. Consequently, the level of IL-6 can serve as a prognostic marker of severe course, and especially where the outcome could be death, in patients with COVID-19 infections [39]. In an earlier study, we developed a model for assessing the risk of cytokine storms (CS) in 458 patients with COVID-19 infections [40]. The patients were divided into two groups, comparable in age. The first group consisted of 100 ($21.8\%$) patients with clinical and radiological features characterizing a stable course of the disease of moderate severity and the second group consisted of 358 ($78.2\%$) people with progressive moderate, severe, and extremely severe cases of the disease. When conducting a comparative analysis of clinical, instrumental, and laboratory data from the selected groups of patients, we found significant differences in the dynamics of the index on the NEWS scale, the absolute number of lymphocytes, and the levels of CRP, ferritin, D-dimer, and IL-6 between the groups, which can serve as the most important indicators characterizing the development of a CS. Using the method of constructing classification trees, the threshold levels for risk factors for the development of a CS were identified. We performed a comprehensive assessment of the risk of CSH by ranking the indicators, which, in accordance with the rank of prognostic significance obtained by the method of constructing “classification trees”, at the beginning of CSH therapy was as follows: dynamics of the index on the NEWS scale; blood IL-6 level above 23 pg/mL; blood CRP level equal to or above 50 mg/L; absolute number of lymphocytes less than 0.72 × 109/L; positive test result for coronavirus RNA (SARS-CoV-2); and an age of 40 years or older. These biomarkers can be used as criteria for assessing the risk of a CS. An increase in the frequency of CS cases correlates with an increase in the number of risk factors (correlation coefficient Rg = 0.91, $p \leq 0.001$). The following risk categories are identified for the practical application of our predictive model: category 1 (0–1 factor): the risk of CSH is practically absent; category 2 (2–3 factors): the risk of CSH increases sharply to $55\%$, a 35.5-fold increase compared to category 1; category 3 (4 or more factors): the risk of CSH reaches $96\%$, an 718-fold increase 718 compared to category 1. The results obtained are consistent with the assessment of risk factors for CS in COVID-19 by other authors [41,42] and allowed us to justify the choice of therapeutic tactics with early prescriptions of proactive anti-inflammatory therapy and anticoid plasma convalescents for patients with a high risk of CS. ## 4.1. Patients The retrospective cohort study included clinical and biochemical data obtained from 158 patients (98 men and 60 women aged 51.2 ± 11.6 years), who showed a positive test results for the presence of SARS-CoV-2 RNA by nucleic acid amplification in polymerase chain reaction (PCR), treated at the budget healthcare institution “City Hospital No. 40 of St. Petersburg Resort administrative district”, the boarding house “Zarya”, and “City Hospital No. 40” from 1 September 2020 to 15 October 2021. The average follow-up time of the clinical course was 10 days. The inclusion criteria were [1] age over 18 years and [2] a positive result of a PCR test for SARS-CoV-2 RNA. The exclusion criteria were [1] age under 18 years, [2] severe course of COVID-19 infection, [3] impaired consciousness, [4] unstable hemodynamics, [5] severe course of other somatic diseases, [6] severe course of oncological diseases, and [7] acute phase of other inflammatory and immune diseases. The main endpoint of the study was biological death. Additional endpoints were desaturation and transfer to the ICU. The study was approved by the Ethics Expert Council of St. Petersburg City Hospital No. 40 and No. 205, dated 2 November 2021, and was conducted in accordance with the general principles of observational research. We determined the severity of COVID-19 infection in our patients based on assessment of their clinical status using the NEWS-2 scale, the degree of lung involvement on CT, the blood level of serum and plasma biomarkers, and their laboratory score. The design of the study is presented in Figure 5. ## 4.2. Clinical Methods and Treatment of Patients with COVID-19 All patients were admitted for inpatient treatment in the emergency room to the infectious diseases department. It was mandatory to provide the entire volume of medical services in accordance with medical and economic standards and in accordance with the version of clinical recommendations in force at the time [4]. Data were collected from the patients, e.g., their epidemiological history, and the presence of clinical symptoms (cough, shortness of breath, fever, fever, weakness, loss of sense of smell and taste, and heaviness in the chest). We also conducted an objective examination of patients with an assessment of hemodynamic parameters, an assessment of the respiratory system (HR, HR, BP, and SpO2), and an assessment of the NEWS scale recommended for use for patients with COVID-19 [43]. On the day of admission or the next day, biomaterial was collected for laboratory tests and an electrocardiogram (ECG) was performed. Computed tomography (CT) of the chest organs was performed with an assessment of the form of the disease on a 4-digit scale without intravenous contrast enhancement (CT-1, CT-2, CT-3, and CT-4). The bilateral lower lobe; the peripheral, perivascular, multilobular character; numerous peripheral seals in the form of “frosted glass” with a rounded shape of various lengths; flattening of the interlobular interstitium in the type of a “cobblestone pavement”; areas of consolidation; symptoms of an air bronchogram, etc. [ 44], were mainly assessed and, if necessary, additional instrumental methods were used. According to the national recommendations for the diagnosis and treatment of COVID-19 [4], we used the following classification of COVID-19 according to severity:Mild course: body temperature < 38 °C, cough, weakness, and a sore throat. Absence of criteria for moderate and severe courses. Moderate course: body temperature > 38 °C, respiratory rate > 22/min, shortness of breath during physical exertion, changes in CT (radiography) typical of a viral lesion, SpO2 < $95\%$, and serum CRP > 10 mg/L.Severe course: respiratory rate > 30/min; SpO2 ≤ $93\%$; PaO2/FiO2 ≤ 300 mmHg; decreased level of consciousness; agitation; unstable hemodynamics (systolic blood pressure less than 90 mmHg or diastolic blood pressure less than 60 mmHg, diuresis less than 20 mL/h); changes in the lungs in CT (radiography) typical of a viral lesion; arterial blood lactate > 2 mmol/L; and qSOFA > 2 points. Extremely severe course: persistent febrile fever; ARDS; acute respiratory failure (ARF) with the need for respiratory support (invasive ventilation); septic shock; multiple organ failure; changes in the lungs on CT (X-ray) typical of a critical viral lesion or ARDS. Treatment of COVID-19 infections and its complications included antiviral drugs, prevention of hypercoagulation and DIC syndrome, symptomatic treatment, and oxygen therapy. In patients with a progressive course of the disease, for the prevention or treatment of a cytokine storm (CS), standard therapy was supplemented with the appointment of pathogen-induced plasma convalescents, anti-cytokine drugs, interleukin-6 receptor inhibitors (IL-6) (tocilizumab, olokizumab, and levilimab), IL-1 (kanakinumab and RH104), JAK kinases (tofacitinib, ruxolitinib, and baricitinib), tyrosine kinase Bcr–Abl (radotinib), and, in some cases, glucocorticosteroids [40]. According to the indications, staged respiratory therapy, antibacterial therapy, treatment of sepsis and septic shock, extracorporeal detoxification and hemocorrection, and extracorporeal membrane oxygenation were performed. A statement of biological death was made by the ICU doctor. The transfer of the patient in accordance with the indications specified in the clinical recommendations of the ICU was carried out and registered at the conclusion of the examination by the on-duty resuscitator. A decrease in blood saturation during dynamic observation was recorded by the medical staff and the attending physician: below $95\%$ in the air and the moment of supply of moistened oxygen through a mask or nasal cannulas in a volume of 5 L per minute, or until saturation of more than $95\%$ with a constant flow of oxygen. Desaturation was reported to the duty officer and attending physicians and noted in the observation sheet. The doctor gave the command to start oxygen insufflation. ## 4.3.1. Biochemical Blood Analysis A detailed clinical blood test was performed on all patients, which included an assessment of 24 laboratory parameters: dynamic analysis of the indicators of the acid-base state of the blood (concentrations of calcium ions, ionized calcium (Ca2+), sodium ions (Na+), potassium (K+), BE (Ecf) excess bases outside the cell fluid, pH, partial pressure of carbon dioxide (pCO2), and bicarbonate in plasma (HCO3−)), lactate, blood oxygen saturation, and partial pressure of oxygen (pO2). Biochemical blood analyses included the determination of alanine aminotransferase (ALT), aspartate aminotransferase (AST), total protein, albumin, total bilirubin, direct (bound), bilirubin, glucose, lactate dehydrogenase (LDH), creatinine, and urea by an automatic hemoanalyzer XN-1000 (Sysmex Corporation, Kobe, Japan) according to the operating instructions [45]. Coagulogram parameters were also measured, e.g., APTT, fibrinogen, prothrombin time, and D-dimer. For example, APTT was evaluated using a set of reagents, STA® Cephascreen® (Diagnostica Stago S.A.S, Asnières-sur-Seine, France), on an STA® analyzer according to the instructions [46]. The amounts of immunoglobulins (IgA, IgM, and IgG), CRP, ferritin, IL-6, and procalcitonin (PCT) were also assessed in the blood. Blood serum and plasma samples were collected in the morning on an empty stomach using vacutenirs containing Li-heparin separation gel, K2-EDTA, or K3-EDTA plasma. The blood was sent to the clinical diagnostic laboratory for examination within 1 h. The biochemical and clinical parameters and a history of comorbidities are presented in Table 8. ## 4.3.2. Evaluation of Interleukin-6 by Electrochemiluminescent Immunoassay The IL-6 levels in blood sera were determined using an Elecsys® IL-6 electrochemiluminescent immunoassay on a cobas e602 analyzer (Roche Diagnostics Corporation, Indianapolis, IN, USA) according to the method in [47]. This test takes 18 min to measure the concentration of IL-6 in the range of 1.5–5000 pg/mL in a sample volume of 30 µL. The immunoassay is based on the sandwich principle, when a blood sample is added to immobilized microparticles coated with streptavidin. After incubation, imaging is performed using biotinylated mouse monoclonal antibodies to IL-6 (0.9 mcg/mL) diluted in a phosphate buffer of 95 mmol/L, at pH 7.3 [48]. ## 4.3.3. Evaluation of Procalcitonin Using an Immunochromatographic Test Procalcitonin in serum and plasma was evaluated using the BRAHMS PCT-Q immunochromatographic test (BRAHMS, Hennigsdorf, Germany) according to the instructions [49]. Six drops of a blood sample were dropped into a round hole on a BRAHMS PCT-Q tablet using a pipette and incubated for 30 min at room temperature. After the specified time (maximum 45 min), the concentration range of the PCT sample was determined. At the beginning, a distinct appearance of the control band was visually recorded. Tests in which only the control band is observed were negative. In these tests, the concentration of PCT was less than 0.5 ng/mL. The tests in which the control and test strips were visualized were positive. The PCT concentration was determined by comparing the intensity of staining of the test strip with the colored stripes on the control card included in the kit. The BRAHMS PCT-Q express test obtain results with a 90–$92\%$ diagnostic sensitivity and a 92–$98\%$ specificity. ## 4.3.4. Determination of Creatinine, C-Reactive Protein, Aspartate Aminotransferase, Lactate Dehydrogenase, and Ferritin Creatinine, LDH, and ACT, as well as CRP and ferritin, were determined, respectively, using spectrophotometric and immunoturbidimetric methods and immunoassays of chemiluminescent microparticles (CMIA) on immunochemical analyzers (Abbott Architect cSystems™ (GMI, Ramsey, MN, USA) and Abbott AEROSET (Diamond Diagnostics Inc., Holliston, MA, USA)) according to the instructions [49,50,51,52,53,54]. ## 4.3.5. The Determination of D-Dimer Using Immunoturdodimetric Analysis The D-dimer was quantified in venous plasma samples using the STA®—Liatest® D-Di kit (Diagnostica Stago, Asnières-sur-Seine, France) for immunotourdodimetric analysis, according to the instructions [55]. This analysis allows one to determine the D-dimer with a sensitivity of 97.0–$100\%$ (91.6–$100\%$), a specificity of 53.3–$77\%$ (72.9–$81.9\%$), a negative predictive value (NPV) of $99.7\%$ (99.2–$100.0\%$), and a positive predictive value (PPV) of 25.5–$33.8\%$ (23.5–$40.5\%$). The plasma samples of patients were examined in undiluted form and loaded into an analyzer, on which a test was selected to evaluate the D-dimer by selecting an option on screen. The analysis of the D-dimer in the tested plasma was automatically performed by the analyzer at a wavelength of 540 nm immediately after loading the samples. The level of D-dimer (mcg/mL) in the sample of the tested plasma was displayed on the analyzer screen. D-dimer levels are expressed in initial equivalent fibrinogen units (FEU). By definition, one FEU represents the amount of fibrinogen initially present, which leads to the observed D-dimer level. The actual amount of D-dimer is about half of the FEU. ## 4.3.6. Assessment of the Level of Secretory Phospholipase A2 by Enzyme Immunoassay Phospholipase A2 in blood samples was determined using the sPLA2 kit (Cayman Chemical, Ann Arbor, MI, USA) for enzyme immunoassay based on the “sandwich” method of double antibodies, according to the instructions [56]. Each well of a 96-well microplate was coated with a monoclonal antibody of human sPLA2 type IIA. Such an antibody will bind to human sPLA2 type IIA located in the well. One hundred milliliters of control and biological samples were added to each well and incubated for 2 h at room temperature on a shaker. Then, the wells of the tablet were washed four times with a washing buffer and 100 µL of secondary HRP-conjugated mouse monoclonal antibodies specific to sPLA2 were added. These antibodies were used to visualize the captured sPLA2 type IIA. The samples were incubated for 1 h at room temperature on a shaker. Excess antibodies were washed 4 times with a washing buffer. The human sPLA2 type IIA concentration was determined by measuring the enzymatic activity of HRP with the addition of 100 µL of the chromogenic substrate 3,3′,5,5′-tetramethylbenzidine (TMB). The samples were then incubated for 30 min at room temperature in the dark. The formation of a blue color was monitored. The reaction was stopped by adding 100 µL of acid, and a bright yellow product was formed, which was measured on an ELISA reader at 450 nm. The intensity of this color is directly proportional to the amount of bound HRP-streptavidin conjugate and the concentration of human sPLA2 type IIA. ## 4.4. Genetic Methods In smears from the nasopharyngeal mucosa, the presence of RNA of the SARS-coronavirus-2 virus, as well as concomitant factors of mixed infection, i.e., RNA of influenza A and B, parainfluenza virus, respiratory syncytial virus, rhinoviruses, DNA of bokavirus and adenovirus, and metapneumovirus, was evaluated by RT-PCR. Sampling of smears was carried out with sterile swabs from both nasal entrances and the nasopharynx. Smears were transported in saline solution in sterile Eppendorf-type microprobes. ## 4.4.1. RNA Isolation The isolation of SARS-CoV-2 virus RNA from nasopharyngeal smears was carried out according to the instructions for the extraction reagent kit, GeneJET (Thermo Scientific, Waltham, MA, USA) RNA Purification kit, at the Magna Pure System station (Roche, Indianapolis, IN, USA) and KingFisher™ [57]. The RNA concentration was measured on a Quantus fluorimeter using a Quantifluorine RNA System (Promega, Madison, WI, USA) [58]. The RNA quality was assessed using the TapeStation 4200 system device and a Highly Sensitive RNA Video Recording Analysis kit [59]. The selection of positive samples (with Cq < 25) for further investigation was carried out using real-time PCR with one of the kits for the diagnosis of the SARS-CoV-2 virus. The excavation of samples into tablets was carried out with the use of the automated stations Xiril AG and Eppendorf epMotion 5075tc. In cases of poor RNA quality, its post-purification was carried out using the GeneJET kit (Thermofisher, Waltham, MA, USA). cDNA was made using a set of SuperScpipt, Mint-2 (Eurogene, Moscow, Russia), or a set for the synthesis of double-stranded cDNA Maxima H Minus (ThermoFisher, Waltham, MA, USA) [60,61]. ## 4.4.2. Polymerase Chain Reaction A RT-PCR analysis was performed using reagent kits for detecting coronavirus RNA SARS-coronavirus-2 in clinical material (produced by the Pasteur Research Institute of EM), GeneFinderTM, and COVID-19 plus RealAmp (OSANG Medicine Co. Ltd., Anyang-si, Korea) on CFX96 PCR devices in a real-time detection system (Biorad, Hercules, CA, USA) [62]. ## 4.5. Statistical Methods The results are presented as the arithmetic means ± standard deviation for the sample volume n (M ± m) and in terms of the median and the first quartile. The significance level was evaluated as * $p \leq 0.05$; $p \leq 0.01$; * $p \leq 0.001$; and **** $p \leq 0.0001.$ Statistical data processing (descriptive statistics and graphical analysis of data relationships from different tables) was performed using the GraphPad application on the Prism 8.01 platform. The frequency characteristics of qualitative indicators (gender, degree of form and pathological processes, and complaints) were evaluated using nonparametric methods, χ2. A Fisher’s exact test was used to compare mortality and disease severity in groups. Differences between groups were identified using the Kruskal–Wallis test and the Mann–Whitney test as a post hoc analysis [63]. ## 5. 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--- title: 'Monks: A Population at Risk for Liver Fluke and Skin-Penetrating Helminths' authors: - Nuttapon Ekobol - Sirintip Boonjaraspinyo - Atchara Artchayasawat - Thidarut Boonmars journal: Tropical Medicine and Infectious Disease year: 2023 pmcid: PMC10059027 doi: 10.3390/tropicalmed8030135 license: CC BY 4.0 --- # Monks: A Population at Risk for Liver Fluke and Skin-Penetrating Helminths ## Abstract Monks cannot cook received raw meat dishes and should walk barefoot while working. This population lacks both a survey of parasitic infection and a proper prevention and control policy. Five hundred and fourteen monks from the Ubolratana, Ban Haet, and Ban Phai Districts of Kh on Kaen Province were enrolled in this study. A stool container and questionnaire were collected from each study participant. Stool samples were processed by formalin ethyl acetate concentration and agar plate culture techniques. We then analyzed the results and risk factors to demonstrate associations. The prevalence of overall parasites, liver flukes, and skin-penetrating helminths were $28.8\%$, $11.1\%$, and $19.3\%$, respectively. Raw fish dish offerings were associated with opisthorchiasis (ORcrude 3.32; $95\%$ CI 1.53–7.20). The risk factors for skin-penetrating helminths were older age (ORcrude 5.02; $95\%$ CI 2.2–11.17), being a long-term ordinate (ORcrude 3.28; $95\%$ CI 1.15–9.34), smoking (ORcrude 2.03; $95\%$ CI 1.23–3.36), and chronic kidney disease with other underlying disease (ORcrude 20.7; $95\%$ CI 2.54–190.1). The protective factors for skin-penetrating helminths were secular education above primary education (ORcrude 0.41; $95\%$ CI 0.25–0.65) and having received health education about parasitic infection (ORcrude 0.47; $95\%$ CI 0.28–0.80). Wearing shoes at times other than alms work does not show a protective effect against skin-penetrating helminths (ORcrude 0.86; $95\%$ CI 0.51–1.46). These findings support the recommendation for a strict Rule of Discipline regarding raw meat ingestion and allowing shoes to be worn for protection against skin-penetrating helminths in high-risk situations. ## 1. Introduction Monks are a population at a unique risk of foodborne parasitic infection and soil-transmitted infection. Monks follow Rules of Discipline [1,2,3], which carry benefits but also risks for parasitic infection. Monks are protected from foodborne parasites by the Discipline of raw meat avoidance. The Buddha allows raw meat and fresh blood in the case of the treatment for demonic possession [1]. Raw meat and some wild animal meats are forbidden [1]. Meat has to be cooked by heat or fire. Water containing small live animals, such as copepods, cannot be used as drinking water [2]. The Lord Buddha allows the use of filter fabric to prevent this drinking water issue [3]. Contrarily, the Rules of Discipline about foods disallow the monks from cooking themselves or ingesting specific meats [1]. Monks cannot further cook raw or undercooked meats after the food is handed to them. Monks are not only at risk of foodborne parasitic infection, but also of soil-transmitted helminths. Infective eggs are ingested through contaminated foods or dirty hands. Penetrating larvae invade once in contact with the skin [4,5,6,7]. Similar to the risk of foodborne parasites in meat, monks cannot reject or rewash fresh vegetables after receiving them from villagers. The Rules of Discipline regarding allowed and prohibited shoes and wooden shoes for specific types of shoes and specific situations of shoe wearing also hinders skin-penetrating helminth prevention [8]. The Lord Buddha allows some shoes to be worn in specific conditions such as foot ulcers, wounds, or corns, as well as difficulty in traversing a route for pilgrimage [1]. Almost all monks have to beg for alms on bare feet, making them vulnerable to parasites penetrating the skin or foot injuries [1]. The exact prevalence of parasitic infection in monks is not well established. The lack of survey data and the migratory behavior of this population has resulted in a lack of screening, prevention, and control of parasitic infections [9]. The study in Nakhon Pathom Province found a parasite prevalence of $48.6\%$ among 173 monk participants [10]. The most common parasites were hookworms, Opisthorchis viverrini (O. viverrini), and Strongyloides stercoralis (S. stercoralis). Another study of parasitic infection in dogs and humans around the temple area with 204 humans ($58\%$ were monks or nuns) and 229 dogs found that prevalence of hookworm and strongyloidiasis in humans was $3.4\%$ and $2\%$, respectively [11]. The most recent study on monks’ health risk of parasitic infection in an urban area with a cement floor environment and some stray dogs and cats in the temple area found a $5.55\%$ prevalence of protozoal infections and did not find helminths in the 36 participants [9]. This study aimed to survey the prevalence of parasitic infection, health behavior risk, and associated factors of parasitic infection in monks from rural areas. The significant factors will be utilized to construct the prevention and control workflow of parasitic infection in monks. ## 2.1. Study Design and Setting This research was a community-based, cross-sectional study conducted from July 2021 to December 2021. The setting was Ubolratana District, Ban Haet District, and Ban Phai District of Khon Kaen Province, northeastern Thailand (Figure 1). Ban Phai is a large rural area. This district contains the Lawa Rapids and the Chi River in the northwestern part. Ban Haet is above Ban Phai and contains the Lawa Rapids and the Chi River in the southwestern part. Ubolratana District is located near the Ubolratana Dam and the Phong River. These 3 study areas reported the prevalence of opisthorchiasis in the general population in 2004, with $18.1\%$ in the Ubolratana District and $33\%$ in the Ban Phai District [12]. The report from 2020 was $7.7\%$ in Ban Haet District and $8.5\%$ in Ban Phai District [13]. None of the target areas had the highest prevalence of opisthorchiasis cases, but the relationship between communities and water reservoirs created a suitable habitat for liver fluke. According to a northeastern Thailand survey from 2016 to 2017, metacercariae infect $50\%$ of cyprinid fish [14]. ## 2.2. Study Population The monk population in Khon Kaen Province of Thailand is the target population for developing a model of liver fluke prevention and control strategies. Monks that were over 20 years old were included; monks that were on a treatment for parasitic infection or that could not collect stool for examination were excluded. All monk participants were informed about the study objective, benefits, and risks. The consent form was prepared and signed by each participant. The Human Ethics Committee of Khon Kaen University approved all protocols (Reference No. HE641207). ## 2.3. Sample Size Estimation The sample size was calculated based on the finite single population proportion [15], an assumed proportion of 0.055 from a previous study [9], an acceptable difference of 0.011 ($20\%$ of prevalence), and a $95\%$ confidence interval. The total monk population from the 3 study areas was approximately 880 monks (using data from the Khon Kaen Buddhist Office before the rain-retreat survey). The estimated sample size was 575 participants. ## 2.4. Survey of Parasitic Infection and Data Collection The self-administered questionnaires and plastic containers were distributed before stool collection. The participants were informed about the stool collection method and completed the questionnaires. Signed consent was given. All questionnaires and stool containers were collected the following morning. The completion of questionnaires was reviewed on site. The fresh morning stool containers were placed in an ice box and transferred to the laboratory room at the Department of Parasitology, Faculty of Medicine, Khon Kaen University. The stool container was opened under the biosafety hood. Three grams of fresh stool was placed on nutrient agar for agar plate culture. The agar plate was incubated at 30 °C for 7 days. The rest of the stool sample was preserved by adding $10\%$ formalin. Stool concentration was determined by the formalin ethyl acetate concentration technique [16,17]. The stool sediments were examined under a compound microscope and the agar plate was examined under a stereomicroscope on day 3, day 5, and day 7 of culture. The positive culture plate by stereomicroscope and the plate at day 7 were rinsed using 10 mL of $10\%$ formalin, and the solution was centrifuged at 2500 rpm for 5 min. The sediment was examined for S. stercoralis and hookworm infection under a compound microscope. The agreement of positivity for parasite samples was confirmed by two parasitologists. All infected participants were treated with anti-parasitic drugs and received education about re-infection. ## 2.5. The Questionnaire The questionnaire for monks consisted of 3 parts. The first part assessed age, ordinate duration, and education (secular and dharma education). The second part assessed health status and history of parasitic infection. The last part assessed health risk behavior for parasitic infection. Age was classified into two groups: <40 years old as young adults and ≥40 years old as middle-aged and senior adults. Secular education was classified as no education to primary education and above primary education. Dharma education was classified as dharma education of advanced level and dharma education lower than advanced level. The duration of monkhood was classified as short-term ordinate (≤1 year) and long-term ordinate (>1 year). Smoking was classified into two groups: no smoking and ex- or current smoking. Alcohol drinking was classified based on history of drinking before monkhood. Anthelmintic drug use was collected as drug use per year and then classified into two groups: no drug use and drug use at least one time per year. The use of non-steroidal anti-inflammatory drugs (NSAIDs) and illegal combined drugs was also collected. Illegal combined drugs are the unknown re-packaging of many types of drugs without drug label by a local shop. This combination drug may contain acetaminophen, 1–3 types of NSAIDs, opioid analgesics, corticosteroids, and some vitamins. Underlying diseases were collected and classified with concern about the effects from multiple-comorbid disease on skin-penetrating helminth infection into chronic kidney disease with other underlying diseases and other underlying disease groups. Offerings of raw meat by the villagers were assessed by the type of meat. Raw meat dishes were reclassified according to the types of raw meat as beef, pork, shrimp, fish, and snail. The self-hygiene questionnaire was composed of a question about drinking water (bucket water, natural water, and tap water), eating a meal with one’s hands, eating freshly cooked food, wearing shoes at other times outside of alms work, toilet use, ground soil defecation, nail hygiene, and hand washing (before eating, after toilet use, after soil contact, and after animal contact). These behaviors were assessed by the frequency of the practice and classified as always practicing and not practicing. ## 2.6. Statistical Analysis The demographic data were presented as frequencies and percentages. The stool examination result was classified as an infected case by the positive finding of at least one parasite and analyzed for prevalence. Skin-penetrating helminths were classified by positive S. stercoralis and/or hookworm findings. The association between risk factors and parasitic infections was analyzed by Pearson’s chi-squared test and binary logistic regression. A p-value less than 0.05 indicated statistical significance. The analysis was performed by SPSS version 28.0.1.0 (IBM Corp., Armonk, NY, USA). ## 3.1. Demographic Characteristics Five hundred and fourteen monks participated, as shown in Table 1, and the response rate was $89.4\%$. The mean age and standard deviation were 52.4 ± 17.9 years. Most of the participants ($88.7\%$) were long-term ordinates. Forty-seven percent of participants completed only primary education, but half of the participants completed the Dharma scholar advanced level ($53\%$). Ban Phai District had the highest number of monk participants ($62.9\%$). The smallest participating area was the Ubolratana District ($11.3\%$) due to the district lockdown to prevent the spread of the SARS-CoV-2 virus. Nearly half of the participants had an underlying disease ($45.6\%$). The common underlying diseases were hypertension ($12.6\%$), diabetes ($11.5\%$), and allergy ($9.9\%$). Less than half had previously been educated about parasitic infection, and one third had previously been examined for parasitic infection. Most participants ($72.1\%$) had previous anthelmintic drug use at least one time per year. The experience of receiving raw meat after the ordinate was reported by $79.8\%$ of participants. The most common groups of raw meat that the villagers presented to monks were raw beef dishes ($68.8\%$), raw fish dishes ($67.4\%$), and raw shrimp dishes ($57.5\%$). ## 3.2. Prevalence of Parasitic Infection in Monks The overall prevalence of parasitic infection was $28.8\%$ ($95\%$ CI 25.0–$32.8\%$), as shown in Table 2. Single infection was $23.3\%$ and multi-infection was $5.5\%$. Strongyloidiasis was the most common infection, with a prevalence of $15.6\%$. Liver fluke infection had $11.1\%$ prevalence and hookworm infection had $7\%$ prevalence. Protozoal infection prevalence was very low, from 0.2 to $0.8\%$. The locations of the temples with prevalent parasites is shown in Figure 2. ## 3.3. Pre-Monkhood Raw Fish Ingestion and Offering Raw Fish Dishes to Monks Associated with Liver Fluke Infection There were 57 cases of liver fluke-infected monks and almost all cases ($95.5\%$, $\frac{42}{44}$, missing data from 13 cases) had a history of raw fish ingestion before monkhood. Eighty-six percent of opisthorchiasis cases reported having been offered raw fish dishes after being ordinated (Figure 3). Being given at least one type of raw fish dish was associated with liver fluke infection in monks (Table 3). ## 3.4. The Forbidden Footwear Rule Assigns a Risk for Skin-Penetrating Helminth Infection to Monks The prevalence of skin-penetrating helminths in monks was $19.3\%$. The alms work with bare feet is shown in Figure 4. Wearing shoes at a time other than alms work did not show a protective effect from skin-penetrating helminths. The prevalence of infection for always wearing shoes versus not always wearing shoes was $18.6\%$ and $21\%$, respectively (p-value of 0.579). ## 3.5. Defecating on Ground Soil While Performing Off-Site Work Spread Liver Fluke and Skin-Penetrating Helminths Forty percent of monks defecated on ground soil while performing off-site work. Twenty-eight percent were parasite cases, $8.7\%$ of which were opisthorchiasis cases and $20.1\%$ of which were skin-penetrating helminth cases. Nevertheless, this practice had no statistically significant link with skin-penetrating helminths in monks (p-value of 0.940). ## 3.6.1. Opisthorchiasis Receiving at least one type of raw fish dish was the only significant factor for liver fluke infection in monkhood (ORcrude 3.32; 95 %CI 1.53–7.20). Age group, smoking behavior, history of pre-monkhood alcohol drinking, anthelmintic drug use at least one time per year, and education about parasitic infection did not show a difference in opisthorchiasis prevalence (Table 3). ## 3.6.2. Skin-Penetrating Helminth The factors that increased the risk of skin-penetrating helminths were older age group (ORcrude 5.02; $95\%$ CI 2.26–11.17), long-term ordinate (ORcrude 3.28; $95\%$ CI 1.15–9.34), ex-smoking or current smoking (ORcrude 2.03; $95\%$ CI 1.20–3.29), and chronic kidney disease with other underlying disease (ORcrude 20.7; $95\%$ CI 2.54–190.1) (Table 4). The factors that decreased risk were secular education above primary education (ORcrude 0.41; $95\%$ CI 0.25–0.65) and having received education about parasitic infection (ORcrude 0.47; $95\%$ CI 0.28–0.80). The use of NSAIDs or illegal combined drugs, alcohol drinking before monkhood, wearing shoes outside (except during alms work), and anthelmintic drug use at least one time per year did not show any association (Table 4). ## 4. Discussion This study was the first scientific report on the association between offering traditional raw fish dishes to monks and liver fluke infection, and between the protective effect of shoes on skin-penetrating helminth and shoes prohibiting rules during alms work. Our study found the prevalence of overall parasitic infection ($28.8\%$) to be lower than the prevalence that was reported in 1989 ($48.6\%$) [10]. Improving health education about parasitic infection and sanitation may lower the risk of infection. However, the monks in our study live in a rural community with a higher risk of parasitic infection by traditional health behavior and a higher chance of soil contact; thus, the prevalence was higher than previous studies in urban monks [9]. Opisthorchiasis was the second most common parasitic infection in monks. The infection and raw fish exposure may continue from secular status to monk status. Almost all opisthorchiasis cases ingested raw fish in traditional foods before being ordinated [18]. This prevalence ($11.1\%$) of liver fluke was lower than the average northeastern Thailand prevalence from 2013 to 2019 of $32.4\%$, as reported by Thinkhamrop et al. [ 19], but slightly higher than the previous survey of the general population in 2020: $7.75\%$ from Ban Haet District and $8.48\%$ from Ban Phai District [13]. The distinct prevalence of liver fluke infection in northeastern Thailand changed as a result of the intensive cholangiocarcinoma screening and care program (CASCAP) [20]. Raw beef salad was the most common raw meat dish offered to monks, but the prevalence of taeniasis was low. The low number of observed stool taeniid eggs may have been caused by detached and migratory gravid proglottids that were viable and not ruptured to release the eggs [21]. Another factor is the modern beef production system, which prevents cattle from ingesting taeniid eggs. However, this beef product is only available in the mid-value or premium beef market. Traditional beef markets sell beef products from native cattle reared by a local farm. Cattle feed or graze on communal land, roadside, or leftover byproducts from cultivated areas. This practice increases the risk of bovine cysticercosis [22]. Unfortunately, there are no reports on cattle cysticercosis, the occurrence of cysticercus by beef inspection from slaughterhouses, or market beef product surveys in Thailand [23]. The distribution of raw meat is still practiced in the temple community, and opisthorchiasis-positive monks received raw fish dish offerings. Giving raw fish dishes to monks causes reinfection or new infection. Risk factors include the contamination or unknown cooking of a freshwater fish dish, lack of proper food inspection, and lack of awareness of hygienic food preparation before offering those foods to monks. Insufficient knowledge about parasitic infection and the familiarity and culture of raw meat distribution can influence the offering of raw fish to monks [18,24]. Northeastern Thailand villagers (especially senior adults) offered personally cooked foods to monks and kept the rest to themselves [25]. Raw fish may be present in this case due to their fresh, sweet, soft, and sticky texture, as well as its peak taste [26]. After the monk inspects and takes offered foods, the leftover foods are shared among the participating villagers and taken back to their families. If raw fish dishes are present at this social gathering, it is difficult to avoid distribution to monks and other villagers [18]. Opportunities to address this risk are the cooperation of the Office of Buddhism and civil society to implement two levels to prevent foodborne parasitic infection. The first level involves implementing a training course for villagers to cook safe food for monks and food inspection training for monk attendants. The second level implements education about parasitic infection to newly ordinated monks and those who are health volunteers (the Kilanupatthaka). Skin-penetrating helminth was the most common soil-transmitted infection in monks. This finding may be caused by their living in the endemic area and their risk for soil contact due to the footwear prohibition rule. This rule assigns easy care to monks in the context of poor socioeconomic communities in the Buddhist era [3]. During this era, shoes were considered luxurious and extravagant, made an annoying sound (wooden shoes in particular), and shoe-wearing monks were accused of having a lustful desire. Monks should not spend time making shoes and should not decorate shoes [1]. This rule is simple for the monk but increases the risk of skin contact with contaminated soil. Our prevalence finding was similar to the prevalence of $15.2\%$ strongyloidiasis in the general population reported in a previous nearby study area in the Nam Phong and Ubolratana Districts of Khon Kaen Province [27]. Moreover, being a long-term ordinate indicated more exposure to contaminated soil and increased the risk of skin-penetrating helminth infection. Alms work results in out-of-temple ground soil contact with the unknown risk of contamination from ground to ground, especially on damp soil and rainy days. Rural villages lack proper water drainage or wastewater irrigation systems. Wastewater soaks the road and sidewalks with eggs and larvae [4]. Wearing shoes for protection outside of alms work does not show a protective effect against this infection. Footwear provides personal protection against soil-transmitted helminths and other neglected tropical diseases [28]. Wearing shoes is the simplest, most effective, and lowest cost method for preventing infection [29]. Ordinary shoes are not luxury equipment in the current socioeconomic context, and monks do not need to spend additional time making shoes for themselves. Wearing this personal protective equipment should be the right of any person. Additionally, monks are spiritual leaders, and wearing shoes in the correct situations may promote public health policy to prevent skin-penetrating helminths [30]. This topic is critical for encouraging the monks’ practice to be more reasonable and safe while preserving their Rules of the Discipline. Theravada Buddhism has adhered to preserving all the rules in the Basket of the Discipline. Monks should not legislate discipline rules that the Lord Buddha did not legislate and should not withdraw any of the discipline rules [1,31]. Revisions or changes to the rules are nearly impossible, but a new method may be to interpret the rules to be more compatible with modern health practice. The older age group showed more prevalence of skin-penetrating helminths. This finding is similar to the study of soil-transmitted helminth in the elderly [32]. More advanced age in the sub-group of the elderly showed a higher prevalence of hookworms, S. stercoralis, and Trichuris trichiura. Adaptive immunity worked differently in the older age group by changing the proportions of T cells, immunoglobulins, and interleukins in a mouse model with filarial worm infection [33]. A decline in the immune response to helminth for both innate and adaptive immunity was also described in another study in the elder age group in combination with the effect of comorbidity [34]. Our study found an association between skin-penetrating helminths and chronic kidney disease. Strongyloidiasis patients had reduced gut microbiota diversity. Shifting of the gut microbial profile towards pathogenic bacteria is associated with a lower GFR or chronic kidney disease [35]. A similar result found in a study of strongyloidiasis and type 2 diabetes with renal complication parameters showed that a significant GFR difference for no diabetes with negative S. stercoralis was higher than that for no diabetes with positive S. stercoralis [27]. There was no Rule of Discipline to prohibit tobacco smoking. This substance threatens health status but does not have an effect on consciousness and was not banned like alcohol drinking [2]. Tobacco smoking has systemic effects on many organs and shortens the life span of the smoker, especially via cardiovascular events and chronic obstructive pulmonary disease [36,37]. Both current and ex-smoking participants were associated with skin-penetrating helminths infection, but these results are a combination of complex mechanisms. Environmental tobacco smoking or prenatal exposure may affect innate immunity to induce airway inflammation that is hyper-responsive and shifts towards a Th2 response, which may benefit the control of pulmonary helminth infection [38]. Another supporting study shows a correlation between tobacco smoking and decreased worm burden for intestinal helminth infection [39]. On the other hand, immune activation from tobacco smoking is too potent, eventually exhausting and weakening the protective effects of both innate and adaptive immunity [40]. S. stercoralis larvae, as well as smoking, contain mechanisms that suppress the pulmonary immune response via shedding cuticle and excretory secretory products [41]. Further investigation of the tobacco smoking effect on skin-penetrating helminths is necessary. Moreover, social influences on cigarette use in monks may result from the pressure from other monks or may be used to relieve stress [42,43]. The monks’ off-site work carries an increased risk for parasitic infection. Villagers may invite monks for community religious rituals. Serving raw meat or raw fish dishes is common in these situations. Pilgrimage is another kind of off-site work, and traveling to a remote area increases the risk of parasitic infection. Limited food choices increase the chance of raw meat being received from local villagers. Pilgrimage to wilderness area benefit skin-penetrating helminth prevention by allowing monks to abstain from the forbidden footwear rule and wear used multilayer shoes. However, remote areas lack restrooms, so monks must defecate on the ground soil, dispersing parasite eggs and larvae to new ground. Yet, there was no association between this practice and infection in monks. Outdoor toilet equipment is required to cut the parasitic life cycle. Screening programs for newly ordinated monks after they return from pilgrimage will benefit parasitic control. Secular education above primary education showed a lower prevalence of skin-penetrating helminth. There are healthy school projects in Thailand to develop health literacy and enhance the skill of self-hygiene in school children [44]. Incomplete or lack of primary education results in insufficient education about parasitic infection. Education about parasitic infection is the important factor for primary and secondary prevention. The received intervention package showed additive prevention for the re-infection of S. stercoralis [45]. Either way, some monks reported behavioral changes after receiving education about parasitic infection, such as minimizing soil contact and always wearing shoes in the temple area. Some temples modified the area for walking meditation to prevent soil contact by coverage with a plastic sheet. The limitation of this study was the cross-sectional design with a single stool sampling. A cross-sectional study has limited power to demonstrate direct causes and effects. Monks have migratory behavior and only complied with a single stool sampling. Measuring the exact raw meat ingestion data by monks violates the Rules of the Discipline. Therefore, we only reported the choices of raw meat offerings. ## 5. Conclusions Monks are a population at high risk for parasitic infection due to traditional raw fish offerings and the Rules of Discipline prohibiting footwear. Strictly applying rules about raw meat ingestion, providing education about parasitic infection, and reinterpreting the footwear prohibition Rule of Discipline to support modern health practices may reduce this risk. ## References 1. 1. Mahamakut Buddhist University The Three Basket and Commentary Translation-Basket of the Discipline, Volume 5Mahamakut buddhist University Printing HouseBangkok, Thailand19911316713–22, 65, 97–101, 130–135, 167. 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--- title: Probiotic-Fermented Camel Milk Attenuates Neurodegenerative Symptoms via SOX5/miR-218 Axis Orchestration in Mouse Models authors: - Ashraf Khalifa - Hairul Islam Mohamed Ibrahim - Abdullah Sheikh - Hany Ezzat Khalil journal: Pharmaceuticals year: 2023 pmcid: PMC10059028 doi: 10.3390/ph16030357 license: CC BY 4.0 --- # Probiotic-Fermented Camel Milk Attenuates Neurodegenerative Symptoms via SOX5/miR-218 Axis Orchestration in Mouse Models ## Abstract Multiple sclerosis is an autoimmune-mediated myelin damage disorder in the central nervous system that is widespread among neurological patients. It has been demonstrated that several genetic and epigenetic factors control autoimmune encephalomyelitis (EAE), a murine model of MS, through CD4+ T-cell population quantity. Alterations in the gut microbiota influence neuroprotectiveness via unexplored mechanisms. In this study, the ameliorative effect of Bacillus amyloliquefaciens fermented in camel milk (BEY) on an autoimmune-mediated neurodegenerative model using myelin oligodendrocyte glycoprotein/complete fraud adjuvant/pertussis toxin (MCP)-immunized C57BL6j mice is investigated. Anti-inflammatory activity was confirmed in the in vitro cell model, and inflammatory cytokines interleukins IL17 (from EAE 311 to BEY 227 pg/mL), IL6 (from EAE 103 to BEY 65 pg/mL), IFNγ (from EAE 423 to BEY 243 pg/mL) and TGFβ (from EAE 74 to BEY 133 pg/mL) were significantly reduced in BEY-treated mice. The epigenetic factor miR-218-5P was identified and confirmed its mRNA target SOX-5 using in silico tools and expression techniques, suggesting SOX5/miR-218-5p could serve as an exclusive diagnostic marker for MS. Furthermore, BEY improved the short-chain fatty acids, in particular butyrate (from 0.57 to 0.85 µM) and caproic (from 0.64 to 1.33 µM) acids, in the MCP mouse group. BEY treatment significantly regulated the expression of inflammatory transcripts in EAE mice and upregulated neuroprotective markers such as neurexin (from 0.65- to 1.22-fold) ($p \leq 0.05$), vascular endothelial adhesion molecules (from 0.41- to 0.76-fold) and myelin-binding protein (from 0.46- to 0.89-fold) ($p \leq 0.03$). These findings suggest that BEY could be a promising clinical approach for the curative treatment of neurodegenerative diseases and could promote the use of probiotic food as medicine. ## 1. Introduction Recently, extensive studies have been conducted on the effect of fermented food products on human health, including probiotics (PBT) and fermented dairy products, as either prophylactic or therapeutic nutraceuticals [1]. PBTs are considered one of the food supplements that are produced using non-pathogenic microorganisms that improve and restore gut commensal microbiomes (GMs) [2]. Reports evidenced that PBTs could potentially improve a variety of gastrointestinal disorders and improve health [3]. Daily consumption of PBTs demonstrated a modulation of the immune system, leading to improvements in health, including a reduction in the complications of multiple sclerosis (MS) [3,4,5]. PBT bacteria include Lactobacilli, Bacillus, Bifidobacteria and Enterococci [6]. Several studies have shown the ameliorative properties of PBTs as food supplements via the regulation of imbalanced GM [7]. Moreover, PBTs have demonstrated alleviation of immuno-inflammatory issues associated with multiple health conditions, including diabetes, inflammatory bowel syndrome (IBS), neuro-inflammatory illnesses and MS [2,8,9,10]. Currently, live PBT cultures are part of fermented dairy products. Milk, including camel milk (CM), is rich in Lactic acid bacteria and Bifidobacteria, which makes it a perfect medium for the growth of PBTs [11]. CM is a natural endowment that is gifted with very beneficial effects on human health by maintaining the appropriate functionality of the gastrointestinal mucosa and toning the inflammatory mediators in the gut [12]. CM has demonstrated a unique composition by being rich in essential contents for the growth of PBTs and helping them to produce a plethora of biologically active metabolites [13]. Moreover, fresh CM has alleviated the pro-inflammatory and necrotic mediators at the level of the gut [14]. Fermented CM is presumed to have exceptional nutraceutical and immunomodulatory characteristics due to the presence of a significant diversity of bioactive metabolites, including beneficial health-promoting peptides and bacteria, when compared with fresh CM [13,15]. MS is a complex neurological syndrome leading to inflammation as well as demyelination of the central nervous system, accompanied by different levels of injury to neurons [16]. The exact pathological events associated with the development of MS remain unclear. However, the MS pathology cascade could be attributed to multiple factors, including damage to and/or loss of oligodendrocytes and neurons [17,18,19]. Demyelination associated with axonal injury is considered one of the most prominent causes of neurologically related MS that could lead to certain limitations in disability [20]. Consequently, the discovery of new medical strategies with immunomodulatory and anti-inflammatory potential could be helpful to control MS. GM consists of colonies of microorganisms forming a complex mutually dynamic system in the human gut that plays essential metabolic and immune regulatory roles [21]. GM–host interactions have demonstrated axial correlations between various body systems and the brain [22,23]. Interestingly, GM is able to support the host with bio-metabolites that trigger immune and inflammatory responses through their communications with the central nervous system, which was evidenced via the secretion of bio-polysaccharides by Bacillus fragilis, indicating intestinal mucosa/brain-associated interaction [24]. Moreover, GM can regulate the release of cellular cytokines and chemokines. Accordingly, GM may exhibit a characteristic promoting action on the release of host neuro-mediators. This type of distinct mutual loop between GM and the host could indirectly induce an immune-regulatory association and result in the expression of neuroactive and bio-amine mediators by the host [25]. Consequently, this signaling pathway will improve the impairments associated with MS [26]. Studies have demonstrated that SCFAs (short-chain fatty acids) are presumed to modulate host immunity and reduce inflammation, leading to an improvement in colon health [27,28,29]. GM is considered one of the substantial initiators of the fermentation process that is required to convert indigestible carbohydrates into SCFAs. Studies have also reported GM-immune system-associated mechanisms with various modulations of the host microRNAs in an animal model of MS and experimental autoimmune encephalomyelitis (EAE) [30,31,32]. In addition, the genomic interactions between GM and host have not been fully explored; hence, the associated molecular patterns need to be elucidated [33]. The current approach highlights the importance of fermented dairy products as a source of PBTs. Based on the fact that fermented CM is reputed to contain a variety of bioactive nutrients that have demonstrated many biological activities [34], the conducted preventive study highlighted the importance of Bacillus amyloliquefaciens (BA) enriched with CM on the expression of pro-inflammatory cytokines in induced IBS in a mouse model [12]. Interestingly, fermented CM supplemented with BA (BEY) serves as a PBT dairy product and could be a therapy for the cure of MS-associated disorders. Therefore, based on the concept that the regulation of GM can play a crucial role in MS pathophysiology, it is beneficial to explore and elucidate the possible modulatory mechanisms exerted by BEY to cure the symptoms associated with MS. To evaluate the potential curative strategy to manage dysfunctions accompanied by MS, this study was conducted using an MCP-immunized C57BL6j mouse model. Specifically, the pattern of inflammatory markers, immunoblot, qPCR, pathological scores and severity of the disease in treated and untreated mice were assessed. ## 2. Results In our previous work, we demonstrated that the sensory quality of BEY was significantly improved compared to traditional cow’s milk yogurt. For this reason, BEY was further investigated as a curative PBT formulation for EAE. ## 2.1. The Effect of BEY on SOX5 Regulation in MOG-Induced Splenocytes Naïve mouse spleens were excised and mononuclear cells were isolated and cultured for 4 h in the presence of 2 ng/mL of myelin oligodendrocyte glycoprotein (MOG) 35–55. Transcriptional factors regulate the polarization of inflammatory cell differentiation and maturation. In this study, the effect of BEY on the regulation of SRY-box transcription factor 5 (SOX5) in MOG-induced splenocytes was examined. The data are presented in Figure 1. As can be seen in Figure 1A,B, SOX-5 facilitates the looping between lymphoid gene promoters to promote EAE pathogenesis and Th17 differentiation. BEY-treated splenocytes showed a significant reduction (from 2.03- to 1.3-fold) in SOX5 protein expression compared to MOG-treated cells at 10 × 7.5 cfu of BA-inoculated BEY. Furthermore, the proliferation level of BEY-treated splenocytes was substantially increased compared to that of MOG-treated cells (Figure 1C). MOG-stimulated splenocytes enhanced the expression levels of inflammatory cytokines, whereas the BEY treatment significantly reduced these inflammatory markers ($p \leq 0.04$). In addition, the level of interleukin-17 (IL-17) and IFN-γ released from Th17 cells was remarkably decreased in the BEY-treated cells (Figure 1D). Expectedly, the reciprocal regulation of interferon gamma (IFN-γ) and transforming growth factor beta (TGF-β) was noted in BEY-treated MOG-challenged splenocytes (Figure 1D). However, the interleukin-6 (IL-6) cytokine in the BEY-treated group exhibited an insignificant change compared to the MOG-treated cells. ## 2.2. Upregulation of the Epigenetic Factors (miRNA218-5p) by BEY Treatment SOX5 expression was confirmed in splenocytes, and a set of SOX5 miRNA inhibitors (miR132, miR21 and miR218) was selected based on target scan tools. The virtual binding of miRNAs was selected for further molecular analysis. To validate and calibrate the expression levels of randomly chosen miRNAs along with the U6 internal control, they were analyzed in qRT-PCR (quantitative Real-Time PCR). The miRNAs were defined by a premature and mature similarity index, with fewer loop and hairpin nucleotides exposed in Figure 2A. The expression of miRNA 218-5p was evaluated, and we found that the BEY (10 Log 7.5) inoculum significantly upregulated miR218 in MCP-stimulated cells (Figure 2B). The promoter region of SOX5 at 71–7 base pairs complexed with miR-218 was confirmed (shown in Figure 2C). Taken together, the results of miR218 validation using qRT-PCR were confirmed in further experiments. ## 2.3. Pathology of EAE C57BL6j Mice Treated with BEY Clinical scores and disease indicators were used to quantify the degree to which physiological symptoms represented a recovery in the MS model. In this investigation, an in vivo mouse model of multiple sclerosis was used to assess whether BEY supplementation could reverse the demyelination and paralysis signs seen in these animals. EAE-disease mice displayed severe MS clinical signs, including tail and hind limb paralysis, after 15 days of MCP immunization. The symptoms peaked after the 18th day and persisted until the end of the experiment (Figure 3A). The treatment of EAE mice with BEY resulted in significant symptom recovery and attenuated the paralysis symptoms after the 20th day of MCP immunization. After the 24th day of observation, the clinical symptoms were potentially reduced with BEY treatment. These results were further confirmed through body weight measurements, tissue pathological features and cytokine expression levels. BEY improved the body weight of EAE mice from 14 to 22 g (Figure 3B). ## 2.4. The Positive Effect of BEY on EAE Pathology in C57Bl6j Mice BEY improved the histopathological conditions in the CNS of EAE mice (Figure 4). The histopathological observations of the peripheral nervous system (white and gray matter), the myelin damage (from 3.92-fold to 2.1-fold) and the T-cell infiltration were obviously reduced by the administration of BEY to the MCP-immunized animal model (Figure 4A). Moreover, the inflammatory damage level ($p \leq 0.03$) was significantly decreased and the pathophysiology score was alleviated in BEY-treated mice. Interestingly, a substantial decrease in neutrophil infiltration was observed in the spinal cord of BEY-treated EAE mice (Figure 4B). Furthermore, the immunofluorescence score of the myelin-binding protein was markedly increased (from 0.18- to 0.42-fold) in EAE mice treated with BEY (Figure 4C,D). Therefore, BEY treatment improved the kinetic function and ameliorated the infiltration and oxidative damage of the myelin sheath in the spinal cords of EAE mice. ## 2.5. Effect of BEY on Biochemical and Inflammatory Markers in MCP-Induced EAE Mice The effect of BEY on the SCFAs of EAE mice was quantified, and the data are displayed in Figure 5A. Two SCFAs, butyric and caproic acids, were substantially upregulated in BEY-treated mice compared to the other EAE group (Figure 5A). The level of butyric acid was increased from 0.55 μM to 0.95 μM in BEY-treated spinal cord tissue. A similar pattern was observed in the caproic acid levels. These results showed that BEY could attenuate EAE symptoms via the activation of SCFAs. The influence of BEY on the inflammatory cytokines (IL-17, IL-6, IFN-γ and TGF-β) in MCP-induced EAE mice was further studied (Figure 5B). Unlike TGF-β, IL-17, IL-6 and IFN-γ levels were significantly higher in the EAE group (420 ± 12 pg/mL, 255.1 ± 9.0 and 680 ± 28 pg/mL, respectively) compared to the BEY-administered EAE mouse group (271.1 ±11.3, 199 ± 18 and 490 ± 13.0 pg/mg, respectively) ($p \leq 0.02$). An insignificant activation of TGF-β was observed in the BEY-treated group (from 181.2 ± 11 to 199 ± 8.0 pg/mL) ($p \leq 0.06$). Comparable results were obtained for BEY-treated naïve control mice and the untreated groups. These data indicate that BEY displayed a pivotal modulatory role in the CNS of EAE mice. The consistent findings obtained from the positive impacts of BEY on EAE pathogenesis and inflammatory markers led to further study of the cell population of CD4, Th17 and CD8 differentiation (Figure 5C–E). The flow cytometric analysis revealed that BEY treatment led to a significant reduction in the CD4 cell population and the activation of CD8 populations in splenic lymphocytes of MCP-immunized mice (Figure 6A–D). ## 2.6. BEY Alleviates EAE Symptoms via the Regulation of the Transcriptional Factors With the exception of CCL2, the mRNA expression levels of NRXN, VCAM, SOX5 and MBP in the microglia of the CNS in BEY-treated EAE mice were significantly upregulated (1.13 ± 0.15-, 0.61 ± 0.04-, 0.93 ± 0.02-, 0.89 ± 0.03-fold) compared to those in MCP-induced mice (0.75 ± 0.1-, 0.43 ± 0.08-, 0.75 ± 0.06-, 0.54 ± 0.05-fold) (Figure 7A). The Western blot results showed a similar confirmatory pattern of protein expression levels of the same transcriptional factors (Figure 7B,C). These findings indicated that BEY treatment of post-immunized mice interacted directly with transcriptional factors that are driven to demyelination and the transmembrane proteins of neurons. ## 3. Discussion CM fermented by BA showed an increase in total fat and cholesterol as well as a decrease in total carbohydrates, indicating its high sensory quality [12]. Fermented CM has been proven to combat host inflammatory disorders, including IBD and hypercholesterolemia, due to its antioxidant capacity, the protective role of membrane integrity and a balanced immunomodulatory effect [12,35]. In this study, the protective function of BEY against the MCP-induced EAE model of MS was investigated using ex vivo and in vivo approaches. In inflammatory diseases, CD4 T cells serve as a potential source of proinflammatory cytokines. Depending on the pattern of regulatory transcriptional factors such as SOX5, AHR and NFkB, the polarization of autoimmune diseases progresses in host cell differentiation and maturation [36,37]. The MOG-antigenic stimulation in splenocytes was attenuated by BEY treatment, as evidenced by the substantial suppression of the SOX-5 expression level. Consequently, the inflammatory cytokines (IL-17 and IFN-γ secreted from CD4+ Th17 cells) were significantly downregulated upon BEY treatment. These findings point out that BEY has a potential role in signaling CD4 T-cell activation and lineage separation for cytokine secretion in MOG-induced splenocytes [38,39]. TGF-β-, however, was found to be expressed differently in MOG-treated cells, while IL-6 cytokines showed only a minor shift in the BEY-treated group. Conversely, anti-inflammatory responses, defined by the activation of Treg cells in cell polarization in the host, may also be elicited by PBT-fermented products [40]. In this decade, miRNAs—epigenetic non-coding short RNAs—have gained renewed interest as an alternative to traditional genetic determinants. miRNAs are believed to be the molecular targets of autoimmune disorders and can suppress and regulate inflammatory markers [41,42]. In this study, miR218-5p was identified as a SOX5 mRNA target using the target scan tool. BEY exposure positively upregulated miR218-5 expression in spleen lymphocytes in a dose-dependent manner. This was confirmed in this study, since BEY treatment showed reciprocal regulatory effects between miR-218-5p and SOX5. Simpson [43] reported that maternal PBT supplementation influences the level of miR218 and long non-coding RNA in offspring and mediates the gut–placental interaction between the mother and fetus [44]. Our data suggest the potential exploitation of SOX5/miR-218-5p as an effective diagnostic marker for MS. Furthermore, BEY treatment regulated other cytokines and inflammatory markers (IL-17, IL-6, IFNγ and TGF-β) through ex vivo and in vivo experiments. BEY controlled the transcription factor SOX5 based on the role of miR-218, which is an intracellular molecular inhibitor of cell maturation and differentiation. This study is the first preclinical approach to explore the therapeutic role of BEY in neuronal autoimmune disorders. BEY displayed amelioration of the clinical disease index by improving the recovery of paralysis and demyelination signs in MS mice. These observations were further substantiated by improving body weight and pathophysiology in the host cells. These therapeutic effects of BEY were corroborated by previous evidence using Lactobacillus reuteri [45], Escherichia coli [46] and combinations of Lactobacillus and Bifidobacteria spp. [ 47]. Additionally, BEY showed consistent health-improving anti-inflammatory effects on the colitis mouse model [12]. In the current EAE model, BEY successfully formed the complex of the miR-218/SOX5 axis, leading to the activation of both the Th1 and Treg populations relative to control mice, especially after MCP immunization, which was further confirmed in the histopathological examinations. The inflammatory mediators were reduced, and the graded infiltration of inflamed cells at the site of damage was significantly reduced compared to non-treated mice. Moreover, the intensity of inflammation was proportional to the number of cytokines present in the damaged tissues. Inflammatory markers (IL-17, IL-6, IFNγ and TGF-β) were significantly reduced in BEY-treated MCP-induced mice, suggesting that BEY played a role in attenuating inflammatory cytokines and preserving spinal integrity through the release of SCFA regulatory mediators in the spinal cord of diseased mice. Decisive suppression of inflammatory markers in EAE animals occurs because PBT-mediated SCFAs are an energy source for the mucin layer and also mediate communication between the gut and the brain [47,48,49,50]. Butyric and caproic acids were found to have a gradual rise during BEY therapy of EAE mice compared to the EAE groups, which is consistent with a study that utilized a PBT mixture of Vivomixx (Lactobacillus and Bifidobacterium spp.) [ 51]. Numerous types of cells work together to control autoimmune disorders. Some of these cells belong to the IL-17 CD4+ group [43,52]. The ameliorating impact of BEY on the myelination of neuronal cells in a CD4-dependent manner is confirmed by the decrease in CD4-positive cells in the BEY-treated mice. The current study showed that the binding of PBT products to these markers causes a significant change. Immunohistologically, EAE mimics MS through Th1 and Th17 immune responses. Conversely, CD4+ T cells and Treg cells with the transcription factor FOXP3 play a crucial role in reducing inflammation in the EAE model [53,54]. This research revealed that BEY significantly decreased the CD4, CD8 and TH17 cell populations in the site of neuronal damage and confirmed the alleviation through the inhibition of Th1 and Th17 polarization. These results demonstrate that lymphoid components are expressed differently in various microenvironments in mice that have been vaccinated against the MCP. Compared to MCP-induced EAE mice, BEY-treated EAE mice exhibited significantly higher mRNA expression levels of NRXN, VCAM, SOX5 and MBP in CNS microglia. These findings were supported by protein expression levels as revealed by Western blotting analysis, providing robustness to the notion that administering BEY to immunocompromised mice induced a direct interaction between BEY and transcriptional factors that drive demyelination and neuronal transmembrane proteins. There are two therapeutic treatments that use interferons and glatiramer acetate to lessen the inflammation and progress of MS (specifically RRMS) [55,56,57]. However, they have limitations such as side effects, weak adhesion and unfavorable administration. Therefore, PBTs showed a promising and effective therapeutic approach for neurological diseases [58] due to their wide range of healthful benefits, including immunomodulatory effects, gastrointestinal barrier protection, antimicrobial activity and increased mucoadhesion compared to immunosuppressive drugs [59,60,61]. From this study, BEY treatment could be a potential therapeutic approach for neurodegenerative diseases, as has been seen in similar PBT studies previously [61,62]. ## 4.1. Animals For experimental analysis, male C57BL6j mice aged six weeks old and weighing between 18 and 22 g were used. They were obtained from the animal facility at the College of Science, King Faisal University (KFU), Al-Ahsa, Saudi Arabia. Ethical Council of Deanship of Scientific Research guidelines for the use and handling of experimental mice were followed throughout all animal experiments (KFU-REC-2021-OCT-EA00075). The Institutional Animal Care and Use Committee (IACUC) of the King Faisal University authorized all animal studies and care. ## 4.2. BA Growth Conditions and Yogurt Preparation The PBT bacterial strain (JF836079) used here was characterized earlier for its immunomodulatory and anti-oxidative features. Growth conditions, preservation and yogurt preparation were carried out as in a previous study [63]. ## 4.3. In Vitro Stimulation of Splenocytes Using MOG35–55 C57BL6j naïve mice were excised from the spleen to extract the splenocytes using the MACS isolation kit (Miltenyi Biotec, Bergisch Gladach, Germany). The isolated cells were subjected to mechanical dissociation, RBC lysis and 70 µm filtration. The cells were then plated at a density of 106 cells per mL after being suspended in full cRPMI activated with 20 g/mL MOG35–55. After 4h, the cells were treated with BEY (106, 107.5 and 109 CFU/mL of yogurt). Treated cells were evaluated for SOX5 using protein immunoblot [12], splenocyte viability was assessed using SRB toxicity assay and the level of inflammatory cytokines was quantified using ELISA kit [64]. ## 4.4. Quantification of Secreted Cytokines by ELISA The cytokines IL-6, IL-17, IFNγ and TGF-β in the MOG-stimulated cells were quantified according to the Biolegend’s recommendations for quantification [65]. Different samples were measured for relative absorbance and compared to the standard curve, which was determined by the known concentration. Hence, the captured protein concentration contents were defined. ## 4.5. EAE Induction and Clinical Evaluation of Experimental Mice Mice were divided in a random manner into four groups (six mice in each group), including: group 1: naïve, untreated control mice; group 2: MCP-immunized EAE mice; group 3: MCP was immunized and BEY was administered from day 3 to day 27; group 4: BEY orally administered to mice from day 3 to day 27 of experiment. Mice were immunized with MOG35–55 (100 μg; Peptide International) emulsified in complete Freund’s adjuvant (CFA; Sigma-Aldrich, St Louis, MO, USA) containing 10 mg/mL heat-killed Mycobacterium tuberculosis H37Ra (Difco Laboratories, Detroit, MI). The mice were injected intraperitoneally with pertussis toxin (PTX) (List Biological Laboratories, Detroit, MI; 500 ng) on days 0 and 2. A total of 200 µL of emulsion (MCP) was administered subcutaneously on mice’s flanks at four locations. After the 3rd day of immunization, BEY was orally administered at 200 mg/20 g of body weight of mice on every alternate day until sacrifice day (27th day). Mouse models of EAE were evaluated for clinical signs using the following disease score: disease severity is measured on a scale from 0 (healthy) to 4 (death or very sick): decreased tail tone (0.5), impaired righting response (1.5), limp tail and hind limb weakness (2.5), paralysis of both hind limbs (2.5), paralysis of both limbs (2.5), paralysis to the hip (3.5) and death (4.0). The highest number contributed by clinical signs is used in the final count [66]. ## 4.6. Histological Analysis Mice were perfused with 10 mL formalin ($10\%$) and heparinized PBS after being euthanized. The extracted whole brains were then preserved in $70\%$ ethanol and set in paraffin blocks. Next, 4 µm-thick sections were cut and adhered to microscope slides by using a waterbath and a microtome. Slides were deparaffinized with xylene and ethanol washes according to the previously published protocols of Hematoxylin and Eosin (H&E) [67]. ## 4.7. Different Inflammatory Markers Assessed in the Spinal Cord The levels of cytokines (IL-6, IL-17, IFNγ and TGF-β) in the spinal cord of all groups were measured using ELISA kits from Invitrogen, Thermo Fisher Scientific, Vienna, Austria; Cayman, CA, USA, following the guidelines provided by the manufacturer. On an automated ELISA plate reader, the levels of cytokines in the plates were reported at 450 nm (BioTek Instruments, Santa Clara, CA, USA). ## 4.8. Quantification of SCFAs The composition of SCFAs was estimated from the cecal content using the previously described methods [68]. In brief, 100 mg of mucus tissue and 400 µL of deionized water were homogenized. Phosphoric acid was used to homogenize the samples, which were centrifuged (12,000× g for 15 min) after 30 min. Ethyl butyric acid (Sigma, St Louis, MO, USA) was used as an internal standard to precisely determine experimental concentrations. To each sample, 0.0375 mM caproic acid (Himedia, India) was supplemented. BIOvision chemical kits were used to analyze the samples. ## 4.9. RNA Extraction and Evaluation of Quantitative PCR The total RNA was obtained from the spinal cord following the trizol extraction method [69]. Exactly 300 ng of RNA was added to prepare cDNA in the Superscript II RT (Invitrogen), and the power SYBR Green Master Mix was used in the amplification of the PCR products using StepOne Real-Time PCR System. Gapdh was used to normalize the samples, and comparative CT method was used to measure the relative mRNA. The primer pairs (Table 1) were used in the expression of specific gene transcripts. To optimize the specificity and sensitivity of the amplification reactions, a melting point analysis was conducted, which was identified with the Sybr Green I dye [70]. ## 4.10. Western Blot Using RIPA lysis buffer, the proximal colons of the mice treated with MCP and BEY were used to produce the protein lysates (Santa Cruz, CA, USA). The lysates were transferred to a PVDF membrane with a thickness of 0.22 m after resolving on an SDS-PAGE gel ($10\%$). The following primary antibodies were used in Western blot assays: NRXN (mouse polyclonal antibody 1:750; Invitrogen, Waltham, MA, USA); VCAM (rabbit polyclonal antibody 1:500; Biorbyt, Cambridge, UK); SOX5 (mouse monoclonal antibody 1:500; Invitrogen, Waltham; CCL2 (mouse monoclonal antibody 1:1000; Invitrogen, Waltham, MA, USA; MBP (rabbit polyclonal antibody 1:1000; Biorbyt, Cambridge, UK); and β-actin rabbit monoclonal antibody 1:1500 (Biorybt, Cambridge, UK). ## 4.11. Statistical Analysis The Quant Studio software (Applied Biosystems) applied Real-Time PCR data for the analysis with the 2−ΔΔCT method [70]. The Western blot analysis revealed the linear range of the chemiluminescent signals by observing the chemiluminescence of the expressed bands; the densitometry tool in ImageJ software version 1.8 was employed for the quantifications. Data were presented as mean ± SD. For statistical analysis, one-way ANOVA was used, followed by a post hoc t-test (significant at p ≤ 0.05). ## 5. Conclusions BEY exhibited promising therapeutic impacts on an autoimmune-mediated neurodegenerative paradigm in MOG-immunized C57BL6j mice, as revealed by robust polyphasic evidence. BEY substantially enhanced neuroprotective markers and reduced the proinflammatory cytokines and demyelination process. BEY acted as a novel orchestrator of SOX5 via the epigenetic factor miR-218, recommending its application as a diagnostic marker for MS. 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--- title: 'Protein Intake Is Associated with Blood Pressure and Cholesterol Levels in Italian Older Adults: A Cross-Sectional Study' authors: - Hélio José Coelho-Júnior - Riccardo Calvani - Anna Picca - Matteo Tosato - Giulia Savera - Francesco Landi - Emanuele Marzetti journal: Metabolites year: 2023 pmcid: PMC10059047 doi: 10.3390/metabo13030431 license: CC BY 4.0 --- # Protein Intake Is Associated with Blood Pressure and Cholesterol Levels in Italian Older Adults: A Cross-Sectional Study ## Abstract The present study was conducted to test the association between protein intake and blood pressure, glucose levels, and blood cholesterol in a large sample of Italian older adults. Longevity Check-up 7+ (Lookup 7+) is an ongoing project that started in June 2015. The project is conducted in unconventional settings (e.g., exhibitions, malls, health promotion campaigns) across Italy with the aim of fostering adoption of healthy lifestyles in the general population. For the present study, participants were eligible if they were 65+ years and provided written informed consent. Systolic (SBP) and diastolic blood pressure (DBP), and blood glucose and cholesterol levels were assessed. Protein intake was estimated using a 12-item food frequency questionnaire. Three-thousand four-hundred and four older adults were included in the study. The results of the linear regression showed an inverse association between protein intake (as a continuous variable) and DBP, and a positive correlation with blood cholesterol levels. The findings of the present study indicate that a high intake of protein was negatively associated with DBP and positively associated with total blood cholesterol levels in a large cohort of Italian older adults, after adjustment for numerous covariates. ## 1. Introduction Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally, with a yearly death toll of almost 20 million [1]. The incidence of CVD increases with age, such that more than $70\%$ of those aged 60+ years are affected [2,3]. The burden of CVD in older adults is especially concerning given the association of CVD with hospitalization, healthcare costs [2,3], and mortality [2,3]. The high prevalence of CVD in old age results from both cardiovascular aging [4] and lifetime exposure to risk factors, such as high blood pressure (BP), abnormal glucose metabolism, hyperlipidemia, environmental pollution, and unhealthy behaviors [5]. Changes in lifestyle habits are a cornerstone in the prevention and management of cardiometabolic diseases [6,7,8]. Studies have found that specific dietary patterns (e.g., Mediterranean and DASH diets) may positively affect cardiovascular and metabolic parameters [9,10]. However, differences in food availability and quality, as well as cooking methods, limit the widespread implementation of these nutritional regimens [11]. Individual macronutrients also have an impact on cardiovascular health. Besides lipids and carbohydrates, a high intake of dietary protein may increase the risk of CVD [12]. However, some amino acids (AAs) have hypotensive effects. For instance, l-arginine serves as a substratum for nitric oxide production, which acts as a potent vasodilator [13]. Moreover, an increased consumption of tyrosine is negatively associated with BP [14]. Studies on the relationship between high protein intake and cardiometabolic parameters have produced mixed results [15,16,17,18,19,20,21,22,23,24,25,26]. Most of these findings were obtained in small samples of adults from different age groups, while studies exclusively based on the old population are scarce. Furthermore, high protein intake has been commonly defined as a protein ingestion greater than the current recommended dietary allowance (RDA, ≥0.8 g of protein per kg of body weight (BW) per day) [27,28]. However, these recommendations have been questioned, given that the RDA is based on nitrogen balance studies and no specific recommendations for older adults are available [27,28]. For this reason, several investigations studies have estimated protein intake levels based on the dietary habits of the studied population [26], using tertiles [14,19,23] or quintiles [21]. To expand the knowledge on the subject, the present study was conducted to test the association between protein intake and cardiometabolic risk factors, including BP, glucose levels, and blood cholesterol, in a relatively large sample of Italian older adults. We also explored the relationship between cardiometabolic risk factors and high protein ingestion estimated according to tertiles and quintiles to identify values of protein intake associated with cardiometabolic health. ## 2. Experimental Design Data of the present investigation were gathered from the Longevity Check-up 7+ (Lookup 7+) project database. Sampling characteristics, procedures, and other results have been published elsewhere [29,30,31,32,33,34]. Lookup 7+ is an ongoing initiative developed by the Department of Geriatrics of the Fondazione Policlinico “Agostino Gemelli” IRCCS at the Università Cattolica del Sacro Cuore (Rome, Italy). The project was designed to foster healthy and active aging by raising awareness among the general public on the importance of modifiable risk factors for chronic diseases [29,30,31,32,33,34]. Recruitment was conducted among people visiting public spaces (e.g., exhibitions, shopping centers) and those adhering to prevention campaigns promoted by our institution. As previously described, recruitment activities were carried out in small (<100,000 inhabitants), medium (100,000–250,000 inhabitants), and large cities (>250,000 inhabitants) to achieve a comprehensive geographic coverage of mainland Italy and major islands [29]. In large cities, participants were recruited in different locations to maximize the representation of the sociodemographic characteristics of inhabitants. The Lookup 7+ protocol was approved by the Ethics Committee of the Università Cattolica del Sacro Cuore (protocol #: A.1220/CE/2011) and each participant provided written informed consent prior to enrolment. The manuscript was prepared in compliance with the STrengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines for observational studies [35]. ## 3.1. Participants From 1 June 2015 to 31 October 2021, 13,515 community-dwelling adults aged 18+ years participated in the study. Exclusion criteria were inability or unwillingness to provide written informed consent, self-reported pregnancy, and inability to perform the physical function tests as per the study protocol. For the present investigation, only people aged 65+ years, with body mass index (BMI) values ≥18.5 kg/m2 and no missing data for the study variables, were included, totaling 3404 participants (10,111 excluded). Each participant received a structured interview to collect information on lifestyle habits, followed by measurement of anthropometric parameters, including height and weight. The BMI was calculated as the ratio between body weight (kg) and the square of height (m2). An oscillometric monitor was used to measure BP (Omron M6 electronic sphygmomanometer, Omron, Kyoto, Japan) [36]. Glucose levels and total blood cholesterol were measured from capillary blood samples using disposable electrode strips based on a reflectometric system with a portable device (MultiCare-In, Biomedical Systems International Srl, Florence, Italy) [37]. Participants were asked if they were fasting for at least 8 h. A food frequency questionnaire (FFQ) adapted from Landi et al. [ 37] was used to collect information on how often in a week participants consumed a standardized portion size of a list of 12 foods, including meat, meat derivatives, fish, eggs, milk, cheese, yogurt, pasta, bread, rice, vegetables, and cereals. Portion size was estimated based on the Italian standard portion reference [37]. The mean daily intake of protein was calculated by multiplying the consumption frequency of a food item by the protein content of its standard portion [37], then dividing by seven (the days of a week), followed by the sum of all applicable items. Smoking status was defined as follows: current smoker (has smoked 100+ cigarettes in lifetime and currently smokes cigarettes), and no current smoker. Regular participation in physical activity was considered as involvement in leisure-time physical activity at least twice a week, 30 min per session, during the past year [37]. Accordingly, participants were considered either physically active or inactive. Participants provided information on the use of antihypertensive, cholesterol-lowering, and antidiabetic drugs. ## 3.2. Statistical Analysis The normal distribution of variables was ascertained via the Shapiro–Wilk test. Continuous variables are expressed as the mean ± standard deviation (SD) or absolute numbers, percentages. Tertiles and quintiles for BW-adjusted daily protein intake were: ≤0.79, 0.80–0.99, and ≥1.00; and ≤0.42, 0.43–0.52, 0.53–0.60, 0.61–0.70, and ≥0.71. Regression analysis was conducted to test the association between protein intake and cardiometabolic risk factors. Scatterplots were constructed using the variables significantly associated. Pearson’s correlation was conducted to quantify the association among the variables analyzed in the Scatterplots. The final model was adjusted for age, sex, BMI, energy intake, sodium, potassium, calcium, magnesium, physical activity, active smoking, fasting state (blood glucose), and antihypertensive (for systolic (SBP) and diastolic BP (DBP)), cholesterol-lowering (for total blood cholesterol), and antidiabetic (for blood glucose) drugs. Significance was set at $5\%$ ($p \leq 0.05$) for all tests. All analyses were performed using the SPSS software (version 23.0, SPSS Inc., Chicago, IL, USA). ## 4. Results Three-thousand four-hundred and four older adults were analyzed in the present study. The main characteristics of participants according to quintiles and tertiles of protein intake are shown in Table 1 and Table 2, respectively. SBP (range 90−200 mmHg), DBP (50−70 mmHg), and BMI (18.5−32.0 kg/m2) were within normal ranges. The studied characteristics did not differ depending on the method used to categorize protein intake. Those in the highest tertile (≥1.0 g/kg BW/day) and quintiles (0.61−0.70 and ≥0.71 g/kg BW/day) of protein intake were older than participants with lower consumption. Energy and micronutrient intake parameters increased across tertiles and quintiles of protein consumption. In contrast, protein intake was inversely related to BMI values. ## 4.1. Association of Protein Intake with Cardiovascular Risk Factors Specific patterns of associations were observed between protein intake and cardiometabolic parameters. When participants were stratified according to quintiles of protein intake, those who consumed ≥0.71 g/kg BW/day had lower DBP values and higher blood cholesterol levels in comparison with all other groups. When participants were stratified in tertiles, those with a protein consumption of 0.80−0.99 g/kg BW/day showed higher blood cholesterol levels than participants with an intake ≤0.79 g/kg BW/day. Participants who consumed ≥1.00 g/kg BW/day had higher blood cholesterol levels when compared with the other two groups. DBP values were lower in participants with a protein intake of 0.80−0.99 g/kg BW/day than in those in the lowest tertile. No differences in DBP were observed among participants with a protein consumption ≥1.00 g/kg BW/day and the other protein ingestion groups. Sex distribution and the use of antihypertensive medications differed across tertiles and quintiles of protein intake, whereas smoking and physical activity habits differed according to quintiles. ## 4.2. Linear Regression Results of the linear regression analysis for the association between protein intake and BP, total blood cholesterol, and glucose levels are shown in Table 3, Table 4 and Table 5, respectively. Protein intake classified according to either quintiles or tertiles was not significantly associated with SBP, DBP, blood cholesterol, or glucose levels after adjusting for covariates. However, an inverse association with DBP (β = −4.925; $95\%$ confidence interval (CI) −9.455, −0.394) and a positive correlation with blood cholesterol levels (β = 17.139; $95\%$ CI 2.021, 32.256) were found when protein intake was analyzed as a continuous variable. Figure 1 shows scatterplots for the associations between protein intake and DBP (Figure 1a) and total blood cholesterol (Figure 1b). ## 5. Discussion The findings of the present study indicate that a high intake of protein is negatively associated with DBP and positively correlated with blood cholesterol levels in a large and relatively unselected sample of Italian older adults. These associations were significant when protein intake was analyzed as a continuous variable, but not when quintiles or tertiles of protein of intake were used. Some studies that have investigated the relationship between protein consumption and BP support our results. Mente et al. [ 25] examined more than 100,000 individuals from 18 countries and found that a high protein intake was negatively associated with BP. Similar findings were reported by other investigations that also assessed large cohorts, such as the INTERSALT [15] and Framingham [16,19] studies. Umesawa et al. [ 38] observed similar patterns of associations in an Asian population. However, other studies found no significant associations between protein intake and BP-related parameters. For instance, absolute protein intake was found to be unrelated to age-related changes in BP and hypertension incidence in Dutch adults [21,22]. Similar findings were reported by Liu et al. [ 24] regarding the prevalence of hypertension in poorly nourished rural Chinese people. Increased protein intake also failed to ameliorate hemodynamic parameters in randomized clinical trials. Indeed, Hodgson et al. [ 39] did not find differences in BP values between older adults on protein supplementation or isocaloric supplement for two years. Differences across studies might be attributed to sample characteristics (e.g., age, sex distribution) [15], amount and quality of dietary protein [23,38,40], hypertension status [21], and the covariables used to adjust the analyses [19,21,23,40]. Interestingly, stronger associations between BP and protein consumption have been observed in older women [15] with untreated hypertension [21]. In contrast, the present study examined a cohort of young older adults [8], prevalently composed of men with BMI and BP levels within normal ranges. An interesting scenario was recently offered by He et al. [ 40], who found a U-shaped relationship between protein consumption and hypertension, with the lowest prevalence of hypertension in individuals with the highest protein intake. Mehrabani et al. [ 41] proposed an alternative model based on an inverse dose–response association between protein consumption and BP levels. These data might explain why DBP, but not SBP, and continuous, but not categorical data, were significantly associated with protein intake. Another important result of the present study was that protein intake and blood cholesterol levels were positively correlated. These findings are not supported by most prior research, given that investigations observed negative [17,26] or null [18,42] associations. However, Mente et al. [ 25] noted that a high intake of protein was associated with elevated blood cholesterol levels [25]. Lifestyle interventions based on protein-rich diets have also been investigated as a non-pharmacological lipid-lowering strategy with promising results [26,43]. There are some possible explanations for our observations. Increasing protein intake raises the concern for potential harm to blood lipid profile [44] and CVD risk [12] due to a possible simultaneous increase in fat intake. For this reason, intervention studies testing high-protein diets typically involve low energy from saturated fats (<$10\%$) [43]. Second, protein sources are an important parameter to take into consideration [44]. Red meat is a common source of dietary protein [45,46] and evidence has shown that the prevalence of hyperlipidemia increases according to meat consumption [47]. Unprocessed and processed red meat increases the risk of type II diabetes [45] and death [46], while diets containing low-fat sources of protein (e.g., nuts, dairy products) are associated with a significantly lower risk of adverse events [45,46]. In contrast, high fish consumption is associated with a low monocyte/high-density lipoprotein cholesterol ratio, thereby reducing CVD risk [48]. An additional explanation for our data involves the AA composition of dietary protein. Several AAs, chiefly methionine and cysteine, might influence blood cholesterol levels [49,50,51]. Cysteine is the major precursor of taurine [52,53]. Fish and seafood (e.g., oysters) are the main sources of taurine, with small concentrations found in poultry (e.g., chicken and turkey) [52,53]. Taurine supplementation reduces total and low-density lipoprotein (LDL)-cholesterol in rats [54] and humans [52]. Such a hypocholesterolemic effect seems to occur through the activation of 7-hydroxylase, which accelerates the catabolism of cholesterol into bile acid [53]. Leucine might have hypocholesterolemic effects. Leucine supplementation for 14 weeks decreased total and LDL–cholesterol levels in mice fed a high-fat diet [55]. In rats, leucine reduced systemic LDL–cholesterol levels [56]. Furthermore, leucine attenuated aging-related impairments in endothelium-dependent and independent vasodilation and collagen deposition in the medial layer of the aorta, and abolished inflammatory cell infiltration in male mice [57]. Decreased systemic inflammation was also described in rats supplemented with leucine [56]. The findings of the present study highlight the importance of professional nutritional counseling to ensure that protein intake is not accompanied by an elevated consumption of dietary components, such as fat, that might raise cholesterol levels and, thereby, cardiovascular risk. A possible strategy to possibly avoid the harmful effects of an increased consumption of other macronutrients might be utilize high-protein, low-fat foods (e.g., lean red meat) [58,59,60]. Despite our efforts of using different methods to identify high protein intake levels that were more associated with cardiometabolic factors, we were unable to establish cutoff values in our population. Such a scenario suggests that an accurate and close monitoring of nutrient intake is necessary to minimize the unwanted effects of diet on cardiometabolic risk. Therefore, the results of our study should be complemented with those of randomized clinical trials specifically designed to test the effects of various levels of protein intake on cardiometabolic parameters in older adults. A major limitation of the present study is that the FFQ used only included weekly consumption of 12 food groups. It is therefore possible that participants either ate foods that were not included in the FFQ or under-reported their dietary intake, which impacted the accuracy of protein intake estimation. Second, participants were relatively young (65–74 years) [61] community-dwelling older Caucasians, and extrapolation to people in other age groups (e.g., old-old adults ≥75 years) or ethnicities should be made with caution. Third, participants were evaluated while they were attending an event. Thus, the possibility the evaluation setting could have influenced the assessment results cannot be excluded. Fourth, a high-protein diet was found to reduce HbA1C, but not blood glucose levels [44]. However, HbA1C was not measured in our study. Fifth, specific patterns of associations have been observed between protein sources and cardiometabolic parameters [62,63]. This aspect was not investigated in the present study. Sixth, participants with cardiovascular or cerebrovascular disease were not excluded and the possibility that this might have influenced our results cannot be ruled out. Finally, the cross-sectional design of the study does not allow any inference to be drawn on the time course of changes in the analyzed variables or on cause-effect relationships. 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--- title: Dioleoylphosphatidylglycerol Inhibits Heat Shock Protein B4 (HSPB4)-Induced Inflammatory Pathways In Vitro authors: - Teresa E. Fowler - Vivek Choudhary - Samuel Melnyk - Mishma Farsi - Luke Y. Chang - Nyemkuna Fortingo - Xunsheng Chen - Mitchell A. Watsky - Wendy B. Bollag journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10059050 doi: 10.3390/ijms24065839 license: CC BY 4.0 --- # Dioleoylphosphatidylglycerol Inhibits Heat Shock Protein B4 (HSPB4)-Induced Inflammatory Pathways In Vitro ## Abstract Our previous work shows that dioleoylphosphatidylglycerol (DOPG) accelerates corneal epithelial healing in vitro and in vivo by unknown mechanisms. Prior data demonstrate that DOPG inhibits toll-like receptor (TLR) activation and inflammation induced by microbial components (pathogen-associated molecular patterns, PAMPs) and by endogenous molecules upregulated in psoriatic skin, which act as danger-associated molecular patterns (DAMPs) to activate TLRs and promote inflammation. In the injured cornea, sterile inflammation can result from the release of the DAMP molecule, heat shock protein B4 (HSPB4), to contribute to delayed wound healing. Here, we show in vitro that DOPG inhibits TLR2 activation induced in response to HSPB4, as well as DAMPs that are elevated in diabetes, a disease that also slows corneal wound healing. Further, we show that the co-receptor, cluster of differentiation-14 (CD14), is necessary for PAMP/DAMP-induced activation of TLR2, as well as of TLR4. Finally, we simulated the high-glucose environment of diabetes to show that elevated glucose levels enhance TLR4 activation by a DAMP known to be upregulated in diabetes. Together, our results demonstrate the anti-inflammatory actions of DOPG and support further investigation into its development as a possible therapy for corneal injury, especially in diabetic patients at high risk of vision-threatening complications. ## 1. Introduction When normal corneal tissue suffers an injury, damaged epithelial cells and stromal keratocytes release damage-associated molecular patterns (DAMPs), endogenous molecules that bind pattern recognition receptors such as toll-like receptors (TLRs) to activate the innate immune system. TLRs are also activated by microbial pathogen-associated molecular patterns (PAMPs), such as lipopolysaccharide (LPS), on the surface of gram-negative bacteria. The activation of TLRs triggers an intracellular cascade, culminating in the production of inflammatory cytokines and chemokines to propagate the immune response and recruit additional effectors [1,2]. Usually, this process occurs and resolves rapidly with the concomitant recovery of corneal clarity, while in some individuals, impaired healing and/or persistent inflammation can result in corneal ulceration or opacification. Heat shock protein B4 (HSPB4) is one DAMP shown to be released upon corneal injury and contribute to sterile inflammation, that is, inflammation in the absence of infection [3]. This can promote neutrophil infiltration into the cornea and decrease its transparency. Voelker and colleagues have shown that in the lung, PAMP-induced TLR activation is inhibited by the phospholipid phosphatidylglycerol (PG) naturally present in surfactant [4]. We later demonstrated in cultured mouse macrophages and epidermal keratinocytes, as well as in a live mouse model of skin inflammation, that PG, and in particular dioleoyl-PG (DOPG), also inhibits the activation of TLRs induced by DAMPs active in psoriasis [5]. Further, we have recently shown that DOPG accelerates corneal wound healing both in vitro and in vivo [6], although this mechanism is still under investigation. Intriguingly, the DAMP-TLR interaction is aided by coreceptors, such as cluster of differentiation-14 (CD14) and myeloid differentiation protein-2 (MD2), which have also been shown to bind PG [7]. We hypothesized that DOPG inhibits activation of TLRs by DAMPs involved in corneal wound healing, like HSPB4, and that this inhibition improves corneal wound healing in inflammatory states. One disease associated with delayed wound healing is diabetes, which is estimated to affect $10.5\%$ of adults worldwide, or 536 million individuals, and is expected to rise to a prevalence of $12.2\%$ in the next 25 years [8]. As the prevalence of diabetes increases, new therapies for its complications are needed. The complications of diabetes are recognized in every organ system, although ocular manifestations are among the most feared, as diabetic eye disease is among the most common causes of new blindness in adults [9]. The cornea is not immune to the destruction of diabetes, with up to $70\%$ of diabetic patients affected by keratopathy [10,11,12]. Corneal injury in individuals with diabetes can be clinically challenging due to pain, delayed healing, neurotrophic keratitis, recurrent erosions, and superimposed infections. It is thought that changes in the inflammatory response play a significant role in corneal morbidity from diabetes. High mobility group box 1 (HMGB1), a DAMP known to be elevated in diabetes [13], is released upon corneal injury [14] and also acts via TLR4 to initiate inflammation [15,16,17,18]. HMGB1, TLR2, TLR4, and several downstream ligands are upregulated in the corneas of diabetic animal models [19,20,21], and the inhibition of HMGB1 has been shown to improve diabetic mouse corneal healing [21]. To examine the effects on TLR activation of the corneal-relevant DAMPs, HSPB4 and HMGB1, as well as PAMPs as positive controls, we used a mouse macrophage cell line and a human epithelial kidney reporter cell line to demonstrate inhibition of TLR activation by DOPG, as well as by a neutralizing antibody to CD14. We also provide evidence that hyperglycemia enhances the activation of TLR4 by HMGB1, while having no effect on TLR2 activation by HSPB4; this effect may contribute to slow corneal recovery in diabetic patients. Our results support further exploration into DOPG as a therapeutic option for corneal injury due to its promotion of wound healing [6] and inhibition of inflammation (this study), with the goal of improving visual health and quality of life for diabetic patients. ## 2.1. DOPG Inhibited Inflammatory Mediator Expression and Production in Mouse Macrophages Stimulated by HSPB4 and Human Corneal Epithelial Cells Exposed to a TLR2 Agonist Studies in rodent models of sterile corneal inflammation upon injury have identified keratocyte-derived HSPB4 as an important DAMP that binds TLR2 on resident macrophages, initiating nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling to produce interleukins (ILs) and tumor necrosis factor-alpha (TNFα) [3]. In previous work, we have shown that DOPG inhibits inflammation in mouse skin in vivo [22], as well as in keratinocytes [23] and RAW264.7 mouse macrophage cells, by inhibiting TLR activation by the DAMP S100A9 [5]. In epidermal keratinocytes stimulated by recombinant S100A9, DOPG inhibits IL1β, IL6, and TNFα production [5]. We hypothesized that the upregulation of these factors in response to the activation of TLR2 by the DAMP, HSPB4, would also be inhibited by DOPG. In Figure 1, transcriptional upregulation of inflammatory mediators was observed in response to HSPB4 in mouse macrophages, specifically of IL-1α, -1β, and -6, as well as TNF. In the presence of the lowest concentration of HSPB4 tested, 0.1 µg/mL, IL1α, and IL1β were not significantly upregulated, while IL6 and TNF were only moderately increased. With 1 µg/mL HSPB4, the transcription of all four mediators increased to a value that was statistically significantly different ($p \leq 0.001$) from all of the other values in the panels, with IL-1α increasing approximately two-fold, IL-1β rising about three-fold, IL-6, approximately five-fold and TNF, about four-fold. These results indicate that the response to HSPB4 is dose dependent. DOPG (at 100 µg/mL) counteracted this response, with the mRNA levels of all tested mediators returning to basal levels, i.e., values that were not significantly different from the control. In Figure 2, we demonstrate by ELISA that the observed increase in TNF mRNA was translated into elevated protein levels, as treatment with 1.0 µg/mL HSPB4 enhanced TNFα protein concentration by more than two-fold ($p \leq 0.05$). As expected, DOPG inhibited this response, again to a level that was not significantly different from the control value. We also determined the ability of DOPG to inhibit TLR2 activation in corneal epithelial cells. Normal human corneal epithelial cells (HCEC) between passages 3 and 7 were treated with the synthetic triacylated lipopeptide TLR2 agonist, Pam3(CSK)4 (Pam), and inflammatory mediator mRNA levels were assessed by quantitative RT-PCR. As shown in Figure 3, Pam increased the expression of three of the four inflammatory cytokines measured, by about three-fold (IL1α), four-fold (IL1β), and four-fold (TNF). As with TLR2 activated by HSPB4 in the macrophage cell line, DOPG inhibited this expression, returning mRNA levels of IL1α to values that were not significantly different from the control values and significantly inhibiting the expression of IL1β and TNF (by about $40\%$ and $25\%$, respectively). The effect of Pam on IL6 expression, although significant, was minimal and was not altered by DOPG. ## 2.2. HSPB4 Dose-Dependently Induced TLR2 Activation in Human Cells, and DOPG Inhibited This Response To further investigate the mechanism behind the ani-inflammatory properties of DOPG, we next examined the activation of TLR2, the macrophage surface receptor for HSPB4. We used human reporter cells (HEK-Blue-hTLR2) which stably express TLR2, coreceptors CD14 and MD2, and a reporter construct which, when activated by TLR2 signaling, drives production of a secreted alkaline phosphatase (SEAP) detectable using the chromophore in the HEK-Blue Detection medium as a change in absorbance at 620 nm. In Figure 4A, we show dose-dependent activation of hTLR2 by recombinant HSPB4 using concentrations of 1, 2.5, and 5 µg/mL HSPB4, with the highest concentration of HSPB4 inducing an approximate 10-fold enhancement of TLR2 activation, as measured by the increase in absorbance at 620 nm ($p \leq 0.0001$). Based on DOPG’s inhibition of TLR2 activation by HSPB4 in mouse macrophages, we anticipated a similar response in the human reporter cell line. Our previous experiments examined concentrations of 25, 50, and 100 µg/mL DOPG [6,24], with lower doses generally showing a similar efficacy as higher. Therefore, we elected to perform a dose response curve to observe the effect of DOPG on HSPB4’s activation of TLR2. Dioleoylphosphatidylcholine (DOPC), a phospholipid with the same two fatty acid tails as DOPG but a distinct head group, was used as a control based on previously published data that DOPC has little or no effect on these pathways [5]. HSPB4-activated hTLR2 cells were treated with DOPG at concentrations of 1, 10, 50, and 100 µg/mL. As shown in Figure 4B, 1 µg/mL HSPB4 induced an approximate 4.5-fold increase in TLR2 activation. In these HSPB4-exposed cells, the inhibitory effect of DOPG on TLR2 activation was robust even at the lowest tested concentration (1 µg/mL), with a return of hTLR2 activity to levels not significantly different from the control value, and maximal inhibition at approximately 10 µg/mL. Therefore, we repeated the experiment with this lower dose and included PG- and PC-alone groups, as shown in Figure 4C. We found that hTLR2 cells treated with 10 µg/mL DOPG or DOPC alone demonstrated hTLR2 activity equivalent to control cells. TLR2 activity was significantly upregulated (more than 10-fold, $p \leq 0.001$) in the presence of 1 µg/mL HSPB4, with DOPG, but not DOPC, blocking the stimulatory effect of HSPB4. ## 2.3. HMGB1 Activated TLR4, and DOPG, but Not DOPC, Inhibited This Activation A growing body of evidence demonstrates that diabetes is a chronic inflammatory state. HMGB1 is an endogenous DAMP known to be upregulated in the serum of patients with diabetes [25]. Further, HMGB1 expression has been shown to be inhibited by metformin [26], a medication with anti-inflammatory properties [27] commonly used to manage diabetes. Additionally, HMGB1 has been shown to be upregulated after wounding, and its inhibition improves corneal wound healing [14]. We hypothesized that HMGB1 contributes to the impaired corneal wound healing seen in diabetic patients, and that DOPG would reduce this inflammatory stimulus. First, we investigated whether HMGB1 can activate TLR4 and if so, whether DOPG inhibited such activation. In Figure 5A, we show that using HEK-Blue-hTLR4 reporter cells, HMGB1 does indeed activate TLR4 in a dose-dependent manner. HMGB1 did not significantly activate TLR4 at 2 and 5 µg/mL, but it led to a modest response at 10 µg/mL, and significantly upregulated TLR4 activity at 20 µg/mL, with about a four-fold increase in hTLR4 activation at this highest dose ($p \leq 0.01$). In subsequent experiments we demonstrate that DOPG, but not DOPC, inhibited HMGB1-induced TLR4 activation, from a level that was approximately five-fold greater than the control ($p \leq 0.001$) to a value that was not significantly different from the control (Figure 5B). ## 2.4. HMGB1-Induced TLR4 Activation Was Increased in High Glucose Conditions but Ligand-Induced TLR2 Activation Was Not To examine the effect of the hyperglycemia accompanying diabetes on the activation of TLR4 by HMGB1, we performed similar experiments in medium with high (4.5 g/L)—or normal (1 g/L)-glucose concentration. TLR4 activity was increased moderately in normal glucose (N-) medium but was significantly enhanced in the presence of high glucose (H-) (Figure 6A). In additional studies, we determined that this effect of the high-glucose medium was also observed in comparison with normal-glucose medium in which the osmolarity was matched to the high-glucose medium by the addition of mannitol (Supplemental Figure S1). We did not observe the same ability of high-glucose medium to augment TLR2 activation by HSPB4; the increase in TLR2 activity was equivalent in normal- and high-glucose states (Figure 6B). It was unclear whether the TLR involved or the activator was responsible for this differing response; therefore, we also examined the response to S100A9, a DAMP that activates both TLR2 and TLR4. We found that high-glucose medium did not enhance the response of either TLR4 (Figure 6C) or TLR2 (Figure 6D) by S100A9 in comparison to normal-glucose medium, suggesting that the effect might be related to the activator. Nevertheless, this finding suggests that a hyperglycemic environment can contribute to some, but not all, inflammatory cascades in the cornea. ## 2.5.1. Anti-CD14 Antibody and DOPG Inhibited hTLR4 Activation by LPS and S100A9 LPS, the major virulence factor responsible for septic shock from gram negative bacteria [28], is a PAMP that activates TLR4. Macrophages are known to express the surface pattern recognition receptor CD14, a known coreceptor for TLR4 [29]. Specific PAMP inflammatory stimuli, such as LPS in the outer membrane of gram-negative bacteria, bind both TLRs and CD14 [30] to produce a robust macrophage response [31]. CD14 has also been shown to bind PG [32] with this interaction likely important in PG’s ability to inhibit TLR activation in the lung [7]. We suspected that the neutralization of CD14 with an anti-CD14 antibody would mitigate the stimulatory effect of PAMPs and DAMPs on TLR4 receptors, and possibly interfere with the anti-inflammatory effect of DOPG. Therefore, we next wanted to explore the mechanisms regulating TLR4 activation by examining the interaction between DOPG and an antibody capable of neutralizing CD14 activity on LPS-induced TLR4 activation. As shown in Figure 7, LPS significantly increased the activation of TLR4 in the reporter cell line approximately two-fold ($p \leq 0.05$), but 100 µg/mL DOPG blunted this response, with a return of TLR4 activity to control levels. When hTLR4 cells were treated with LPS in the presence of the anti-CD14 neutralizing antibody, TLR4 activation was again inhibited to a value not significantly different from the control, supporting the importance of CD14 in this interaction. Note that an antibody of the same isotype (ISO) as the anti-CD14 antibody (IgG1), but which does not recognize CD14, was used as a control for potential non-specific antibody effects, and as expected, did not inhibit LPS-induced TLR4 activation. Cells treated with both DOPG and anti-CD14 demonstrated low TLR4 activity that was not significantly different from either compound alone, making it difficult to evaluate whether an additive effect was present; however, there was also no interference with either’s inhibitory effect. Taken together, these data support an important role for the CD14 co-receptor in PAMP-induced activation of TLR4, as well as the ability of both DOPG and an anti-CD14 neutralizing antibody to inhibit this process. S100 calcium-binding protein A9 (S100A9) is a DAMP released upon corneal wounding, which contributes to corneal inflammation [33]. S100A9 activates both TLR2 and TLR4 [34,35], and in RAW264.7 macrophages we have previously shown that DOPG inhibits S100A9-induced hTLR2 activation in the reporter cell line [5]. We next questioned whether TLR4 activation induced by DAMPs also requires CD14. In Figure 7B, we observed increased TLR4 activity in the presence of S100A9 (of about six-fold, $p \leq 0.0001$), with inhibition in the presence of the anti-CD14 antibody or DOPG to levels that were not significantly different from the control value. TLR4 reporter cells exposed to S100A9, anti-CD14, and DOPG concurrently demonstrated receptor activity equivalent to that of S100A9 with DOPG alone, again suggesting no interference from anti-CD14 towards the inhibitory effect of DOPG. ## 2.5.2. TLR2 Activation by a PAMP or DAMP Was Inhibited by DOPG and by an Antibody Recognizing CD14, but Effects Were Not Additive Although CD14 is well known to serve as a coreceptor for TLR4 [29], perhaps less recognized is its involvement in TLR2 activation. We first verified the importance of CD14 in the TLR2 response to PAMPs. We exposed hTLR2 cells to a synthetic microbial triacylated peptide known to activate TLR2, Pam3CSK4 (Pam) and, as expected, saw a significant rise in TLR2 activity to more than three-fold over the control ($p \leq 0.0001$). Pam stimulation of TLR2 activity was blunted by treatment with either anti-CD14 or DOPG alone, as well as in combination, to levels that were not significantly different from the control value (Figure 7C); again, the combination showed neither an additive nor a subtractive response. We next wanted to know whether the same responses would occur when cells were stimulated with an endogenous DAMP, such as HSPB4, instead of a microbial PAMP. We also used a lower concentration of antibody and DOPG (both 1 µg/mL) to see if submaximal doses of these two agents would show additive effects. As shown in Figure 7D, we found that hTLR2 activity stimulated by HSPB4, which was elevated by approximately seven-fold ($p \leq 0.0001$), was inhibited by both DOPG and anti-CD14 antibody by about $33\%$ but that there was no additive inhibitory effect of the combination. In another set of experiments, we used comparable doses as in Figure 7A–C (10 µg/mL DOPG and 2.5 µg/mL anti-CD14 antibody) and observed that hTLR2 activity stimulated by HSPB4 is equivalently inhibited by DOPG and anti-CD14 antibody, such that exposure to both inhibitors in combination yielded TLR2 activity not significantly different from either inhibitor alone. ## 2.6. DMPG, a Phosphatidylglycerol Already Used in Commercial Eye Drops, Has a Similar Inhibitory Effect as DOPG on HSPB4-Induced TLR2 Activation Alcon’s treatment for dry eye, Systane® Complete Lubricant Eye Drops, lists dimyristoylphosphatidylglycerol (DMPG) as an inert ingredient [36]. DMPG is a species of phosphatidylglycerol with two saturated 14-carbon fatty acids in place of the two monounsaturated 18-carbon fatty acids found in DOPG. Importantly, Voelker and colleagues have previously shown that DMPG can block LPS-induced TLR4 activation in alveolar macrophages [7]. Therefore, DMPG was tested in the reporter cell system for its ability to inhibit TLR2 activation by HSPB4, since this DAMP is known to be released in the cornea upon wounding [3]. Figure 8 demonstrates that HSPB4 increased TLR2 activation by more than 10-fold ($p \leq 0.0001$) and DMPG inhibited HSPB4-induced TLR2 activation with a similar dose dependence as DOPG, such that doses of 5 µg/mL or greater DMPG/DOPG significantly reduced—and doses of 50 µg/mL and above completely blocked—TLR2 activation, returning the levels to a value not significantly different from the control. DMPG alone had no effect on TLR2 activation. Thus, although the concentration of DMPG in Systane® Complete is not provided by the company, this result suggests the possibility that the DMPG in these eye drops may not be an inert ingredient, as previously assumed. ## 3. Discussion Corneal injury involves complex inflammatory signaling, with activation of TLRs leading to production of cytokines and chemokines to recruit immune effector cells. In this work, we used a macrophage cell model and the HEK reporter cell line to investigate several inflammatory stimuli, including representative endogenous DAMPs and microbial PAMPs, along with their TLR receptors and CD14 coreceptor. We selected the RAW264.7 mouse macrophage cell line to model the stromal macrophages previously shown to respond to HSPB4 [3] and also examined the response of HCECs to a synthetic triacylated lipopeptide TLR2 agonist. We chose to use the HEK-Blue-hTLR2 and -hTLR4 reporter cells as highly sensitive indicators of TLR2 or TLR4 activation. For DAMPs, we selected HSPB4 based on previous studies demonstrating its importance in mediating the corneal keratocyte inflammatory response to epithelial damage [3]. Our interest in HMGB1 stemmed from its established upregulation in diabetes [25]. We show new evidence that CD14 is an important coreceptor in the activation of both TLR2 and TLR4, and that neutralization of CD14 dampens TLR-induced NF-κB activation, and presumably the immune response, as does treatment with DOPG. DOPG is a potent inhibitor of these pathways, even at low concentrations, as is DMPG, which we propose makes these phospholipids a promising therapeutic option for noninfectious corneal inflammation, especially in cases of impaired healing such as in diabetes. In this study, we used high-glucose media to simulate the hyperglycemic state present in diabetes, finding enhancement of TLR4 activation by HMGB1 by the high glucose concentration but no effect on HSPB4-induced TLR2 activation. These results suggest that augmentation of specific inflammatory signaling interactions is one mechanism by which diabetes may contribute to prolonged inflammation, providing a potential target for development of therapeutic interventions. It should be noted that since the serum levels of HMGB1 are increased in diabetic individuals [13], TLR4 activation by this DAMP might also play a role in impaired skin wound healing in diabetes. Therefore, DOPG could potentially be applied topically to these wounds to reduce inflammation and promote wound healing. Several properties of DOPG make it an attractive potential therapeutic. Previous work by our laboratory supports its efficacy in promoting healing of injured corneal epithelium both in vitro and in vivo [6]. PG is found naturally in human surfactant, and thus is presumably safe for use as a topical medication for humans. As mentioned in Section 2, PG, in the form of DMPG, which also inhibits HSPB4-induced TLR2 activation, is already present in an ophthalmic solution used to treat dry eye, indicating a good safety profile in this organ and stability in commercially available topical formulations. Further, PG suppresses DAMP- and PAMP-stimulated inflammation without suppressing immune protection globally, demonstrated by studies in the lung showing that inhaled PG enhances protection against viral infection [4,37,38], and thus, may be safe for use, even if an unrecognized infectious pathogens are present. The development of safe and effective drops with a favorable side effect profile to enhance recovery from and reduce vision-threatening complications of corneal disease could considerably improve visual outcomes, especially in diabetic patients. The mechanism by which DOPG (or DMPG) functions to inhibit TLR activation is not entirely clear. In 2009, Voelker and colleagues showed that two components of the TLR signaling system, CD14, an apparent co-receptor, and myeloid differentiation factor-2 (MD-2), an adaptor protein, are able to bind phosphatidylglycerol [7], suggesting the possibility that one (or both) of these proteins mediates the effects of DOPG. A more recent study with phosphatidylglycerol analogs indicates that the capacity of these analogs to inhibit PAMP-induced TLR activation correlates with their binding to CD14, rather than MD-2 [32], identifying the CD14 TLR co-receptor as the likely site of DOPG’s action. Nevertheless, in the current report, the blocking antibody recognizing CD14 did not act additively, nor did it inhibit, the ability of DOPG to reduce TLR2 or TLR4 activation by either PAMPs or DAMPs. This result raises the question as to whether DOPG is actually working through CD14. However, the data do not eliminate the possibility that the anti-CD14 and DOPG bind to different sites on CD14 and the binding of the antibody and/or phospholipid does not change CD14’s conformation sufficiently to alter its capacity to bind the other. At present, oral doxycycline is one of the limited therapeutic options employed in patients with prolonged corneal inflammation, including diabetic corneal injury. This broad-spectrum antibiotic has been shown to have anti-inflammatory properties in the cornea distinct from its antibiotic effects, including the inhibition of matrix metalloproteinases [39], blockage of immune cell activation, and reduction of unwanted neovascularization [40]. Similar to the effects seen with DOPG, topical doxycycline in mouse models of dry eye reduces expression of IL-1α, IL-1β, and TNF-α, and in LPS-stimulated corneal epithelial cells, it has been shown to reduce IL-1β transcription and translation [41]. Topical doxycycline has also recently been shown to inhibit TNFα expression in rat corneas subjected to alkali burn [42], and to block production of nitric oxide by cultured macrophages stimulated by LPS [43]. Of course, the use of systemic doxycycline can have unwanted effects unrelated to the eyes, such as gastrointestinal distress, esophagitis, photosensitivity, and hepatotoxicity, as well as the promotion of antibiotic resistance, and patients with corneal disease are often kept on this medication for long periods of time. Our results suggest that DOPG and DMPG have similar anti-inflammatory properties to doxycycline but without some of the unwanted side effects, supporting further investigation into these agents’ potential development as a therapeutic option. Limitations of this study include the fact that the results were obtained in vitro, although this approach allowed us to investigate human TLR signaling with a highly sensitive reporter system, and to begin to examine the mechanisms by which DOPG might be exerting its anti-inflammatory effects. Nevertheless, it is unclear whether these same effects will occur in vivo. In addition, for our studies examining the ability of HSPB4 to stimulate inflammatory mediator production in innate immune cells, we used a macrophage cell line, RAW264.7 cells, which may not be a good equivalent of normal macrophages [44]. Finally, incubating cells in a high-glucose medium for a short time cannot reproduce the many changes experienced by tissues in a chronic disease like diabetes. In summary, these results provide new insight into the anti-inflammatory effects of DOPG (and DMPG) in response to DAMPs and PAMPs. Our representative DAMPs were selected based on their role in corneal injury or in diabetes, which is known to be a chronic inflammatory state with impaired corneal healing [45,46,47]. We provide new evidence that neutralization of the CD14 coreceptor blunts TLR2 and TLR4 activation in response to DAMPs and PAMPs, but does not interfere with DOPG’s action. Next steps include in vivo application of this knowledge to mouse models of corneal injury, including knockouts with impaired healing and those with diabetes. The primary goal of our work is to identify potential novel therapeutics to reduce the morbidity of inflammatory corneal disease, and these results support DOPG as a promising candidate for development into a topical therapy. ## 4.1. Materials Cultured RAW264.7 mouse macrophage cells were obtained from Dr. Carlos Isales (Augusta University, Augusta, GA, USA) who purchased them from American Type Culture Collection (Manassas, VA, USA). HEK-Blue-hTLR2 (catalog #hkb-htlr2) and -hTLR4 (catalog #hkb-htlr4) cells expressing CD14, MD2, and an inducible secreted embryonic alkaline phosphatase (SEAP) reporter gene were purchased from InvivoGen (San Diego, CA, USA) as was the HEK-Blue Detection medium (catalog #hb-det3). Enzyme linked immunosorbent assay (ELISA) studies were performed with kits obtained from BD Biosciences (San Jose, CA, USA). Recombinant human S100A9 protein (catalog #9254-S9-050) was from R&D Systems (Minneapolis, MN, USA) and Recombinant Human AlphaA Crystallin/CRYAA (HSPB4; NBC1-18351) from Novus Biologicals (Centennial, CO, USA). Phospholipids (DOPG, DOPC, and DMPG) were obtained from Avanti Polar Lipids, Inc. (Alabaster, AL, USA). Pam3Cys-Ser-(Lys)4 (Pam; catalog #506350) and lipopolysaccharide (LPS) were obtained from Sigma-Aldrich (St. Louis, MO, USA). Human CD14 antibody (MAB3832) and mouse IgG1 Isotype control monoclonal antibody (MAB002) were purchased from R&D Systems (Minneapolis, MN, USA). ## 4.2. Cell Culture Culture medium for RAW264.7 cells consisted of Dulbecco’s Modified Eagle Medium (DMEM) with $10\%$ fetal bovine serum and $1\%$ penicillin and streptomycin. HEK-Blue-hTLR2 and hTLR4 cells were cultured in a growth medium, as per the supplier’s instructions. For experiments examining cells treated under normal-(1 g/L glucose) and high (4.5 g/L glucose)-glucose conditions, media were from Fisher Scientific (Hampton, NH, USA; catalog numbers MT10014CV and MT10013CM, respectively). Primary human corneal epithelial cells (HCEC) were prepared from human corneal rims, as described in [48]. HCEC (passage 3–7) were maintained in normal-glucose (1 g/L) DMEM containing $10\%$ fetal bovine serum, insulin/transferrin/selenium (ITS), epidermal growth factor (EGF) and gentamycin. For experiments, the HCEC were grown on 6-well plates with an initial plating density of 150,000 cells per well. Once the cells reached approximately $70\%$ confluence, the cells were treated with or without the TLR2 agonist Pam (2.5 µg/mL) in the presence and absence of DOPG (100 µg/mL) for 2 h. At the end of the treatment, cells were collected in RNA lysis buffer (PureLink RNA Mini kit, Thermo Fisher Scientific) and total RNA was isolated and analyzed as described below. ## 4.3. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) After the treatment of cells, PerfectPure RNA tissue kits (QuantaBio, Gaithersburg, MD, USA) were used for total RNA extraction, followed by verification of RNA quality and quantity using a Nanodrop spectrophotometer (Wilmington, DE, USA). Reverse transcription of the total RNA was performed using iScript cDNA synthesis kits from Bio-Rad Laboratories (Hercules, CA, USA). Real time quantitative polymerase chain reaction (qRT-PCR) experiments were performed using Taqman probes (Supplemental Table S1), Fast Reagent PCR Master Mix, and the StepOnePlus Real-time PCR system from Applied Biosystems (Waltham, MA, USA). GAPDH was selected for use as the housekeeping gene and gene expression values calculated using the ΔΔCt method. For the studies in HCEC, mRNA expression of inflammatory cytokines was analyzed using GAPDH and RPLP0 as reference genes. The data were expressed as the percent of the maximal response for each cytokine. ## 4.4. Absorbance Assays to Assess TLR2 or 4 Activity TLR2 and TLR4 activation was determined using human reporter cells (HEK-Blue-hTLR2 and HEK-Blue-hTLR4), which stably express human TLR2 or TLR4, the coreceptors CD14 and MD2, and a reporter construct which drives the production of a secreted alkaline phosphatase (SEAP) when activated by TLR signaling. SEAP activity can then be detected using HEK-Blue Detection medium, which contains a chromogenic substrate that changes its absorbance at 620 nm when acted upon by SEAP. Cultured HEK-Blue-hTLR2 or -hTLR4 reporter cells were resuspended in HEK-Blue Detection medium and added to a 96-well plate with the desired activator (HMGB1, HSPB4, LPS, Pam, or S100A9) and/or inhibitor (DOPG, anti-CD14 antibody). Phosphate-buffered saline (PBS), DOPC, and an isotype control antibody (ISO) were used as controls. Cells were treated for 24 h with the selected compounds at 37 °C. Absorbance was measured at 620 nm to determine secreted embryonic alkaline phosphatase (SEAP) activity, using a Synergy HT microplate reader from Bio-Tek Instruments (Winooski, VT, USA) with Gen5 analysis software. ## 4.5. ELISA Assay Supernatants of treated RAW264.7 cells were collected and analyzed by an enzyme-linked immunosorbent assay (ELISA) from BD Biosciences (San Jose, CA, USA), as previously described [49]. ## 4.6. Statistical Analysis All experiments were repeated in at least duplicate in at least 3 separate experiments, with the results reported as the mean ± standard error of the mean. Differences between two groups were compared using an unpaired, two-tailed t-test. When three or more groups were analyzed, a one-way analysis of variance was used with a Tukey’s post-hoc test. ## 5. 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--- title: Combinatory Effects of Training and Nutritive Administration of Carbohydrates and Protein via Food on Strength in Postmenopausal Women, and Old Men and Women authors: - Katharina Hofmann - Ulrich Flenker - Gina Kiewardt - Patrick Rene Diel journal: Nutrients year: 2023 pmcid: PMC10059059 doi: 10.3390/nu15061531 license: CC BY 4.0 --- # Combinatory Effects of Training and Nutritive Administration of Carbohydrates and Protein via Food on Strength in Postmenopausal Women, and Old Men and Women ## Abstract The age-related loss of muscle mass promotes many impairments. Training and protein supplementation are suggested to prevent muscle wasting, but recommendations for all populations are not based on scientific evidence. This study combines protein/carbohydrate supplementation (PCS) and training for seniors and postmenopausal women. Project A: 51 postmenopausal women (PMW, 57.3 ± 3.0 years old) underwent health-oriented training (12 weeks, moderate-strength training + moderate-endurance training). The intervention group (IG) additionally received 110 g sour milk cheese (SMC) and toast. Project B: 25 women and 6 men (65.9 ± 4.9 years old) performed intense sling training (12 weeks). The IG additionally received 110 g SMC, toast, and buttermilk. Strength was tested before and after in both studies. Project A: there was significant increase in strength, no additional effect of PCS, and a reduction in body fat in the controls. Project B: there was significant increase in strength, significant additional effects of PCS for trunk strength, and a significant reduction in body weight. Combining training and PCS may counteract strength loss. Combined endurance/resistance training is recommended to PMW for whom the benefits of PCS are restricted. Aged subjects may benefit from PCS when training intensely, but these benefits may be strongly individual. ## 1. Introduction Aging is accompanied by a variety of physical changes, such as a decrease in muscle mass up to sarcopenia, an increase in cardiovascular diseases, and frailty syndrome. In women, the onset of menopause or menopausal transition plays a role. Likewise, the massive decrease in estradiol supports the decrease in muscle mass and promotes the development of sarcopenia [1,2,3]. The likelihood of metabolic diseases such as Type 2 diabetes mellitus and metabolic syndrome also strongly increases [1,4]. There are numerous studies demonstrating the beneficial effects of exercise in the prevention and therapy of muscle mass loss, sarcopenia, metabolic syndrome, and risk for cardiovascular diseases [5,6,7,8,9,10,11]. The reduction in muscle mass during aging is due to a decrease in physical activity, and an imbalance between muscle-protein synthesis and breakdown. This can lead to the development of sarcopenia [10,12], which negatively impacts the functional capacity and quality of life of affected persons [12,13]. The revised 2019 version of the guidelines of the European Working Group on Sarcopenia in Older People (EWGSOP) emphasizes muscle strength as the main determinant, as it is best suited for predicting the adverse outcomes of sarcopenia [14]. Naseeb and Volpe summarized that protein supplementation and long-term aerobic exercise reduce the age-related loss of muscle strength [15]. An age-related decrease in muscle mass, even if it cannot be defined as sarcopenia, is a general risk in the aging population [15,16] that menopause promotes [16]. Avoiding a decrease in muscle mass and strength with physical training [17] is important for the prevention of a variety of age-related diseases. Aging is often accompanied by a decrease in physical activity [10]. In many cases, musculoskeletal disorders such as osteoarthritis cause this [17,18], but there are various additional reasons, including psychological ones [19,20]. Untreated, these impairments lead to an increased risk of becoming frail. Frailty syndrome is characterized by reduced activity and gait speed, a decrease in body strength, fatigue, and weight loss. Sarcopenia, stroke, myocardial infarction, arterial hypertension, and diabetes mellitus are closely related to the syndrome. A reduction in risk factors, and endurance, strength, and coordination training affect the risk of frailty syndrome [8]. The beneficial effects of physical activity on the maintenance of skeletal muscle mass are supported with protein supplementation [10]. There is a difference between protein supplementation that aims to compensate for the lack of protein intake through a normal diet and a situation with higher protein needs. The first scenario is typical for geriatric or cachectic individuals [21]. The adequate plasma levels of essential amino acids have a positive effect on muscle protein synthesis [22]. Chronic inflammatory processes that are exacerbated in old age by the decrease in estrogen and the increase in visceral adipose tissue favor proteolysis over protein synthesis. Thus, the breakdown of dietary proteins is imbalanced with the formation of new proteins from amino acids in cells. The result is an increased demand for proteins for equivalent and sufficient muscle protein synthesis in older adults [21,23]. A 2015 data analysis conducted by Gregorio et al. on postmenopausal women identified that about $25\%$ of the population had lower protein intake than the daily recommendation [24]. This same subgroup showed a significant limitation in upper- and lower-extremity functionality. However, for the majority of postmenopausal women and older individuals, protein via supplementation is not needed as a strategy to compensate for a lack of protein uptake. Nevertheless, protein uptake in such individuals, as in younger ones, can support the functional adaptation of the skeletal muscle to a training stimulus [25]. After exercise, the intake of an additional 20–25 g of protein is recommended [21]. Amino acid availability shows a positive effect on muscle development, lean and muscle mass, and muscle strength. Likewise, it increases the plasma concentrations of IGF-1. Protein intake also positively influences calcium absorption and, thus, supports bone health [2]. Studies showed that the combined intake of proteins and carbohydrates leads to higher glycogen storage in the skeletal muscle, and a higher increase in blood sugar and insulin concentration than those of just carbohydrate combinations [26]. The increase in serum insulin levels entails the binding of insulin to IGF-1 receptors, which stimulates muscle protein synthesis in the skeletal muscle and the uptake of amino acids into skeletal muscle cells via various processes [27]. Isenmann et al. compared the intake of a protein/carbohydrate combination via shakes and natural foods by directly following a workout with regard to the regenerative effect on the muscles. The results showed that shakes and supplementation via a natural protein source could equally reduce muscle damage after exercise, and insulin was involved in the regenerative effects [27]. Lichtenberg and colleagues showed that training with protein supplementation using powders also resulted in significant muscle and strength gains in sarcopenic seniors [28]. In those studies, however, supplementation was always via powders or capsules and never via food. In addition, the studies in the available reviews were not consistent. Different supplements, compositions, and time points were used [29,30]. Trommelen et al. indicated that age, and the type and timing of supplementation play a decisive role, so supplementation should be specifically adapted to, for example, age [31]. Eating dairy products and white bread has proregenerative effects on skeletal muscle after exercise [32]. On the basis of the work of Diel and colleagues, and Isenmann and colleagues, this study examines whether the combined uptake of protein and carbohydrates directly after training from natural protein sources could also result in an increase in training adaption, mainly muscle strength, in postmenopausal women and old individuals. ## 2.1.1. Study Design and Participants The study was a randomized intervention with 2 (CG and IG) parallel groups. We recruited 58 women between 50 and 65 years old in Germany by using personal contacts, calls on social media, gynecologists as gatekeepers, or the newsletter of the German Menopause Society (Figure 1). The sample size was determined on the basis of preliminary studies by Wacker [33]. The study started in January 2021 and was completed in November 2021. All examinations took place at the German Sport University, Cologne under the current valid COVID-19 protection regulations. Inclusion criteria were postmenopausal status, and the last menstrual period had to have been at least two years earlier. Exclusion criteria were hormonal diseases, metabolic diseases, cardiac arrhythmias requiring treatment, and limiting neurological, muscular, degenerative, or gastrointestinal diseases. Participants with a history of cancer within the past 5 years were excluded. Unbalanced diets such as vegan diets, smoking, and hormonal substitutions of any kind were excluded. All women had a low-to-moderate fitness status and none of them exercised more than twice per week in terms of strength or endurance training. Prior to recruitment, the approval of the ethics committee of the German Sport University, Cologne (number $\frac{008}{2021}$) was obtained, and the study was registered in the German Clinical Trials Register, number DRKS-ID: DRKS00024144. The study protocol was in accordance with the Declaration of Helsinki. After the study procedure had been communicated via telephone, and the inclusion and exclusion criteria had been checked, the women received all information in paper form. Subsequently, an appointment was booked to sign the informed consent form, clarify questions, and start with the examinations. All 63 participants signed the informed consent form. ## 2.1.2. Test Day All participants fasted, with their last meal 12 h before the examination. After the blood samples had been collected, anthropometric data (weight, height, abdominal girth, and body composition) were collected via bioimpedance analysis (BIA) (BodyExplorer, Kommunikation & Service GmbH, Berliner Chaussee 74, 15234 Frankfurt, Oder). The blood was analyzed by the Wisplinghoff laboratory; parameters to determine postmenopausal status were estradiol, progesterone, and follicle stimulating hormone (FSH). To determine endurance capacity, a lactate threshold test was performed on a treadmill (Woodway PPS55med, Woodway GmbH, Steinackerstr. 20, 79576 Weil am Rhein): participants started at 5 km/h, and the speed was increased by 1.2 km/h every 5 min. Termination criteria for the test were reaching the maximal heart rate (220 minus age), feeling unwell or exhausted, or reaching 20 in the BORG scale. Hand-grip strength was tested via a grip test; to determine the maximal force for the chest via a chest press and leg strength via a leg press, the repetition maximum was tested according to Rühl [34]. According to Rühl, 1RM is calculated based on preformed repetitions. All participants were randomly divided into an intervention group and a control group using a computer program (RITA version 1.51) while taking into account the parameters of age, weight, and walking speed (km/h) at $60\%$ of the 4 mmol lactate/threshold. Before randomization, participants were stratified by age (<55, 55–60, >60 years old), by weight (<70, 70–90, >90 kg), and walking speed (km/h) at $60\%$ of the 4 mmol/threshold (<4, 4–5, >5 km/h). ## 2.1.3. Training Intervention Each woman received an individual parameter for endurance training. Over 3 weeks, for familiarization, walking training took place at a speed corresponding to $60\%$ of the 4 mmol lactate threshold. Walking speed and heart rate were monitored by using sports watch Polar Ignite for training supervision. Subsequently, training was increased to $70\%$ km/h of the 4 mmol lactate threshold for the following 4 weeks. Then, for the last 5 weeks, the training was at $75\%$ km/h of the 4 mmol lactate threshold. All data were stored in the Polar Coach and tracked by the study management. Online strength training was offered twice a week via Cisco Webex Meetings (Cisco Systems GmbH). An alternate appointment was offered if participants were absent. The intervention and control groups completed the strength training together. All participants had to attend $80\%$ of endurance training and $100\%$ of strength training. Strength training consisted of bodyweight exercises such as squats, crunches, dips, and planks for all major muscle groups, such as M. quadriceps femoris, M. ischiocrurales, Mm. pectorales, M. triceps brachii, M. biceps brachii, Mm. glutei, and the trunk muscles. The gluteal and abdominal muscles must be constantly tensed to keep the body tense. The first 4 weeks were used for familiarization and a successive increase in intensity. Thus, we started with 10 repetitions in 3 sets, and increased to 12 repetitions in 3 sets. This was followed by an increase to 10 to 12 repetitions in 4 sets in the following 3 weeks. In the 8th week, a load–relief phase was scheduled with 8–10 repetitions in 4 sets before increasing to 12–15 repetitions in 4 sets in the last 4 weeks. In addition, the intensity of the exercises was increased through changes in execution. Each training session was organized as circuit training, so the strained muscle groups were changed and had time to relax. The cardiovascular system, however, was constantly strained. During the 12 weeks of the intervention, the women were not allowed to participate in other kind of sports (Figure 2). ## 2.1.4. Nutritional Intervention The intervention group received protein/carbohydrate supplementation consisting of 100 g of sour milk cheese (Käserei Loose) and 76 g of white bread immediately after each training session. The nutritional values of the meal were 36.1 g protein, 35.3 g carbohydrate, 3.5 g fat, and 321 kcal. Sour milk cheese was provided by Käserei Loose, Leppersdorf, Germany (Table 1). ## 2.2.1. Study Design and Participants The study was designed as a randomized intervention study with two parallel groups (IG and CG). We included 35 participants in the randomization (Figure 3). Simple randomization was used, and care was taken to ensure an equal distribution ofparticipants. Stratification based on gender, age and weight data was performed during randomization. The sample size was determined on the basis of preliminary studies and the results of Gaedtke [2014]. All participants completed sling training based on Gaedtke [35,36,37]. All men and women were recruited in the Ruhr area. Inclusion criteria were an age above 60 years and having been active in sports for at least one year. Exclusion criteria were an acute disease of the musculoskeletal system, cardiovascular diseases, and experience with sling training. After the study procedure had been communicated via telephone, and the inclusion and exclusion criteria had been checked, the interested participants received all information in paper form. Subsequently, an appointment was booked to sign the informed consent form, clarify existing questions, and start with the examinations. Prior to recruitment, the approval of the ethics committee of the German Sport University, Cologne (number $\frac{82}{2015}$) was obtained. The study protocol was in accordance with the Declaration of Helsinki. The examinations and training sessions took place in a training center for seniors in Essen-Bochold and Gelsenkirchen-Mitte. ## 2.2.2. Test Day The maximal force for chest (chest press) and leg (leg press) strength was established via the repetition maximum according to Rühl [34,38]. The Swiss Olympic trunk test was also performed for the ventral, dorsal, and lateral trunk muscles. The following program was followed according to Tschopp [39,40]. After a 10 min warm-up, ventral, lateral, and dorsal trunk strength was tested. The participants always had a 10 min break between individual tests. Ventral trunk strength: From a plank position, feet were lifted alternately while contact had to be maintained with a control bar on the head and glutes. The time for which the correct position could be maintained was measured. Lateral trunk test: From lateral support, the pelvis was lowered and raised again, and contact with the control bar on the pelvis had to be repeatedly established. The seconds were counted. Dorsal trunk test: From a prone position on a box, the upper body was lowered and raised again, and the control bars had to be touched. The seconds were counted. ## 2.2.3. Training Intervention The only training during the 12 weeks of intervention was sling training. Training took place three times per week (Monday, Wednesday, and Friday) and lasted 30 min. The whole group was divided into smaller groups of 3 to 6 to create a safe training situation. The intervention and control groups completed the training together. The training was divided into 4 training phases of 2 weeks. In the first phase of training, the participants were familiarized with the equipment, and the workout took place, so low intensity and high repetitions were used. Training control was performed with four different variations of an exercise (A–D), where A represented the easiest and D the most challenging variation. In the different variants, the difficulty was increased by reducing the support base (principle of the support base) [37]. Each training session included 7 exercises with 90 s rest between each exercise. The exercises were divided into:Two exercises for the upper body (rowing and chest press).Two exercises for the legs (squat and hip abduction).Two exercises for the trunk (crunches and side bend).One exercise for the entire ventral chain (body stretching). The sequence of exercises was chosen so that one muscle group was not used twice in succession. Body tension is the basis of every exercise. The gluteal and abdominal muscles must be constantly tensed to keep the body in extension. In addition, the shoulders always remain low, and the neck relaxed. These points were emphasized in each unit. The number of repetitions Increased after a subject had achieved two more repetitions on one exercise in the last set over two training sessions (progressive overload). This ensured progression in the training, which started with 8 repetitions and ended with 12. Once the 12 repetitions had been reached, the intensity was increased using the OMNI Res value. For this purpose, the trainer asked for a value between 1 and 10 after each set, where 1 meant very low effort and 10 meant very high effort [41]. On the basis of the training goal, 6 and 8 was the optimal intensity range. Using the settings, the suspensions or variant intensity could be increased if the value was less than 6 or decreased if the value was greater than 8 (Figure 2). ## 2.2.4. Nutritional Intervention After the training session, the intervention group received 100 g of sour milk cheese (Käserei Loose), 76 g of white bread, and 250 mL buttermilk immediately after each sling training session. The nutritional values of the meal were 44.6 g protein, 45.8 g carbohydrate, 5 g fat, and 416 kcal. Sour milk cheese and buttermilk were provided by Käserei Loose, Leppersdorf, Germany (Table 1). After each training session, all participants remained in the training center for 30 min to ensure that only the intervention group received the protein/carbohydrate supplementation. ## 2.3. Statistical Analysis Strength data were normalized to body weight prior to further analysis. Subsequently, they were processed with principal component analysis (PCA). All variables had been mean centered and scaled to unity variance. The total variances of the datasets thus amounted to 4.0 (Study A) and 6.0 (Study B). PCA was performed on the data acquired before the intervention periods. Postintervention data then were submitted to PCA transformation using previously obtained coefficients. This procedure facilitated the detection of possible changes in the latent variables represented by the strength dataset. The variables extracted with PCA were then analyzed with linear mixed-effect models (LME). As we were interested in the experimental effects of training intervention combined with supplementation, the fixed effects consistently encompassed these factors and their corresponding interaction term. For Study B, the subjects were classified according to their adiposity status (BMI > 30). Adiposity served as an additional covariate with two levels (adipose: Adip+, not adipose: Adip−). Because participants in Study B were significantly more overweight and also obese compared to participants in Study A, we decided to analyze weight as a covariate. In addition, the interaction of adiposity and training intervention was included. The incorporation of higher-order interaction terms was not feasible due to the restricted sample size. Time (i.e., training intervention) grouped within individuals consistently served as a random effect. The used software was the latest version of statistical language R [42]. LMEs were fitted with the use of R’s standard nlme library [43]. The assessors were not blinded, but the data analysis staff were blinded in both studies. ## 3.1. Study A A total of 51 postmenopausal women (57.3 ± 3.0 years) finished the study (Table 2). Reasons for dropouts were diseases/injuries ($$n = 4$$), elevated hormone levels that did not meet the inclusion criteria ($$n = 4$$), and too much time expenditure ($$n = 4$$). None of the diseases or injuries were related to training. Table 3 shows the changes in the strength and body composition of the intervention and control groups; all strength parameters could be increased. PCA showed that the individual strength parameters could be represented as a general strength score. There was a significant training effect, but the effect of the influence of supplementation was not significant. A change in body composition with a reduction in fat and an increase in muscle mass was also evident. ## 3.1.1. PCA The PCA yielded merely one significant component, i.e., one variable with variance larger than unity (PC1) that contained $0.65\%$ of the total variance. Therefore, all four strength values (chest strength, leg strength, and left- and right-hand-grip strength) were combined into one strength value, the general strength score (GS). ## 3.1.2. LME Figure 4 shows the changes in general Strength score (intervention group = Treat; control group = Ctrl). Table 4 shows the significant changes due to training. Training intervention had a positive and strongly significant effect o (+0.65, p ≤ 0.001) but supplementation had no detectable additional effect (ca. 0, p = ca. 0.85). Figure 4 shows significant increases in general strength. ## 3.2. Study B A total of 31 participants comprising 6 men and 25 women finished the study (65.9 ± 4.9 years) (Table 5). We excluded 3 participants during the 12 weeks because of injuries. None of the diseases or injuries were related to training. ## 3.2.1. PCA Table 6 shows strength increase and body-weight decrease values. All participants gained strength and lost body weight. Using PCA, two strength scores (limb strength and trunk strength) could be formed from the six strength values (leg, chest, ventral-trunk, dorsal-trunk, and left and right lateral-trunk strength). PCA yielded two significant components, PC1 and PC2, with $0.55\%$ and $0.25\%$ of the total variance, respectively. Thus, the cumulative variance amounted to $80\%$. ## 3.2.2. LME Table 7 and Table 8 show the parameters of the LMEs fitted to trunk-strength (TS) and limb-strength (LS) data, respectively. TS significantly increased during the training intervention (+2.305, p ≤ 0.001). While adipose subjects exhibited lower starting values (−1.683, p ≤ 0.05), they also react significantly more weakly to the training intervention (−1.513, p ≤ 0.01). Dietary supplementation yielded an additional and significant positive effect on TS (+0.950, p ≤ 0.05) (Table 7 and Figure 5). LS significantly increased after the training intervention (+0.753, $p \leq 0.05$). Apart from a weak initial trend of adipose subjects showing stronger values (+0.942, $$p \leq 0.096$$), there were no further significant terms in the model (Table 8 and Figure 6). ## 4. Discussion We compared two different training types in combination with protein/carbohydrate supplementation via food immediately after training in postmenopausal women, and elderly men and women. Both studies showed a positive effect of training; sling training increased limb and especially trunk strength in elderly men and women. Gaedtke showed significant results on chest-muscle strength in elderly people through sling training [35]. Various studies showed a positive effect of sling training on muscle mass in general and the trunk muscles in particular [36,44,45,46,47]. Trunk-muscle strength was more promoted in the IG after the consumption of sour milk cheese, bread, and buttermilk than that in the CG. We were not able to show this effect in limb strength. However, training was significantly more effective in the intervention group. Sling training is common as a treatment for lower-back pain, which is often triggered by a deficit in the trunk muscles. Local trunk muscles are a possible explanation for the larger effects in trunk strength [48,49]. Protein/carbohydrate supplementation seemed to be able to intensify these positive effects (Figure 5), perhaps due to the proregenerative effects that Isenmann and colleagues described [27]. The elderly participants regularly use their leg and chest muscles in everyday life, so the proregenerative effects could not show a large effect. However, as aging trunk muscles slim down, sling training with a focus on trunk stabilization, like our training, is a great challenge and requires these muscles. The training was offered three times per week. Therefore, there may be proregenerative effects, such as an increase in insulin serum concentration, a decrease in proinflammatory markers, and an increase in anti-inflammatory markers. Isenmann and colleagues showed these effects in young men after a similar protein/carbohydrate supplementation via food immediately after training [27]. The positive proregenerative effect of protein/carbohydrate supplementation after training was also shown by other authors [26,50]. Zawadzki and colleagues showed that the administration of a protein/carbohydrate combination right after training could enhance glycogen storage in muscles, which contributes to faster recovery. Leg and chest strength also increased over the 3 months, but this effect was not increased via protein/carbohydrate intake [50]. The significant training effect was less pronounced in participants with a higher BMI (>30) than that in participants with a lower BMI (Figure 5 and Figure 6). A possible explanation could be that, with greater body weight, the sling exercises could not be performed as well or could only in simpler variations, which could have caused a reduced training effect. Morat et al. showed that variations in body angle while training intensify the sling training [47]. On the other hand, the participant group was more likely to have the high body fat percentage that caused the high BMI. Since untrained and overweight individuals usually experience faster and greater effects with the same training than those of persons with normal weight, such effects were also more likely here [51]. Therefore, it is reasonable to assume that sling training was not as effective for heavier participants. In summary, a significant increase in strength was achieved in the seniors as a result of the training, which is a very positive effect, especially with regard to the risk of sarcopenia. Supplementation with food in the form of an evening meal increased trunk strength more significantly, which is an important aspect with regard to frailty in old age. The combination of endurance and strength training for postmenopausal women could increase strength and made the women feel more fit. We showed effects in whole body strength, which consists of chest, leg, and hand-grip strength. The effect on the hand grip is important for postmenopausal women because many of them have low bone and low muscle mass, which comes with a low hand grip. In addition, low hand-grip strength is associated with a low quality of life [52]. Using principal component analysis, we and other authors showed that hand-grip strength could be used as an indicator of overall body strength [53]. So, these findings are in line with the increase in and the role of hand-grip strength. Thus, the increase in hand-grip strength may explain the increase in the subjective fitness status of the participants. Leg and chest strength was analyzed via the repetition maximum, which is a possible reason for the lesser effects. In this repetition method, the one repetition maximum (1 RM) is not tested, but calculated on the basis of weight and repetitions. This method can be used especially for untrained and inexperienced people, and in medical training therapy [54]. In a heterogeneous group (experienced and inexperienced or trained and untrained participants), however, this can lead to errors or unequal results. We were not able to demonstrate a significant influence of supplementation even if hand strength increased more significantly. In Study B, there was a significant decrease in body weight; in Study A, we were unable to show this. However, participants in Study A with a BMI of 25.1 were normal to slightly overweight compared to the participants in Study B (BMI 30.9). In addition, in Study B, strength training was performed 3 times per week, whereas in Study A, moderate and fat-metabolism-oriented endurance training was performed twice per week, and strength training only once per week. Thus, endurance training had an effective effect on fat mass, whereas strength training had a faster effect on body weight [5]. Here, the exact determination of body composition in Study B would have been helpful. The limitations of our study are the missing analysis of insulin, skeletal-muscle creatine kinase, myoglobin, and serum cytokine levels in both studies that would have contributed to proving the proregenerative effect. Nutritional and protein statuses were not recorded before and during training in either study, which would have been useful in identifying possible deficiencies in the supply or oversupply of dietary protein, especially since the effect of protein/carbohydrate supplementation was so pronounced in older participants. One hypothesis here is that the postmenopausal women consume sufficient protein in their diet, while the seniors showed a deficit. In Study B, protein/carbohydrate supplementation was provided as a common meal in the evening after training: sour milk cheese, bread, and buttermilk. In Study A, this effect was absent because no communal meal was possible after training due to the COVID-19 pandemic. Thus, some participants trained in the morning and supplemented the protein/carbohydrate combination afterwards, and others trained in the evening. Due to the different training times, the supplementation was not taken together as a meal, which may have led to participants taking the supplementation in addition, while others replaced a meal with it. This could explain the missing change in body weight. The supervision of the consumption of sour milk cheese and bread after each training session was also lacking, which presumably reduced compliance among the women. In Study B, body composition was not determined, so conclusions could be drawn about the changes in body weight, but not about the exact body composition. These parameters would have been useful to see the influence of training and protein/carbohydrate intake on muscle and fat mass. Since the body weight of the subjects in Study B were significantly higher (85.4 ± 15.6 kg) than those in Study A (69.7 ± 12.7 kg), the exact body composition would have been an interesting parameter to compare baseline muscle and fat mass because a significantly lower baseline value would be assumed for the seniors, according to [17,55]. Study B also showed that the training effect was less pronounced in participants with a higher BMI (>30) than that in lighter participants. This may have been due to the nature of the training, as the participants’ entire weight had to be carried on the slings. This is much more difficult with a greater body weight and may mean, for example, that the exercises could only be increased more slowly. ## 5. Conclusions Our results indicated that a combination of training and protein/carbohydrate supplementation via food directly after training may be a suitable strategy to counteract the age-related loss of trunk strength in seniors. 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--- title: Using a Hybrid Neural Network and a Regularized Extreme Learning Machine for Human Activity Recognition with Smartphone and Smartwatch authors: - Tan-Hsu Tan - Jyun-Yu Shih - Shing-Hong Liu - Mohammad Alkhaleefah - Yang-Lang Chang - Munkhjargal Gochoo journal: Sensors (Basel, Switzerland) year: 2023 pmcid: PMC10059063 doi: 10.3390/s23063354 license: CC BY 4.0 --- # Using a Hybrid Neural Network and a Regularized Extreme Learning Machine for Human Activity Recognition with Smartphone and Smartwatch ## Abstract Mobile health (mHealth) utilizes mobile devices, mobile communication techniques, and the Internet of Things (IoT) to improve not only traditional telemedicine and monitoring and alerting systems, but also fitness and medical information awareness in daily life. In the last decade, human activity recognition (HAR) has been extensively studied because of the strong correlation between people’s activities and their physical and mental health. HAR can also be used to care for elderly people in their daily lives. This study proposes an HAR system for classifying 18 types of physical activity using data from sensors embedded in smartphones and smartwatches. The recognition process consists of two parts: feature extraction and HAR. To extract features, a hybrid structure consisting of a convolutional neural network (CNN) and a bidirectional gated recurrent unit GRU (BiGRU) was used. For activity recognition, a single-hidden-layer feedforward neural network (SLFN) with a regularized extreme machine learning (RELM) algorithm was used. The experimental results show an average precision of $98.3\%$, recall of $98.4\%$, an F1-score of $98.4\%$, and accuracy of $98.3\%$, which results are superior to those of existing schemes. ## 1. Introduction In 2019, the World Health Organization (WHO) proposed guidelines for digital health interventions which provide information on the potential benefits, harms, feasibility, and resources required for such interventions [1]. Digital health techniques include mobile health (mHealth) and electronic health (eHealth) and have been recognized as important tools for combating pandemic diseases [2,3]. mHealth employs mobile devices, mobile communication techniques, and the Internet of Things (IoT) to enhance healthcare in various areas, including traditional telemedicine, healthcare monitoring and alerting systems, drug-delivery programs, and medical information awareness, detection, and prevention [4,5,6]. Presently, smartphones and smartwatches are the most important mobile devices in mHealth [7,8]. They are equipped with various sensors and have many applications in the monitoring, prevention, and detection of diseases. In more advanced services, they can even provide basic diagnoses for conditions such as cardiology [9,10], diabetes [11,12], obesity [13,14], smoking cessation [15], and chronic diseases [16]. Health and fitness applications (apps), which can detect the numbers of steps walked and stairs climbed in a day using accelerometers and gyroscopes, are the most popular apps. These physical activities are used to calculate the number of calories spent. Over the past decade, recognition of physical activities has been applied to prevent falls among the elderly [17,18,19]. However, with the COVID-19 pandemic and an aging society, monitoring quarantined or elderly individuals has become a major issue in mHealth. Numerous studies have shown that people’s activities have strong correlations with their physical and mental health [20,21]. Therefore, recognizing physical activities using accelerometers and gyroscopes embedded in smartphones and smartwatches is a critical challenge in mHealth. In recent years, deep learning (DL) and machine learning (ML) have been widely applied in mHealth [22,23,24,25]. In these studies, DL and ML models are not only used for diagnosing, estimating, mining, and delivering physiological signals, but also for preventing chronic diseases. However, in mHealth, the big data need to be delivered to servers, such as hospitals or health management centers. Therefore, telecommunications and navigation technologies are also important, in which the technologies of artificial intelligence have been applied [26,27]. Stefanova-Pavlova et al. proposed the refined generalized net (GN) to track users’ locations [28]. Silva et al. used Petri nets to process the reliability and availability of wireless sensor networks in a smart hospital [29]. Ruiz et al. proposed a tele-rehabilitation system to assist with physical rehabilitation during the COVID-19 pandemic [30]. Convolutional neural networks (CNNs) can extract features from signals, while long short-term memory (LSTM) can recognize time-sequential features. Therefore, some studies have proposed deep neural networks that combine CNNs and LSTM to recognize physical activities [31,32]. Li et al. utilized bidirectional LSTM (BiLSTM) for continuous human activity recognition (HAR) and fall detection with soft feature fusion between the signals measured by wearable sensors and radar [33]. The extreme learning machine (ELM) has shown excellent results in classification tasks with extremely fast learning speed [34]. Chen et al. proposed an ensemble ELM algorithm for HAR using smartphone sensors [35]. Their results showed that the performance was better than those of other methods, such as artificial neural networks (ANNs), support vector machines (SVMs), random forests (RFs), and deep LSTM. In order to improve the accuracy of HAR systems, more complex deep learning models have been proposed. Tan et al. used smartphone sensors for HAR. They proposed an ensemble learning algorithm (ELA) that combined a gated recurrent unit (GRU), a hybrid CNN+GRU, and a multilayer neural network, then fused them with the fully connected three layers [36]. In 2020, the International Data Corporation (IDC) reported that wearable devices are being used more frequently to monitor health due to the COVID-19 pandemic, resulting in a $35.1\%$ increase in smartwatch sales [37]. Thus, more activities could be classified and higher accuracies could be approached if smartphones and smartwatches are synchronously used for HAR. Weiss et al. used smartphone and smartwatch sensors for HAR with an RF algorithm [38]. Mekruksavanich et al. also used smartphone and smartwatch sensors for HAR with a hybrid deep learning model called CNN+LSTM [39]. Prior studies have shown that adding hand-movement signals measured by smartwatch sensors can enhance the accuracy of HAR. To improve the accuracy of HAR systems, the development of more complex deep learning models will be necessary. Thus, this study focuses on recognizing 18 different physical activities, including body and hand movements, as well as eating movements, utilizing data from sensors embedded in smartphones and smartwatches. The recognition process involves two steps: feature extraction and HAR. To extract features, a hybrid structure was used that consisted of a CNN and a recurrent neural network (RNN), while a multilayer perceptron neural network (MPNN) was used for the recognition of activities. The RNN was replaced with various other models, such as LSTM, GRU, BiLSTM, and bidirectional GRU, to optimize the hybrid structure. The MPNN was trained separately using backpropagation (BP), the ELM, and the regularized ELM (RELM). The HAR dataset used in this study was obtained from the UCI Machine Learning Repository and specifically the WISDM smartphone and smartwatch activity and biometrics dataset [31]. According to the experimental results, the proposed HAR system demonstrated superior performance when compared to the systems developed in existing studies. ## 2. Materials and Methods The proposed HAR system has three components: a data processing unit, a feature extraction unit, and a classification unit, as illustrated in Figure 1. Physical activity signals are captured by a smartphone and a smartwatch and are subsequently sampled, segmented, and reshaped for further processing. The sensor data features are extracted using a hybrid CNN+RNN model. Finally, an MPNN is employed to classify the 18 types of physical activities. ## 2.1. UCI-WIDSM Dataset The UCI-WISDM dataset [40] is comprised of tri-axial accelerometer and gyroscope data obtained from 51 volunteer subjects. The subjects carried an Android phone (a Google Nexus $\frac{5}{5}$x or a Samsung Galaxy S5) in a front pocket of their pants and wore an Android watch (an LG G Watch) on their wrist while performing eighteen activities, which were categorized as body movements (walking, jogging, walking up stairs, sitting, and standing) included in many previous studies, hand movements (kicking, dribbling, catching, typing, writing, clapping, brushing teeth, and folding clothes) representing activities of daily life, and eating movements (eating pasta, drinking soup, eating a sandwich, eating chips, and drinking from a cup) to investigate the feasibility of automatic food-tracking applications [38]. The data were sampled at a rate of 20 Hz, and the 12 signals were segmented into fixed-width sliding windows of 6.4 s with $50\%$ overlap between them. Each sample contained 12-channel signals, and each channel comprised 128 points. Samples containing two activities were removed. The numbers of training and testing samples were 34,316 and 14,707, respectively, and the sample numbers for each of the eighteen activities are presented in Table 1. ## 2.2. Feature-Extraction Model Figure 2 illustrates a feature-extraction model that employs a hybrid CNN and RNN to extract the features of sensor signals. The fully connected layer, consisting of three layers, is used to classify the 18 types of physical activities. After training, the outputs of the RNN for the training samples serve as the feature samples to train the activation-classification models. Since the human movements in each activity occur in chronological order, the sensor signals represent time-sequential data. To address this, a time-distributed layer comprising four 1D CNNs (i.e., four pairs of CNNs with three layers and a maximal pool layer as the last layer) is stacked on top of the RNN. This separates a sample into four segments, with each segment containing 32 points. In the convolutional layer, the number of filters is 64; the kernel sizes are 3, 5, and 13; the stride is 1; and the padding is 4. In the pooling layer, the kernel size is 2, and the stride is 2. The activation function employed is ReLU. The RNN is replaced with the LSTM, BiLSTM, GRU, or BiGRU, with the unit numbers of LSTM and GRU set to 128 and those of BiLSTM and BiGRU set to 256. The batch size is set to 32, with the control reset gate and update gate using a sigmoid function and the hidden state using a tanh function. The numbers of full connection layers are 128, 64, and 18, respectively, with ReLU used as the activation function in hidden layers and softmax in the output layer. The loss function is the categorical Cross-Entropy (CE) function, and the Adam optimizer is used [41], with the learning rate set to 0.0001. Equation [1] is the formula for categorical CE:[1]CE=−log(exp(ak)∑$i = 1$Mexp(ai)) where M is 18, ak is the score of softmax for the positive class, and ai is the score inferred by the net for each class. ## 2.3. Activation-Classification Model The activation-classification model is a single-layer feedforward neural network (SLFN) with the ELM algorithm [42]. Its advantages are the convergent time being shorter than that of the BP method and its not converging to the local minimum. For an SLFN, a training set S = {(Xr, Yir\| Xi = (xr1, xr2, …, xrn)T ∈ Rn, Yr = (yr1, yr2, …, yrm)T ∈ Rm}, where Xr denotes the rth input vector and Yr represents the rth target vector. The output o of SLFN with l hidden neurons can be expressed as: [2]ok=∑$j = 1$lβkjf(WijXij+bj), $k = 1$,…, m, where f(x) is the activation function in the hidden layer, Wji is the weight vector from the input layer to the jth hidden node, Wji = (wj1, wj2, …,wjn) ∈ Rn, bj is the bias of the jth hidden node, βk is the weight vector from the hidden nodes to kth output layer, and l is the number of hidden layers. In the ELM, activation functions are nonlinear functions that provide nonlinear mapping for the system. Or is the rth output vector. Mean square error (MSE) is the object function:[3]MSE=∑$i = 1$N(Yi−Oi)2, where N is the number of samples. The MSE will approach 0 as the number of hidden nodes approaches to infinity. The output o of SLFN is equal to the target output y. Thus, Equation [2] could be described as follows:[4]yk=∑$j = 1$lβkjf(WijXij+bj), $k = 1$,…, m. Y = Hβ, [5] where Y is the output matrix, H is the matrix of the activation function in the hidden layer, and β is the weight matrix from the hidden nodes to the output layer. ELM uses random parameters Wij and bj in its hidden layer, and they are frozen during the whole training process. β = H†Y, [6] where H† is the Moore–Penrose inverse. The resident, εi, is between the target and output values of the ith sample. However, the ELM has the risk to approach the result of over-fitting model because it bases on the empirical risk minimization principle [43]. Den et al. proposed a regularized ELM (RELM) that used a weight factor γ for empirical risk [44]. [ 7]min12‖β‖2+12γ‖ε‖2, In order to obtain a robust estimate weakening outlier interference, εi can be weighted by a factor vi. Equation [7] is changed thus:[8]min12‖β‖2+12γ‖Dε‖2 where D=dialog(v1, v2, …, vN) and ε=[ε1, ε2,…,εN]. The method of Lagrange multipliers is used to search for the optimal solution of Equation [8]:[9]L(β, ε, α)=12‖β‖2+γ2‖Dε‖2−α(Hβ−O−ε) where α is the Lagrange multiplier with the equality constraints of Equation [9]. Setting the gradients of L(β,ε,α) equal to zero gives the following Karush–Kuhn–Tucker (KKT) optimality conditions [44,45]:[10]α=−γ(Hβ−T)T [11]β=(Iγ+HTD2H)†HTD2T [12]εi=αiγ, ($i = 1$, 2, …,N) ## 2.4. Experimental Protocol The hardware used in this study comprised an Intel Core i7-8700 CPU and a GeForce GTX1080 GPU. The operating system used was Ubuntu 16.04LTS, with development being conducted in Anaconda 3 for Python 3.7. The deep learning tool used was Pytorch 1.10, and the compiler used was Jupyter Notebook. To assess the proposed method’s performance, we evaluated the optimal feature-extraction model and the activation-classification model for HAR separately. In the feature-extraction model, the RNN was replaced with LSTM, BiLSTM, GRU, and BiGRU, separately. The training samples were used to adjust the parameters of the hybrid CNN+RNN, while the testing samples were used to evaluate the performances of these RNNs. The feature-extraction model that achieved the best performance was one in which the RNN outputs for all training and testing samples were used as the new training and testing samples to evaluate the activation-classification model. In the activation-classification model, a multilayer perceptron neural network (MPNN) was used to classify the 18 physical activities. The output number of the MPNN was 18, and the input number depended on the number of RNN outputs. The training algorithms used were BP, ELM, and RELM. The number (l) of hidden layers and the regularized parameter (γ) of RELM were optimized using the grid-search method to find the optimal values. ## 2.5. Statistical Analysis According to the proposed method, a sample was considered a true positive (TP) when the classification activity was correctly recognized, as a false positive (FP) when the classification activity was incorrectly recognized, as a true negative (TN) when the activity classification was correctly rejected, and as a false negative (FN) when the activity classification was incorrectly rejected. In this work, the performance of the proposed method was evaluated using the measures given by Equations [13]–[16]:[13]Precision (%)=TPTP+FP×$100\%$ [14]Recall (%)=TPTP+FN×$100\%$ [15]F1-score (%)=2×precision×RecallPrecision+Reacll×$100\%$ [16]Accuracy (%)=TP+TNTP∓TN+FP+FN×$100\%$ ## 3. Results In order to evaluate the effectiveness of the proposed method, we will present three sets of results: those for the feature-extraction model, the activation-classification model, and the training times of the models. ## 3.1. Analysis of the Feature-Extraction Model The learning curves for the hybrid CNN+LSTM model are depicted in Figure 3, where (a) and (b) represent the accuracy and loss curves, respectively. The blue line corresponds to the training data, while the original line corresponds to the validation data. The optimal values for the accuracy and loss function are achieved at epoch 29. When applied to the testing data, the model achieved an average precision, recall, F1-score, and accuracy of $93.8\%$, $93.8\%$, $93.8\%$, and $94.1\%$, respectively. The total training time for the model was 130.26 s. In Figure 4, the learning curves for the hybrid CNN+GRU model are presented, where (a) and (b) denote the accuracy and loss curves, respectively. The blue line represents the training data, while the original line represents the validation data. The optimal values for the accuracy and loss function are attained at epoch 28. When evaluated on the testing data, the model achieved an average precision, recall, F1-score, and accuracy of $92.6\%$, $92.6\%$, $92.5\%$, and $92.2\%$, respectively. The total training time for the model was 98.67 s. The learning curves for the hybrid CNN+BiLSTM structure are displayed in Figure 5, where (a) and (b) represent the accuracy and loss curves, respectively. The blue line corresponds to the training data, while the original line corresponds to the validation data. The optimal values for the accuracy and loss function are achieved at epoch 30. When applied to the testing data, the model achieved an average precision, recall, F1-score, and accuracy of $95.3\%$, $95.3\%$, $95.3\%$, and $95.3\%$, respectively. The total training time for the model was 138.86 s. In Figure 6, the learning curves for the hybrid CNN+BiGRU model are presented, where (a) and (b) denote the accuracy and loss curves, respectively. The blue line represents the training data, while the original line represents the validation data. The optimal values for the accuracy and loss function are attained at epoch 29. When evaluated on the testing data, the model achieved an average precision, recall, F1-score, and accuracy of $95.7\%$, $95.4\%$, $95.5\%$, and $95.2\%$, respectively. The total training time for the model was 108.69 s. Table 2 provides an overview of the performances of four feature-extraction models. Although the hybrid structures with BiLSTM and BiGRU require more training time per epoch than LSTM and GRU (4.60 s vs. 4.49 s and 3.74 s vs. 3.52 s, respectively), their testing accuracies are superior to those of LSTM and GRU ($95.3\%$ vs. $94.1\%$ and $95.2\%$ vs. $92.2\%$). Given that the hybrid structure with BiGRU saves $19\%$ of training time compared to BiLSTM and that their accuracies are very similar ($95.25\%$ vs. $95.3\%$), the feature-extraction model based on the hybrid CNN+BiGRU structure was chosen for building the HAR system. ## 3.2. Analysis of the Activation-Classification Model To classify the 18 types of physical activities, an MPNN was utilized, where the input and output nodes were set to 256 and 18, respectively. The MPNN was trained using three activation-classification algorithms: BP, ELM, and RELM. The performance of ELM and RELM was influenced by two parameters: the regularized index (γ) and the number of hidden layers (l). ## 3.2.1. Performance of the MPNN with the BP Algorithm The MPNN with the BP algorithm had two hidden layers with 128 and 64 nodes, respectively, where ReLU was used as the activation function in the hidden layers and softmax in the output layer. Table 3 shows the performances of the MPNN with the BP algorithm for 18 physical activities on the testing data. The model achieved an average precision of $97.1\%$, an average recall of $97.2\%$, an average F1-score of $97.2\%$, and an accuracy of $97.2\%$. The total training time was 10.563 s. Among the 18 activities, the worst F1-scores were obtained for the eating pasta, catching a ball, and eating a sandwich activities, which all involve hand and eating movements. ## 3.2.2. The Optimal Parameters of the RELM The SLFN utilized both ELM and RELM algorithms, and the optimal parameters for the RELM were determined using a grid-search method. For the RELM, the regularized index (γ) was set to 5 × 10−4, and the number of hidden layers was gradually increased from 256 nodes to 8000 nodes. Table 4 displays the testing accuracies and training times for various numbers of hidden layers. The highest accuracy of $98.35\%$ and a training time of 3.80 s were achieved with 6000 hidden nodes. After that, when l was fixed at 6000, γ gradually increased from 5 × 10−4 to 4. Table 5 shows the testing accuracies and training times for different regularized indexes. It was observed that the most accurate results and the highest training time were obtained when γ was set to 5 × 10−4. In Equation [7], the empirical risk, ‖ε‖2, is regularized by γ. Thus, the performances of the ELM and RELM would be close in this study. ## 3.2.3. Performances of the SLFN with the ELM and RELM Algorithms For the ELM algorithm, the SLFN had one hidden layer with 6000 nodes. Figure 7 shows the confusion matrix of the classification of eighteen activities. The performances of writing, clapping, brushing teeth, eating chips, and drinking from a cup activities were better than those for the ELM algorithm. Table 6 presents the performances of the SLFN with the ELM algorithm on the testing data. The model achieved an average precision of $97.9\%$, a recall of $97.9\%$, an F1-score of $97.9\%$, and an accuracy of $97.8\%$. The total training time was 7.52 s. The F1-scores for the eating pasta, catching a ball, and eating a sandwich activities rose to $98.0\%$, $96.4\%$, and $98.1\%$, respectively. For the RELM algorithm, l was set to 6000 for the SLFN, and γ was set to 5 × 10−4. Figure 8 shows the confusion matrix of the classification of eighteen activities. The eating pasta activity was easily confused with the drinking soup and drink from a cup activities. Catching a ball was easily confused with kicking a ball. Table 7 shows the performances of the SLFN with the RELM algorithm on the testing data. The model achieved an average precision of $98.3\%$, a recall of $98.4\%$, an F1-score of $98.4\%$, and an accuracy of $98.3\%$. The total training time was 3.59 s. The F1-scores for the eating pasta, catching a ball, and eating a sandwich activities rose to $98.1\%$, $97.6\%$, and $99.2\%$, respectively. ## 4. Discussion The proposed HAR system involves the use of a hybrid CNN+RNN model to extract activation features from accelerometers and gyroscopes in smartphones and smartwatches. This method was originally proposed by Tan et al. [ 36]. Since the accelerometer and gyroscope signals for activities are time-sequential, the performance of different RNN models can vary for HAR. In this study, LSTM, GRU, BiLSTM, and BiGRU were explored, and the classifying performances of BiLSTM and BiGRU were found to be very similar. However, BiGRU had a shorter training time than BiLSTM (108.69 s vs. 138.86 s) and was therefore used to extract the activation features. To enhance the performance of the classifier, the SLFN with the RELM algorithm was used. The ELM algorithm, which utilizes an SLFN with hidden neural weights and bias, was proposed by Huang et al. [ 46,47]. The ELM has an extremely fast training time and good generalized performance. Deng et al. proposed the RELM, which is based on the structural risk minimization principle of statistical learning theory and overcomes the drawbacks of the ELM [44]. Table 8 summarizes the total performances of the activation-classification models, the MLNN with BP, and the SLFN with the ELM and RELM. It was found that the classifying performances of the ELM and RELM were very similar ($97.8\%$ vs. $98.2\%$ accuracies). The reason for this was the very small regularized weight, γ. However, the training time of the ELM was shorter (7.52 s vs. 10.56 s). However, the RELM exhibited the best performance for HAR despite its longer total testing time (feature extraction plus classification) compared to the ELM (0.038 s vs. 0.025 s). Table 9 presents a comparative analysis of our proposed method with those of other studies that utilized the UCI-WISDM smartphone and/or smartwatch activity and biometrics dataset for six/eighteen activities. Previous studies [36,48,49,50,51,52] only classified six activities, while studies [38,39] classified eighteen activities. As shown, the proposed HAR system using the hybrid CNN+BiGRU model and the SLFN with the RELM achieved an F1-score and an accuracy of $98.4\%$ and $98.2\%$, respectively, which are among the best results reported in the literature. For the opening HAR datasets, the sensors, which are all accelerometers and gyroscopes, are embedded in smartphones or smartwatches or are body-worn [38,52]. The greater the number of sensors, the higher the accuracy of HAR. Table 10 displays the F1-scores of 18 physical activities using the accelerometers and gyroscopes embedded in the smartphones and smartwatches. We explored the performance of our proposed method when only using these sensors, specifically, either the accelerometers or the gyroscopes. When HAR used the sensors of the smartphones and smartwatches, the average F1-scores were $90.7\%$ and $89.1\%$, respectively. When only the accelerometers or gyroscopes of the smartphones and smartwatches were used for HAR, the average F1-scores were $94.1\%$ and $76.9\%$, respectively. These results suggest that the accelerometers provide more information than the gyroscopes for HAR. ## 5. Conclusions The proposed deep learning model utilizes the hybrid CNN+BiGRU for feature extraction from the signals of sensors embedded in smartphones and smartwatches and the SLFN with the RELM algorithm for the classification of 18 physical activities, including body, hand, and eating movements. The experimental results demonstrate that the proposed model outperforms other existing schemes that utilize deep learning or machine learning methods in terms of F1-scores and accuracy. Notably, the worst F1-score was found in the classification for brushing teeth. Our investigation shows that using different deep learning models for feature extraction and classification during the training phase can effectively increase recognition accuracy and training time. Moreover, since the data are recorded by smartphones and smartwatches, our proposed method has the potential to be used for mHealth in real time in environments without embedding of wireless sensor networks. The weakness of this study is that it ignores signals sent when two activities are transferring. Thus, in the future, we will explore this problem. ## References 1. WHO Guideline: Recommendations on Digital Interventions for Health System Strengthening 2. Wang Q., Su M., Zhang M., Li R.. 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--- title: 'Acceptability of Herpes Zoster Vaccination among Patients with Diabetes: A Cross-Sectional Study in Saudi Arabia' authors: - Dawood Al-Orini - Abdulrahman A. Alshoshan - Abdullah O. Almutiri - Abdulsalam A. Almreef - Essa S. Alrashidi - Abdulrahman M. Almutiq - Rehana Noman - Osama Al-Wutayd journal: Vaccines year: 2023 pmcid: PMC10059133 doi: 10.3390/vaccines11030651 license: CC BY 4.0 --- # Acceptability of Herpes Zoster Vaccination among Patients with Diabetes: A Cross-Sectional Study in Saudi Arabia ## Abstract Background: Vaccines have recently been made available free of charge by the Saudi Ministry of Health for people 50 years or older. Diabetes mellitus (DM) increases herpes zoster (HZ) susceptibility, severity, serious complications, and negative impacts on underlying DM conditions, which are highly prevalent in Saudi Arabia. This study aimed to assess the acceptability of the HZ vaccination and its predictors among patients with diabetes in the Qassim region of Saudi Arabia. Methods: A cross-sectional study of patients with diabetes from a primary healthcare center in the Qassim region was conducted. Information was obtained on sociodemographic characteristics, history of herpes zoster infection, knowing someone who had had herpes zoster, past vaccinations, and factors influencing their intention to receive the HZ vaccination through a self-administered online questionnaire. Results: The median age (IQR) was 56 years (53–62). Overall, $25\%$ ($$n = 104$$/410) of the participants reported their acceptability of the HZ vaccination, and the predictors were being male (AOR 2.01, $95\%$ CI 1.01–4.00, $$p \leq 0.047$$), believing the HZ vaccine was effective (AOR 3.94, $95\%$ CI 2.25–6.90, $p \leq 0.001$), and awareness that immunocompromised individuals are at a higher risk of contracting HZ (AOR 2.32, $95\%$ CI 1.37–3.93, $$p \leq 0.002$$). A total of $74.2\%$ ($$n = 227$$/306) of the participants reported their acceptability of the HZ vaccination if advised by their physician, and the predictors were being male (AOR 2.37, $95\%$ CI 1.18–4.79, $$p \leq 0.016$$) and having a history of varicella vaccine uptake (AOR 4.50, $95\%$ CI 1.02–19.86, $$p \leq 0.047$$). Conclusions: One-quarter of the participants were ready to accept the HZ vaccine, but this proportion significantly increased when the patients were advised by their physicians. The uptake rate can be improved with the involvement of healthcare providers and focused awareness campaigns about the effectiveness of the vaccine. ## 1. Introduction The Kingdom of Saudi Arabia (KSA) ranks second-highest in the Middle East for the rate of diabetes and has been reported as seventh of the top ten countries in the world by the World Health Organization (WHO), with seven million patients with diabetes and approximately three million pre-diabetic patients [1]. Patients with diabetes mellitus (DM) are highly susceptible to herpes zoster (HZ) disease [2]. The number of people living with diabetes is increasing worldwide, and according to the International Diabetes Federation (IDF), this number is estimated to reach one in ten people by 2035 [3]. In Saudi Arabia, $21.5\%$ of HZ cases are diabetic, and diabetes is the most common comorbidity of HZ infection [4]. Herpes zoster, also called shingles, is caused by the reactivation of the varicella-zoster virus (VZV), and this is the same virus that causes varicella (chickenpox) [5]. The connection between these two infections has been acknowledged for approximately 100 years and is determined by two observations, including a primary disease with VZV, which causes varicella, and once the varicella resolves, the virus remains latent in the dorsal root ganglia and can be reactivated later in the person’s life [2,4,5]. Herpes zoster (shingles) involves the sensory ganglion, nerves, and skin [5]. It causes unilateral radicular pain and a vesicular rash, which is limited to a single dermatome, related to the sensory ganglion in which the latent VZV is reactivated [6]. Studies have indicated that approximately $25\%$ of people develop HZ during their lifetime, and diabetes remains the main risk factor for HZ infection [7,8,9]. This is because patients with diabetes are at risk of various infections due to their impaired innate and adaptive immunity [10]. This has been affirmed by a number of studies showing that inadequate cell-mediated immunity, opsonization, and phagocytosis were weakened in patients with diabetes [11,12,13]. Another factor that plays a significant role in the reactivation of VZV among patients with diabetes is an imbalance in T-cell homeostasis [14]. Taking into account that DM is a common comorbidity with HZ and that it can lead to a substantial economic burden, the HZ vaccine can serve as a cost-effective measure [2,10,13]. Two vaccines are currently used for varicella and herpes zoster [15]. The first is the live attenuated vaccine (VZL), also known as ZOSTAVAX (OkaIMerck), which is administered in a one-dose schedule and is suitable for people aged 60 and above [16]. The other is the recombinant subunit glycoprotein E vaccine (RZV), also known as SHINGRIX, which is administered in a two-dose schedule and is suitable for people aged 50 and above [17]. SHINGRIX has been licensed by Saudi Arabia, and the Ministry of Health has recently announced its availability in all primary care centers of the Kingdom for those aged 50 and older or those aged 18 and older with immunocompromising conditions. For this reason, it is important to assess the acceptance of the herpes zoster vaccine (HZV) by patients with diabetes [18]. To the best of our knowledge, this is the first study aiming to assess the acceptability of the HZ vaccination and its predictors among patients with diabetes in the Qassim region of Saudi Arabia. ## 2.1. Study Design A quantitative cross-sectional study was conducted at a primary healthcare center in Al Bedaya city, Qassim region of Saudi Arabia, from November to December 2022. The eligibility criteria included being 50 years or older, being registered at a primary healthcare center in Al Bedaya city, and being diagnosed with diabetes mellitus. We utilized a convenience sample, and patients who were potentially eligible received a message/call from their physician (D.A.) inviting them to participate in the study. A link was sent to those who were interested to complete a self-administered online questionnaire. The validated questionnaire was prepared according to the research objectives of this study [19,20]. It consisted of items collecting the demographic characteristics of the participants (age, gender, educational level, and employment status), along with several items about awareness of varicella, herpes zoster and its vaccine, willingness to accept the HZ vaccination, reasons for HZV hesitancy, and willingness to accept the HZ vaccination if advised by a physician. A pilot study was conducted with 25 patients with diabetes, and the results from the pilot were not included in this study. The minimum sample size was determined with OpenEpi software, and it was found to be 424. The assumptions included a $5\%$ margin of error, a confidence interval (CI) of $95\%$, a level of HZ vaccination acceptance at $50\%$ to obtain the maximum sample size, and $10\%$ added to account for incomplete or missing responses. ## 2.2. Data Analysis The data were analyzed using STATA software version 16. The data are presented as frequencies and percentages for the categorical variables. A simple logistic regression was performed to assess the association between the independent variables and two dependent variables (acceptability of HZ vaccination and acceptability of HZ vaccination if advised by a physician), and variables with a p-value of <0.25 were included in the multiple logistic regression. The crude and adjusted odds ratios in the simple and multiple logistic regression analysis models are reported, respectively. A two-sided p-value of ≤0.05 was considered strong evidence against the null hypothesis. ## 3. Results The response rate was $91.7\%$. We approached 450 participants and obtained 410 complete responses (Figure 1). ## 3.1.1. Participant Characteristics A total of 410 participants were included in this study; the median (IQR) age of the participants was 56 (53–62) years, 270 ($66\%$) were male, 260 ($63.4\%$) had university-level or higher education, and 115 ($28\%$) were employed. A majority of the participants ($$n = 351$$, $85.6\%$) knew that there was a disease called varicella, approximately one-third ($$n = 151$$, $36.8\%$) had had varicella disease in the past, and only a few had received the varicella vaccine ($$n = 35$$, $8.5\%$). Just over half of the participants knew about herpes zoster (shingles) infection ($$n = 234$$, $57\%$), only 23 ($6\%$) had a previous history of HZ, and 251 ($61\%$) knew someone who had been infected with HZ. Half of the participants ($$n = 219$$, $53\%$) were acquainted with the availability of the HZ vaccine, but only 82 ($20\%$) believed that it was effective. Only 27 ($6.9\%$) knew that an individual was at high risk of contracting HZ if they had suffered from chickenpox in the past, and approximately one-third ($$n = 138$$, $33.7\%$) were aware that immunocompromised individuals were at a higher risk of contracting HZ than immunocompetent individuals (Table 1). ## 3.1.2. Predictors of Vaccination Acceptability Overall, $25\%$ ($$n = 104$$/410) of the participants were willing to get the HZ vaccine. According to the bivariate analysis, participants were more likely to be willing to get the HZ vaccine if they were male (COR 1.67, $95\%$ CI 1.02–2.74, $$p \leq 0.043$$), knew about HZ infection (COR 1.68, $95\%$ CI 1.06–2.68, $$p \leq 0.028$$), knew someone who had been infected with HZ (COR 1.69, $95\%$ CI 1.05–2.73, $$p \leq 0.031$$), knew that there was an HZ vaccine (COR 1.94, $95\%$ CI 1.22–3.08, $$p \leq 0.005$$), believed that the HZ vaccine was effective (COR 5.17, $95\%$ CI 3.09–8.67, $p \leq 0.001$), knew that people were at higher risk of contracting HZ if they had had chickenpox (COR 4.13, $95\%$ CI 1.86–9.15, $p \leq 0.001$), and knew that immunocompromised individuals were at a higher risk of contracting HZ (COR 3.19, $95\%$ CI 2.01–5.05, $p \leq 0.001$). In the multivariable analysis, the variables that remained statistically significant predictors were being male (AOR 2.01, $95\%$ CI 1.01–4.00, $$p \leq 0.047$$), having a belief that the HZ vaccine was effective (AOR 3.94, $95\%$ CI 2.25–6.90, $p \leq 0.001$), and knowing that immunocompromised individuals are at a higher risk of contracting HZ (AOR 2.32, $95\%$ CI 1.37–3.93, $$p \leq 0.002$$) (Table 2). ## 3.1.3. Reasons for HZ Vaccination Hesitancy The reasons for vaccine hesitancy listed by our study respondents included concerns about side effects ($31.6\%$), self-perceived immunity from HZ ($25.4\%$), generally not being in favor of vaccination ($14.4\%$), doubts about HZ vaccine effectivity ($9.5\%$), a belief that HZ is not a serious and severe infection ($6.9\%$), low prioritization of the HZ vaccination ($3.3\%$), and others ($8.9\%$). ## 3.2.1. Participant Characteristics A total of 306 participants were asked about their acceptability of the HZ vaccine if advised by their physician. Their median (IQR) age was 56 (53–61) years, 193 ($63\%$) were male, 190 ($62\%$) had university-level or higher education, and 85 ($27.8\%$) were employed. The majority of the participants ($$n = 260$$, $85\%$) knew that there was a disease called varicella, approximately half ($$n = 107$$, $35\%$) had had varicella disease in the past, and only a few had received the varicella vaccine ($$n = 26$$, $8.5\%$). Just over half of the participants knew about herpes zoster (shingles) infection ($$n = 165$$, $53.9\%$), very few ($$n = 14$$, $4.6\%$) had a history of HZ, and most ($$n = 178$$, $58\%$) knew someone who had been infected with it. Half of the participants ($$n = 151$$, $49.3\%$) knew about the availability of the HZ vaccine, but not many ($$n = 38$$, $12.4\%$) believed that it was effective. Only a few ($$n = 12$$, $3.9\%$) knew that an individual was at high risk of contracting HZ if they had suffered from chickenpox in the past, and approximately one-quarter were aware that immunocompromised individuals were at a higher risk of contracting HZ than immunocompetent individuals ($$n = 82$$, $26.8\%$) (Table 1). ## 3.2.2. Predictors of Vaccination Acceptability A total of $71.5\%$ ($$n = 445$$/622) of the participants were willing to get the HZ vaccine if advised by their physician. The bivariate analysis revealed that being male (COR 2.16, $95\%$ CI 1.28–3.65, $$p \leq 0.004$$), having a history of varicella vaccine (COR 4.55, $95\%$ CI 1.05–19.72, $$p \leq 0.043$$), knowing someone infected with HZ (COR 0.56, $95\%$ CI 0.32–0.96, $$p \leq 0.034$$), having had an HZ infection (COR 0.24, $95\%$ CI 0.10–0.72, $$p \leq 0.011$$), and knowing about the HZ vaccine (COR 0.58, $95\%$ CI 0.34–0.97, $$p \leq 0.037$$) were significantly associated with vaccine acceptance. In the multivariable analysis, the variables that remained statistically significant predictors were being male (AOR 2.37, $95\%$ CI 1.18–4.79, $$p \leq 0.016$$) and a history of varicella vaccine uptake (AOR 4.50, $95\%$ CI 1.02–19.86, $$p \leq 0.047$$) (Table 3). ## 4. Discussion To the best of our knowledge, this is the first study conducted in the Kingdom of Saudi Arabia to investigate the predictors of accepting a herpes zoster vaccination among patients with diabetes using an objective instrument. Our results demonstrate that one-quarter of the participants had the intention to receive the HZ vaccine in the Qassim region of Saudi Arabia. Although this rate is low, it is still higher than the rate of $4.5\%$ in Riyadh and $18\%$ in the whole Kingdom among patients with a history of HZ [4,21]. Our findings are consistent with the coverage rate in Greece, which was reported as $26.3\%$ for the HZ vaccine among individuals with diabetes aged 60 years and older [22]. A wide range of variations have been noted in HZ vaccination coverage in different countries. A coverage rate of $24\%$ was found in the USA among adults aged 60 years or older [23], and coverage rates of $9\%$, $11.9\%$, and $16.57\%$ have been reported in South Korea, Texas, and China, respectively [24,25,26]. The uptake rate in the Netherlands has been reported as $58.1\%$ [27]. One explanation for the low willingness to accept the HZ vaccine among our respondents, despite its free availability at PHCs in Saudi Arabia, could be the patients’ low awareness about HZ infection, the HZ vaccine, indications for patients with diabetes, and the vaccine’s free-of-cost availability. Approximately half of our participants knew about HZ, and an equal proportion was acquainted with its vaccine (HZV), while less than one-quarter thought that the vaccine was effective. These results are similar to a study conducted in the United Arab Emirates, which showed $60\%$ awareness of HZ and $15\%$ awareness of the vaccine [28]. Similarly, in Hong Kong, $47.1\%$ of the study’s respondents were aware of HZV [19]. In a South Korean study and systemic review of 17 countries, $85.7\%$ and $67.1\%$ of the participants were aware of HZ, respectively, and $43.6\%$ of the participants knew about the HZ vaccine [29,30]. Most people appear to have relatively limited knowledge about the HZ vaccine’s free-of-cost availability at all PHCs in the Kingdom, which was announced relatively recently in Saudi Arabia [18]. Additionally, unawareness of the indications of the specific vaccine among the older population with T2D is common, despite the fact that two-thirds of HZ cases are found at ages >50 years [31]. Our data revealed that low awareness was not the sole reason for low willingness to accept the HZV among patients with diabetes, but it was certainly a prevalent reason, as was evident in the participant responses that indicated feeling that HZV was not needed, self-perceived immunity from HZ, beliefs that HZ was not a serious or severe infection, and low prioritization of the HZ vaccination. These findings are in line with the results of the US 2007 National Immunization Survey-Adult (NIS-Adult), which reported similar findings [32]. Our data also indicated that doubts about HZV effectivity and concerns about side effects contributed a great deal to unwillingness toward the vaccination, despite the strong evidence provided by a number of studies about the safety, effectiveness, and good tolerability profile of HZV among both the <60 and >60 age groups [33,34,35]. This study also found that a certain proportion of participants were generally not in favor of vaccination, which was consistent with an Italian study conducted with the same objectives in 2016 [20]. One possible explanation for this could be people’s mistrust of vaccinations, which could lead to concerns about their possible side effects and effectiveness. We found that about $74\%$ of those who did not intend to vaccinate against HZ were ready to receive it if advised to do so by their physicians. In other words, the rate of willingness to vaccinate against HZ was found to improve dramatically from one-quarter to half of the study participants if doing so was recommended by their physicians. This finding is consistent with previous studies [28,29]. Our data supported findings from other studies and added insights by highlighting a number of significant factors that had a positive association with HZ vaccination willingness, including male gender, an awareness that immunocompromised individuals are at a higher risk of contracting HZ, and the belief that the vaccine was effective. Moreover, we found that willingness to receive the HZ vaccine on a physician’s advice was significantly associated with the male gender and a history of varicella vaccine uptake. Our findings regarding the positive influence of physicians’ recommendations on willingness to receive the HZV are similar to studies conducted in Italy, the United Arab Emirates, South Korea, the United Kingdom, and the USA. This information is reassuring because it is plausible that physicians can play an effective role in increasing HZ vaccine coverage [20,24,28,29,36,37,38]. In contrast to a study conducted in China, we found that male participants were more likely to accept the HZV than female participants [26]. Our study provides information regarding the strong association of HZV willingness among patients with diabetes who are aware that immunocompromised individuals are at a higher risk of HZ infection and believe that the vaccine is effective. These findings correspond to those of previous studies [20,27]. This could be rationalized by our participants being more motivated toward prevention and immunization which is driven by self-perceived susceptibility and effectiveness of the vaccine as stated by the health belief model that people become more receptive to optional vaccines if they believe the following: a health condition is serious, they are susceptible to it, the vaccine would benefit them by mitigating their risk of contracting a disease, or the benefits of the vaccine are greater than its potential risks [39,40]. Despite the fact that all people aged ≥50 years should receive the HZ vaccine, regardless of their previous vaccination for varicella, the patients with diabetes who had received the varicella vaccine in the past were hesitant to receive the HZ vaccine, and they were willing to receive it only with their physician’s advice [41]. This finding can be attributed to the misconception of our participants that they were immune to shingles if they had had the varicella vaccine in the past. However, it was positive that they were largely willing to receive the HZV if their physicians recommended it to them. The study had some limitations, including the self-reported nature of our data. Even though the accuracy of most of the responses can be ensured, it is difficult to verify participants’ responses regarding vaccine uptake or knowing someone with HZ. Additionally, we cannot rule out recall bias. A causal relationship cannot be established due to the cross-sectional study design. Further, this study has not covered some variables such as diabetes drugs, metabolic control, history of obesity, micro- or macro-vascular complications, and sleep disturbances leading to immune dysfunction, which may influence the decisions of patients with diabetes towards vaccination [42,43]. ## 5. Conclusions Willingness to receive the HZ vaccination among patients with diabetes is far below the optimum level in the Qassim region of Saudi Arabia, but it can be significantly increased if patients are advised by their physicians. We believe that our findings related to low willingness can contribute to the improvement in the HZ vaccination rate among people with DM in the KSA, but there is a need for a large-scale study to generalize the findings to all regions of the Kingdom. This will help policy-makers monitor and plan adequately at a national level. 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--- title: Adiponectin Enhances Fatty Acid Signaling in Human Taste Cells by Increasing Surface Expression of CD36 authors: - Fangjun Lin - Yan Liu - Trina Rudeski-Rohr - Naima Dahir - Ashley Calder - Timothy A. Gilbertson journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10059208 doi: 10.3390/ijms24065801 license: CC BY 4.0 --- # Adiponectin Enhances Fatty Acid Signaling in Human Taste Cells by Increasing Surface Expression of CD36 ## Abstract Adiponectin, a key metabolic hormone, is secreted into the circulation by fat cells where it enhances insulin sensitivity and stimulates glucose and fatty acid metabolism. Adiponectin receptors are highly expressed in the taste system; however, their effects and mechanisms of action in the modulation of gustatory function remain unclear. We utilized an immortalized human fungiform taste cell line (HuFF) to investigate the effect of AdipoRon, an adiponectin receptor agonist, on fatty acid-induced calcium responses. We showed that the fat taste receptors (CD36 and GPR120) and taste signaling molecules (Gα-gust, PLCβ2, and TRPM5) were expressed in HuFF cells. Calcium imaging studies showed that linoleic acid induced a dose-dependent calcium response in HuFF cells, and it was significantly reduced by the antagonists of CD36, GPR120, PLCβ2, and TRPM5. AdipoRon administration enhanced HuFF cell responses to fatty acids but not to a mixture of sweet, bitter, and umami tastants. This enhancement was inhibited by an irreversible CD36 antagonist and by an AMPK inhibitor but was not affected by a GPR120 antagonist. AdipoRon increased the phosphorylation of AMPK and the translocation of CD36 to the cell surface, which was eliminated by blocking AMPK. These results indicate that AdipoRon acts to increase cell surface CD36 in HuFF cells to selectively enhance their responses to fatty acids. This, in turn, is consistent with the ability of adiponectin receptor activity to alter taste cues associated with dietary fat intake. ## 1. Introduction Obesity remains a major public health challenge worldwide and is labeled as a national epidemic in the US with up to $40\%$ of adults having excessive body fat accumulation and body mass index ≥30 kg/m2 in 2020 [1]. Obesity decreases life expectancy and quality of life; it also increases a person’s risk to develop a number of preventable health conditions that contribute to chronic illness and death, including heart disease, stroke, hypertension, and type 2 diabetes mellitus. Lifestyle, particularly eating behavior, plays an important role in the development of obesity, and excess calorie consumption can result in disproportional energy intake and expenditure. Indeed, dietary fat intake is implicated in the development of obesity specifically by a positive correlation between fat intake and weight [2]. Foods with high-fat content are both calorically dense and palatable [3]. As the gustatory system plays a crucial role in promoting nutrient intake, a preference for the taste of fats is due, in part, to dietary fatty acids activating unique lipid-sensing chemoreceptors found on taste bud cells that are embedded in the tongue. However, increased consumption of dietary fat reduces our ability to detect fatty acids, therefore requiring larger amounts of fat in our diet to achieve pleasurable taste. Moreover, taste is weakened in obese, especially the taste for fat [4,5]. Adiponectin is secreted into the circulation by adipocytes in response to calorie restriction. A decline in circulating adiponectin levels is observed in obesity and has been suggested to play an important role in the pathogenesis of several obesity-related conditions including heart disease and type 2 diabetes mellitus [6,7]. Adiponectin exerts its pleiotropic functions by interaction with three key receptors including AdipoR1, AdipoR2, and T-cadherin [8,9]. These receptors have attracted great interest as potential therapeutic targets for multiple conditions including obesity, cardiovascular disease, and diabetes. AdipoRon, an orally active adiponectin receptor agonist, binds with high affinity to the adiponectin receptors AdipoR1 and AdipoR2, which acts via 5’ adenosine monophosphate-activated protein kinase (AMPK) and peroxisome proliferator-activated receptor alpha (PPARα) pathways, respectively [10]. Importantly, AdipoRon acts in a manner consistent with the activity of adiponectin in a number of physiological systems [11,12,13,14,15,16]. Recently, Crosson and colleagues found that adiponectin receptors are highly expressed in mice taste buds [17]. Therefore, it has been hypothesized that through its receptors, adiponectin has the potential to markedly affect peripheral taste signaling. Indeed, there are accumulating data demonstrating that circulating peptides/hormones act on their receptors, which are present in the peripheral gustatory system, to regulate taste function and preference. Additionally, behavioral studies showed that salivary gland-specific adiponectin rescue in adiponectin knockout mice significantly increases behavioral taste responses to intralipid (fat stimulus) [17]. However, the molecular and cellular mechanisms that underlie adiponectin’s role in fatty acid detection in the gustatory system remain unclear. The transduction of polyunsaturated fatty acids (PUFAs) in the mammalian taste system has been extensively explored. Briefly, PUFAs such as linoleic acid, the most extensively studied fatty acid, activate GPR120 and CD36 to initiate a signaling pathway that involves, at least in part, the activation of G proteins and the production of the ß2 isoform of phospholipase C (PLC), the liberation of IP3 and diacylglycerol (DAG), the rise in intracellular free Ca2+ and activation of transient receptor potential channel subtypes M5 and M4 (TRPM5, TRPM4), culminating in eventual neurotransmitter release (for review, see [18,19,20]). Given the overlap between the transduction elements of fatty acid signaling and the expression of adiponectin receptors in the taste system, it is plausible that adiponectin might regulate the expression or activity of the molecular components of the fatty acid transduction pathway in the gustatory system. One potential target of adiponectin signaling is the fatty acid translocase cluster of differentiation 36 (CD36) which is known to facilitate fatty acid uptake in multiple tissue types and also serves as a detector for dietary fatty acids in the taste system. Interestingly, in rodents adiponectin upregulates CD36 expression [21] and increases the translocation of CD36 to the plasma membrane via the activation of AMPK [22]. Following adiponectin’s demonstrated regulatory effects on the uptake of long-chain fatty acids [23,24,25], we hypothesized that in the taste receptor cells of the peripheral gustatory system, adiponectin may similarly modulate fatty acid responsiveness. Taste transduction pathways are well characterized in rodent models, but studies in humans have been comparatively rare. Recent attempts to develop human taste cell lines hold promise for expanding these mechanistic studies to further understand taste transduction pathways in human cells. In the present study, we utilized a recently developed immortalized human fungiform taste cell line (HuFF) to identify adiponectin’s role, if any, in fatty acid-induced cellular responses. Specifically, we investigated the potential effect of the adiponectin receptor agonist, AdipoRon, on fatty acid-induced calcium responses in HuFF cells. The aims of this study were [1] to validate if the HuFF cells are functionally comparable to primary rodent taste cells and can serve as a model for studying fatty acid taste signaling, [2] to determine whether AdipoRon selectively enhances the cellular responses to fatty acids in HuFF cells, and [3] if so, to examine whether AdipoRon enhances fatty acids responses via AMPK activation and subsequent CD36 translocation to the plasma membrane. ## 2.1. HuFF Cells Express Adiponectin Receptors and Fat Taste Receptors Previous studies have shown that fat taste receptors (CD36 and GPR120) are expressed in human fungiform taste bud cells [26] and that CD36 is co-expressed with GPR120, PLCβ2, and Gα-gust [27]. Here, we used quantitative RT-PCR and immunofluorescence assay to determine the expression of adiponectin receptors (AdipoR1, AdipoR2, and T-cadherin), fat taste receptors (CD36 and GPR120), and downstream taste signaling molecules (PLCβ, Gα-gust, and TRPM5). As a result, mRNAs for AdipoR1, AdipoR2, CDH13, CD36, GPR120, PLCβ2, and GNAT3 were expressed in HuFF cells (Figure 1). Immunofluorescence microscopy also confirms that AdipoR1, CD36, GPR120, PLCβ2, Gα-gust, and TRPM5 expression was visible in HuFF cells (Figure 2) and that AdipoR1 is co-expressed with CD36 (Figure 2A) and GPR120 (Figure 2B). ## 2.2. HuFF Cells Differentially Respond to Bitter, Sweet, Umami, and Fatty Acids To determine if the HuFF cells are functionally comparable to primary rodent taste cells, calcium imaging studies were performed to explore the cellular responsiveness to different taste stimuli. As shown in Figure 3A, saccharin (20 mM; “sweet”), denatonium benzoate (DB, 5 mM; “bitter”), linoleic acid (LA, C18:2, 30 µM; “fatty acid”), and capric acid (C10:0, 100 µM; “saturated fatty acid”) elicited reversible calcium responses in HuFF cells, but monosodium glutamate (MSG, 20 mM) did not reliably generate any changes in intracellular calcium in a significant proportion of HuFF cells (only 4 responding cells in a total of 280 cells; $1.4\%$). The overlap in the HuFF cells’ responses to saccharin ($27.8\%$ of cells responding), DB ($18.9\%$), LA ($58.6\%$), and capric acid ($7.5\%$) are presented in Figure S1 ($$n = 280$$ total cells). In rodent taste cells, long-chain fatty acid responses are limited to cis-unsaturated fatty acids [18,28]. To determine the type of fatty acid that could elicit cellular responses in HuFF cells, various cis-PUFAs (docosahexaenoic acid, DHA, C22:6; eicosapentaenoic acid, EPA, C20:5; arachidonic acid, AA, C20:4), monounsaturated fatty acids (MUFAs; nervonic acid, NA, C24:1; erucic acid, EA, C22:1), and one trans-PUFA (linolelaidic acid, LEA, trans-C18:2) were applied during calcium imaging. As shown in Figure 3B, HuFF cells only responded to cis-PUFAs (DHA, 22 in 46 cells; AA, 29 in 46 cells; EPA, 35 in 46 cells), and did not reliably respond to trans-PUFAs (LEA, 1 in 46 cells) or MUFAs (NA, 2 in 46 cells; EA 3 in 46 cells). ## 2.3. HuFF Cells Act as a Model System for Exploring Fatty Acid Signaling To determine if HuFF cells were able to recapitulate the transduction pathway for PUFAs that has been well established in mouse primary taste cells, we performed a series of experiments using ratiometric calcium imaging focusing on response to linoleic acid, the prototypical PUFA stimulus. Similar to responses shown in rodents [29,30], HuFF cells showed a robust rise in intracellular calcium in a dose-dependent manner in response to a series of LA concentrations ranging from 10 to 200 µM (Figure 4A). To compare across cells from different preparations, the area under the curve for each response was determined and normalized relative to the response to 30 µM LA in the same cell. Data from 27–50 cells per point were averaged and fit with a logistic relation to determine a relative EC50 for LA of 64.03 µM (Figure 4A). Generally, there are two receptors, GPR120 and CD36, that have been most commonly implicated in the initial transduction of PUFAs in the taste system as mentioned above. To confirm the involvement of CD36 and GPR120 in the LA-induced signaling pathway in HuFF cells (Figure 4B–D), we conducted calcium imaging using a series of pharmacological agents targeting specific elements in the transduction pathway. As expected, the intracellular calcium responses induced by 30 µM LA were significantly reduced by the irreversible CD36 inhibitor, sulfosuccinimidyl oleate (SSO, 400 µM, 20 min pre-treatment, 41.3 ± $2.8\%$ [SEM] reduction; Figure 4B), and the GPR120 antagonist AH-7614 (10 µM, 20 min pre-treatment, 56.4 ± $3.7\%$ reduction; Figure 4B), consistent with the contribution from these two receptors. The contribution of other pathway elements (cf. [ 20]) was also verified using this same approach. Treatment with triphenylphosphine oxide (TPPO, a reversible and selective blocker for the TRPM5 channel, 200 µM, 78.4 ± $2.7\%$ reduction; Figure 4B,C), and U73122 (PLC inhibitor, 6 µM, 66.7 ± $5.4\%$ reduction; Figure 4B,D) inhibited LA-induced intracellular calcium responses in HuFF cells. In addition, LA-induced calcium responses were inhibited by a store-operated calcium entry (SOCE) blocker BTP2 (10 µM, 2 h pre-treatment, 88.4 ± $2.5\%$ reduction; Figure 4B). All inhibitions by pharmacological agents were significant ($p \leq 0.001$) as assessed by independent one-sample t-tests (Figure 4B). ## 2.4. AdipoRon Selectively Enhances Calcium Responses to Fatty Acids in HuFF Cells AdipoRon is a selective agonist for both AdipoR1 and AdipoR2 with dissociation constants (Kd) of 1.8 μM and 3.1 μM, respectively [10]. AdipoRon was demonstrated to increase intracellular calcium levels in high-glucose-treated human glomerular endothelial cells and murine podocytes [31]. In contrast to those cells, however, AdipoRon (5 µM) alone did not reliably generate any measurable changes in intracellular calcium levels in HuFF cells (Figure 5A). While LA (30 µM) alone reliably induced calcium responses of 104.39 ± 8.54 nM ($$n = 436$$), the addition of AdipoRon increased the magnitude of the LA-induced calcium responses in a concentration-dependent manner (0.1 µM: 89.81 ± 7.95, $$n = 109$$; 0.5 µM: 123.11 ± 23.27, $$n = 110$$; 1 µM: 135.47 ± 17.63, $$n = 97$$; 5 µM: 225.30 ± 29.00, $$n = 159$$; and 10 µM: 250.45 ± 29.47, $$n = 121$$, Figure 5B,C). The EC50 for the enhancement effect of AdipoRon on calcium responses to LA was 1.67 µM (Figure 5D), which was close to the previously reported Kd (1.8 μM) of AdipoRon bound to AdipoR1. In marked contrast, calcium responses to a mixture of sweet (20 mM saccharin), bitter (3 mM denatonium benzoate, DB, and 0.1 mM cycloheximide), and umami (5 mM monosodium glutamate, MSG) stimuli were not affected by AdipoRon treatment (t[100] = 0.011, $$p \leq 0.9912$$, unpaired t-test, Figure 5E,F), indicating that AdipoRon selectively enhances calcium responses to fatty acids in HuFF cells. ## 2.5. AdipoRon Acts on CD36 to Increase Fatty Acids-Induced Responses in HuFF Cells Since AdipoRon selectively increased the LA-induced calcium responses in HuFF cells, we next sought to determine which of the fatty acid signaling pathway is involved in AdipoRon-modulated fatty acids responses in HuFF cells. A series of calcium imaging experiments were performed to test whether there are any changes in the enhancement effect of AdipoRon on fatty acid responses of HuFF cells by pharmacologically blocking the activation of fatty acid receptors. The results showed that the CD36 antagonist SSO inhibited (t[169] = 2.149, $$p \leq 0.0331$$, unpaired t-test, Figure 6A,C) and AdipoRon enhanced (t[136] = 2.879, $$p \leq 0.0046$$, unpaired t-test, Figure 6B,C) the LA-induced calcium responses. Blocking CD36 eliminated the ability of AdipoRon to enhance LA-induced calcium responses (t[203] = 1.654, $$p \leq 0.0996$$, unpaired t-test, Figure 6A,C). In contrast, AH-7614 (GPR120 antagonist) inhibited LA-induced calcium responses (t[247] = 2.366, $$p \leq 0.0187$$, unpaired t-test, Figure 6D–F), but did not affect the ability of AdipoRon to increase LA-induced responses (t[238] = 4.487, $p \leq 0.0001$, unpaired t-test, Figure 6D,F). In addition, AdipoRon had no effect on GW9508 (an agonist for GPR120 [and GPR40])-induced calcium responses in HuFF cells (t[90] = 0.2709, $$p \leq 0.7871$$, unpaired t-test, Figure 6F). Similar to its effects on LA responses, inhibition of CD36 inhibited cellular responses of HuFF cells to EPA (t[125] = 3.388, $$p \leq 0.0009$$, unpaired t-test, Figure S2A–C) and DHA (t[144] = 2.017, $$p \leq 0.0456$$, unpaired t-test, Figure S2D–F). Further, AdipoRon increased the calcium responses of HuFF cells to EPA (t[146] = 2.305, $$p \leq 0.0226$$, unpaired t-test, Figure S2B,C) and DHA (t[168] = 2.296, $$p \leq 0.0229$$, unpaired t-test, Figure S2E,F), and the effect of AdipoRon on these fatty acid-induced calcium responses was dependent upon the activity of CD36 since inhibition of CD36 with SSO blocked any enhancement (EPA, t[104] = 0.0195, $$p \leq 0.9845$$; DHA, t[120] = 1.760, $$p \leq 0.0810$$, unpaired t-test, Figure S2A,C,D,F). Interestingly, however, another PUFA, arachidonic acid (AA) did not show a similar result. AA induced a rise in intracellular calcium that was not affected by the application of SSO (t[96] = 0.3238, $$p \leq 0.7468$$, unpaired t-test, Figure S3A–C) and AH-7614 (t[110] = 0.08296, $$p \leq 0.9340$$, unpaired t-test, Figure S3D,E). In addition, AdipoRon did not enhance the calcium responses of HuFF cells to AA (t[100] = 0.2175, $$p \leq 0.8282$$, unpaired t-test, Figure S3B,C). LA has been reported to induce the production of AA that will open the Orai$\frac{1}{3}$ channels, which are responsible for the SOCE in mice taste bud cells [32]. Consistent with this finding, the SOCE blocker BTP2 inhibited AA-induced calcium responses in HuFF cells (t[169] = 7.786, $p \leq 0.$ 0001, unpaired t-test, Figure S3D,E). Taken together, these results indicate that CD36, but not the GPR120, may be responsible for the ability of AdipoRon to enhance fatty acid-induced responses in HuFF cells. ## 2.6. AdipoRon’s Effect on LA-Induced Responses Is Mediated by Activation of AMPK It has been shown in numerous studies that phosphorylation of AMP-activated protein kinase (AMPK) mediates many of the effects of AdipoRon (adiponectin) at the cellular level in a variety of cell types [33,34,35]. To test for the contribution of AMPK in the HuFF cell PUFA responses, we performed an ELISA assay for phosphorylated AMPKα using a commercially available kit. Our results show a significant (1.3-fold) increase in the phosphorylation state of AMPKα (Thr172) under the stimulation of AdipoRon for 30 min, which was inhibited by an AMPK inhibitor, dorsomorphin (compound C; F[2,6] = 24.38, $$p \leq 0.0013$$, Figure 7A). To link the activation of AMPK to the enhancement role of AdipoRon on fatty acid-induced calcium responses, we examined the effect of compound C on AdipoRon’s effect on LA-induced calcium responses in HuFF cells. A one-way ANOVA showed that the ability of AdipoRon to enhance LA-induced calcium responses in HuFF cells was significantly inhibited by the treatment of compound C (F[2,189] = 14.28, $p \leq 0.0001$, Figure 7B,C). ## 2.7. AdipoRon-Stimulated CD36 Translocation Is Dependent on AMPK Activation Previous studies demonstrated that adiponectin increases CD36 translocation to the plasma membrane in cardiomyocytes and upregulates CD36 expression in L6 myotubes via activation of AMPK [21,22]. Therefore, to test if AdipoRon similarly affects CD36 translocation in HuFF cells via AMPK, we monitored the subcellular distribution of CD36 in AdipoRon-treated HuFF cells using an immunofluorescence assay (Figure 8A) and a CD36 translocation assay (Figure 8B). After a 1 h serum starvation, little CD36 could be detected on the cell surface (and was likely localized to the perinuclear region) in the control group (Figure 8A). By contrast, with stimulation by AdipoRon (5 μM for 5 or 30 min), CD36 was recruited to the cell surface (Figure 8A), which resulted in an approximately 1.4-fold increase in cell surface CD36 (5 min: F[3,16] = 40.14, $p \leq 0.0001$; 30 min: F[3,16] = 8.411, $$p \leq 0.0014$$, Figure 8B). The change in CD36 expression caused by AdipoRon was not due significantly to an increase in gene expression. Using real-time PCR assays on mRNA isolated from HuFF cells treated with AdipoRon in the presence and absence of compound C, we measured the relative expression of CD36, AdipoR1, AdipoR2, and CDH13 (T-cadherin). AdipoRon application did not change the relative expression of AdipoR1, AdipoR2, CDH13, and CD36 in HuFF cells (Figure 8C). Therefore, AdipoRon apparently increases the surface expression of CD36 via AMPK activation but does not alter CD36 transcription in HuFF cells. ## 3. Discussion The continuing high incidence of obesity is a major public health challenge worldwide. Obesity increases the health risks associated with many chronic morbidities, such as diabetes, cardiovascular disease, metabolic disease, and cancer [36,37]. Lifestyle choices, particularly eating behavior coupled with a sedentary lifestyle, are considered major factors in weight gain [38,39]. Taste is a key driver in food selection and may enhance preference for foods high in fat and sugar [40], which are both palatable and energy dense. However, high dietary fat reduces hedonic responses and sensitivity to fat taste [41], which may increase the drive for fat consumption, leading to chronic positive energy balance, and resulting in obesity. Moreover, obese subjects present a diminished ability to detect fatty acids with a much stronger preference for fat-rich foods [42,43] indicative of an inverse relationship between peripheral fat sensitivity and overall intake, which further increases the risk of adiposity. By contrast, fat restriction in obese people increases fat taste sensitivity [5], and individuals with high-fat sensitivity present lower consumption and less preference towards foods that are high in fat [4,44]. Thus, targeting the taste of fat might be a potential therapeutic approach for the management of fat intake and body weight. Dietary fats are critical for our life and health. For example, essential fatty acids (which cannot be produced by metabolic processes in humans) must be obtained from food. Therefore, the ability to detect these essential fatty acids in food sources is necessary for survival. However, the oral detection of dietary fat was initially thought to be dependent on its texture rather than its taste. Our group provided some of the first evidence for the ability of fatty acids to activate our taste cells and has worked on exploring underlying mechanisms our body uses to recognize and respond to dietary fat [28]. Since then, accumulating evidence from humans and other animals provided support that fat may be classified as the sixth basic taste [45,46,47]. Indeed, long-chain fatty acids have been reported to elicit a unique taste sensation in humans [45]. Both CD36 and GPR120 are thought to be the functional fat taste receptors in taste buds cells [48,49]. The downstream transduction signaling pathways are well characterized in rodent models. In brief, long-chain fatty acids bind to CD36 to induce the activation of Src-PTKs [50] or bind to GPR120 causing the release of G proteins which, in turn, stimulate PLC and generate inositol 1,4,5-phosphate (IP3), resulting in an elevation of intracellular calcium and the opening of TRPM5 channels that are responsible for taste cell depolarization [20]. Human taste bud cells express fat taste receptors (CD36 and GPR120) and downstream signaling elements (Gα-gust and PLCβ), and in response to fatty acids show an increase in the intracellular calcium level [27]. However, in contrast to rodents, much less is known about fat taste transduction pathways in human taste cells. In this study, we show the expression of fat taste signaling elements and calcium responses in an immortalized human fungiform taste cell line (HuFF). Dose-dependent calcium responses to LA in HuFF cells were similar to the range of effective concentrations seen in rodent taste cells, and LA-induced calcium responses were significantly reduced by the administration of CD36, GPR120, PLCβ, and TRPM5 inhibitors. These data suggest that HuFF cells are functionally comparable to primary rodent taste cells and may serve as an appropriate model for studying fatty acid taste signaling in humans. While we have focused on their role in fatty acid signaling HuFF cells could serve as a model to study sweet and bitter signal transduction as well. Approximately $30\%$ and $20\%$ of HuFF cells responded to saccharin and DB, respectively. Although umami taste shares a similar downstream signal transduction pathway with the fat, sweet, and bitter taste, HuFF cells do not appear to be a good model for investigating umami taste signaling. It was beyond the scope of this research to fully characterize HuFF cells and a caveat is that we did not investigate a range of concentrations for other tastants in the present study. Recently, a number of studies have shown that many peptide hormones and their receptors, such as Peptide YY, glucagon-like peptide-1 (GLP-1), leptin, cannabinoid, ghrelin, estrogen, and adiponectin that are classically considered to regulate food intake, also are present in taste bud cells and play a direct role in the modulation of fat taste responsiveness. Peptide YY gene knockout (PYY−/−) mice displayed a reduction in behavioral responsiveness to fat emulsions and it was effectively rescued by the reconstitution of salivary PYY [51]. Intraperitoneal injection of Exendin-4 (GLP-1 receptor agonist) reduced the lick responses and trial initiation of rats to both intralipid and sucrose during brief-access tests [52]. Leptin inhibited LA-induced intracellular calcium responses in taste bud cells and decreased the gustatory preference for LA in mice, whereas gene silencing of leptin or its receptor via the application of siRNAs onto the mice’s tongues upregulated the LA preference [53]. Cannabinoid 1 receptor gene knockout (CB1R−/−) mice showed a lower preference for fatty solutions compared to the WT controls, while LA-induced calcium responses were decreased in taste cells by pharmacologically (rimonabant, a specific CB1R inverse agonist) or genetically (CB1R−/− mice) blocking the function of CB1R [54]. Ghrelin knockout (ghrelin−/−) and ghrelin O-acyltransferase knockout (GOAT−/−) mice demonstrated reduced expression levels of fat taste receptors (CD36 and GPR120) in taste bud cells and exhibited decreased fat taste sensitivity, compared to WT mice [55]. We also found a reduction of fat responsiveness in female ghrelin receptor knockout mice following 6 weeks of a $60\%$ high-fat diet, but not in males, compared to WT controls [29]. Fatty acid-induced taste bud cell activation and fat taste sensitivity in mice were reported to be increased by estrogen, which was considered a major contributor for the sex differences in fat taste [30]. It has been found that adiponectin receptors are highly expressed in taste buds and salivary gland-specific adiponectin rescue in adiponectin knock out mice significantly increases behavioral taste responses to intralipid [17]. Interestingly, a similar positively correlated link between adiponectin level and fat taste sensitivity is also found in different genders. The adiponectin levels in both saliva and plasma are higher in females than in males coupled with a greater taste sensitivity to fatty acids [30,56,57]. Taken together, these findings provided evidence for the hormonal involvement in fat taste perception; however, there is still little understanding of the molecular and cellular mechanisms underlying hormonal peptide regulation in the taste system. In this study, we show the target of fat taste modulation by the adiponectin receptor agonist, AdipoRon, in HuFF cells. Our results showed that AdipoRon selectively enhances fatty acids-induced calcium responses via modulation the cell translocation of CD36, and this enhancement role of AdipoRon on fat taste is dependent upon the activation of 5’ adenosine monophosphate-activated protein kinase (AMPK). Adiponectin is a hormone primarily secreted from adipose tissue, with the monomeric protein post-translationally modified into different molecular weight multimers: trimer (low), hexamer (middle), and 12–18 monomers (high) [58]. There are three proteins (AdipoR1, AdipoR2, and T-cadherin) that have been identified as adiponectin receptors that mediated the pleiotropic actions of adiponectin [8,9]. AdipoR1 has a high affinity for globular adiponectin, while AdipoR2 displays an intermediate affinity for both globular and full-length adiponectin, whereas T-cadherin shows a high affinity for the middle and high molecular weight multimers [8,9]. AdipoR1 and AdipoR2 are structurally related to each other and ubiquitously expressed in many tissues, while T-cadherin is structurally different from AdipoRs and there is comparatively little known about its signaling pathway. Activation of AdipoR1/APPL1 by adiponectin increases CD36 translocation and fatty acid uptake via the phosphorylation of AMPK in rat cardiomyocytes [22]. Our qRT-PCR results were consistent with the high expression of adiponectin receptors in taste cells [59], and the double-labeled immunostaining showed that AdipoR1 was co-expressed with fat taste receptors (CD36 and GPR120). These results provide insights into the role of adiponectin signaling in modulating fat taste. To test this possibility, we examined the potential effects of the adiponectin receptor agonist AdipoRon on intracellular calcium responses to LA as well as a taste mixture of sweet, bitter, and umami in HuFF cells. Unlike the high-glucose-treated human glomerular endothelial cells and murine podocytes [31], AdipoRon (5 µM) alone did not alter the intracellular calcium levels in HuFF cells. We found that AdipoRon enhances the LA-induced calcium responses in a dose-dependent manner with an EC50 value of 1.67 µM, which was close to that previously reported Kds of AdipoRon bound to AdipoR1 (1.8 μM) and AdipoR2 (3.1 μM) [10]. RNA interference or CRISPR gene knockout techniques are needed in future studies to address which of the adiponectin receptors mediates the role in fat taste. A previous study showed that no significant difference in behavioral taste responses has been found between adiponectin KO and WT mice, but salivary gland-specific adiponectin rescue in adiponectin KO mice significantly increased the brief-access taste responses to intralipid stimulus, but not for sucrose and QHCl [17]. Consistent with this behavioral study, our calcium imaging data showed that AdipoRon enhances the cellular responses of HuFF cells to LA, but not for the sweet, bitter, and umami mixture. Next, we provided evidence that the CD36 pathway, independent of GPR120, is functionally responsible for the enhancement role of AdipoRon on fatty acids responses. Pharmacologically blocking the function of CD36 by SSO eliminated the enhancement effect of AdipoRon on fatty acid-induced responses (LA, EPA, and DHA). Similar results in HL-1 cell studies have also shown that SSO completely prevented insulin-stimulated fatty acid uptake [60]. In contrast, blocking the function of GPR120 by AH-7614, AdipoRon was still able to enhance the LA-induced calcium responses. Moreover, GPR120 agonist GW9508-induced calcium response was not affected by the application of AdipoRon. AA acts on different types of ion channels, such as TRP channels, SOCE, and non-SOCE channels, and plays a variety of functions in living cells. In mice taste bud cells, LA has been shown to induce the production of AA that will open the Orai$\frac{1}{3}$ channels, which are responsible for the SOCE [32]. Interestingly, we also found that AdipoRon did not enhance the calcium responses induced by AA in HuFF cells. Further studies showed that BTP2, but not SSO and AH-7614, inhibited AA-induced calcium responses in HuFF cells, suggesting that AA may act directly on SOCE channels to induce calcium influx independent of either CD36 or GPR120. These data suggest that AdipoRon would modify the fat taste responses of HuFF cells via the mediation of the CD36 pathway in these cells. In the present study, we revealed the importance of AMPK in AdipoRon’s effect on fat taste. AdipoRon increased the phosphorylation of AMPKα (Thr172) and it was inhibited by AMPK inhibitor compound C. Similarly, the enhancement role of AdipoRon on LA-induced calcium responses of HuFF cells was significantly inhibited by the treatment of compound C. Studies in intestinal epithelial cells have suggested that AMPK is critical for CD36 translocation and long-chain fatty acid uptake [61]. CD36 dynamically traffics between the plasma membrane and subcellular compartments. Several studies have revealed that muscle contractions [62,63] and hormones, such as adiponectin [22] and insulin [64], could be the important factors that initiate the translocation of CD36 from intracellular compartments to cell surface membranes. Therefore, we hypothesize that AdipoRon selectively enhances the cellular response to fatty acids through the AMPK pathway, which increases the translocation of CD36 to the plasma membrane of HuFF cells. However, little is known about the time course dynamics of the CD36 translocation under stimulation. The enhancement of the LA-induced calcium responses by AdipoRon was rapid and could be seen within a few minutes of administration. The results from our present study suggested that the membrane recruitment of CD36 induced by AdipoRon is rapid and may occur in a few minutes, which could possibly explain why it selectively enhances taste responses to fatty acids. In support of these findings, it has been reported that 15 and 30 min application of adiponectin increased CD36 translocation from intracellular to the cell surface [22], and the translocation of CD36 was observed even within 1 min of muscle contractions [63]. Although the mechanisms initiating the translocation of CD36 are unclear, previous studies have demonstrated that CD36 translocation is stimulated by adiponectin through the activation of AMPK [22], by insulin via the PI3K/AKT signaling [65], and by muscle contractions in both AMPK-dependent and AMPK-independent manners [62,63]. Our results in this study indicated that AMPK is essential in the regulation of CD36 translocation induced by AdipoRon. Together, our results suggest that AdipoRon via the activation of AMPK promotes the cell surface translocation of CD36 and therefore enhances cellular responses to fatty acids. Future studies are needed to understand in greater detail adiponectin’s effects on an animal’s fat taste behavior. ## 4.1. Cell Culture The commercially available human fungiform taste cell line (HuFF; Applied Biological Materials, Richmond, BC, Canada; Catalog #: T0029) was immortalized via serial passaging and transformation with recombinant lentiviruses carrying simian virus 40 Large T antigen. HuFF cells were cultured in Prigrow V medium supplemented with $10\%$ fetal bovine serum and $1\%$ penicillin/streptomycin solution under a humidified atmosphere containing $5\%$ carbon dioxide at 37 °C. The cells were seeded on glass coverslips 4–24 h before calcium imaging and 24–48 h before immunofluorescence assay. HuFF cells cultured in 96-well plates and 6-well plates were used for the CD36 translocation assay and ELISA experiments, respectively. ## 4.2. Solutions Standard Tyrode’s solution contained 140 mM NaCl, 5 mM KCl, 1 mM CaCl2, 1 mM MgCl2, 10 mM HEPES, 10 mM glucose, and 10 mM Na pyruvate; adjusting the pH to 7.40 with NaOH; 300–320 mOsm. Stock solutions of polyunsaturated fatty acids (Sigma-Aldrich, St. Louis, MO, USA or Cayman Chemical, Ann Arbor, MI, USA) were made in $100\%$ ethanol and stored under nitrogen at −20 °C. All working solutions of the polyunsaturated fatty acids were made from stock solutions immediately before use. Taste mixture solution contained 115 mM NaCl, 5 mM KCl, 1 mM CaCl2, 1 mM MgCl2, 10 mM HEPES, 10 mM glucose, 10 mM Na pyruvate, 20 mM Na saccharin, 5 mM monosodium glutamate (MSG), 3 mM denatonium benzoate (DB), and 0.1 mM cycloheximide; adjusting the pH to 7.40 with NaOH at an osmolarity of 300–320 mOsm. Stock solutions of AH-7614 (Sigma-Aldrich), sulfosuccinimidyl oleate (SSO; Cayman Chemical), N-[4-[3,5-Bis(trifluoromethyl)-1H-pyrazol-1-yl]phenyl]-4-methyl-1,2,3-thiadiazole-5-carboxamide (BTP2; EMD Millipore), triphenylphosphine oxide (TPPO; Sigma-Aldrich), U73122 (Cayman Chemical), AdipoRon (MedChem Express, Monmouth Junction, NJ, USA), GW9508 (MedChem Express), and dorsomorphin (compound C; ApexBio, Houston, TX, USA) were made in DMSO and diluted the day of the experiment to a designated concentration with Tyrode’s. ## 4.3. Quantitative RT-PCR Analysis HuFF cells cultured in surface-treated sterile tissue culture flasks (12.5 cm2, Fisher Scientific) were used for studies involving the measurement of gene expression of adiponectin receptors and fat taste signaling elements. To test the effect of AdipoRon on the expression of CD36 and adiponectin receptors (cf. Figure 8C), HuFF cells were incubated in 6-well plates with DMSO (control), 1 µM AdipoRon, 5 µM AdipoRon, and 5 µM AdipoRon plus 10 µM compound C for 20–24 h. Total RNA extracted from HuFF cells according to the RNAzol RT protocol (Molecular Research Center, Cincinnati, OH, USA), followed by the RNA clean and concentrator-25 kits (Zymo Research, Irvine, CA, USA) included an in-column DNase treatment. RNA integrity and purity were evaluated by using agarose gel electrophoresis and Nanodrop 8000 Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA), respectively. Then, RNA samples were converted to cDNA by qScript cDNA Synthesis Kit (Quanta Biosciences, Beverly, MA, USA). Commercially available TaqMan assays (FAM-labeled), obtained from Fisher scientific: AdipoR1 (Hs00360422_m1), AdipoR2 (Hs00226105_m1), CDH13 (Hs01004531_m1), CD36 (Hs00354519_m1), GPR120 (Hs00699184_m1), GNAT3 (Hs01385398_m1), PLCβ2 (Hs01080541_m1), TRPM5 (Hs00175822_m1), were used to detect the gene expression of adiponectin receptors and fat taste signaling elements. The GAPDH qPCR probe assay (Hs. PT.39a.22214836, HEX-labeled, Integrated DNA Technologies, Coralville, IA, USA) was used as an internal control. Final reaction cocktail (20 µL) contained the following: 10 µL TaqMan master mix (2×), 1 µL Taqman assays (20×), 1 µL GAPDH probe (20×), 1 µL template, and 7 µL nuclease-free water. Quantitative real-time PCR analyses were carried out following TaqMan protocols according to the manufacturer’s instructions for the QuantStudio 3 Real-Time PCR System (Thermo Fisher Scientific). Four independent experiments, each consisting of three replicates, were conducted. Following the RT-PCR reaction, gene expression was quantified by measuring the cycle threshold (CT). Each target gene was compared with GAPDH and relative expression was normalized to the expression level for CD36, which served as the calibrator. The standard ΔΔCT method was used to generate measures of relative gene expression for all targets of interest [30]. The mean relative expression ± SEM of each target gene was then calculated using the 2−ΔΔCT analytical method [66]. ## 4.4. Immunofluorescence Assay HuFF cells, seeded on 15 mm glass coverslips in 12-well plates without any treatment for 1–2 days, were used for immunostaining experiments to determine the expression of AdipoR1 and fat taste signaling components. To monitor the subcellular distribution of CD36 under AdipoRon treatment, HuFF cells need to be washed and incubated in a serum-free medium for at least 1 h prior to the treatment. Then, serum-free medium with DMSO (control), 1 µM AdipoRon, 5 µM AdipoRon, and 5 µM AdipoRon plus 10 µM compound C were applied to the HuFF cells for 5 and 30 min. The cells were fixed with cold $100\%$ methanol for 10 min at 4 °C and washed three times (5 min for each) with cold PBS. Then, samples were placed in a blocking buffer ($1\%$ bovine serum albumin, $0.1\%$ Tween-20 in PBS) for 1 h at room temperature and incubated with primary antibodies overnight at 4 °C: rabbit polyclonal anti-AdipoR1 (1:50; Invitrogen, Waltham, MA, USA), mouse monoclonal anti-CD36 (1:50; Abcam, Boston, MA, USA), rabbit polyclonal anti-CD36 (1:50; Santa Cruz Biotechnology, Dallas, TX, USA), mouse monoclonal anti-GPR120 (1:50; Santa Cruz Biotechnology), mouse monoclonal anti-PLCβ2 (1:50; Santa Cruz Biotechnology), rabbit polyclonal anti-Gα-gust (1:50; Santa Cruz Biotechnology), rabbit polyclonal anti-TRPM5 (1:100; Alomone Labs). After washing three times with PBS, the coverslips were incubated with goat anti-rabbit Alexa Fluor 594 (1:500, Invitrogen) and/or goat anti-mouse AlexaFluor488 (1:500, Invitrogen) for 1.5 h at room temperature. Subsequently, the cells were washed twice with PBS and counterstained with DAPI (1 µg/mL in PBS; Invitrogen) for 5 min at room temperature. Finally, coverslips were mounted to glass slides with Fluoromount G (Southern Biotech, Birmingham, AL, USA) and sealed using nail polish. The immunofluorescence images of the labeled HuFF cells were obtained using an all-in-one fluorescence microscope (BZX800, Keyence, Itasca, IL, USA). ## 4.5. Calcium Imaging HuFF cells were seeded on coverslips for at least 4 h, then loaded with 4 µM of Fura-2AM (Invitrogen) in Tyrode’s with $0.05\%$ pluronic acid (Invitrogen) for 1 h in the dark. The coverslips were placed onto the perfusion chamber (RC-25F, Warner Instruments, Holliston, MA, USA). Tastant solutions were perfused extracellularly at a flow rate of 4 mL/min, followed by 1 min of $0.1\%$ fatty acid-free BSA solution, and then regular Tyrode’s (about 2 min) until the calcium signal returned to near baseline level. Cells were illuminated with Lambda DG-5 (Sutter Instruments, Novato, CA, USA) or CoolLED pE-340fura (CoolLED, Andover, UK) illumination system, and imaging was performed using an acA720 camera (Basler, Ahrensburg, Germany) coupled to a microscope (Olympus CKX53). The cell fluorescence at excitation wavelengths of 340 and 380 nm was recorded at a rate of 20 pairs per minute and converted to calcium concentration according to a standard curve generated from the calcium calibration kit (Invitrogen) by InCyt Im2™ imaging software (Version 6.00, Cincinnati, OH, USA). ## 4.6. AMPKα [pT172] ELISA HuFF cells grown in 6-well plates were serum-starved for at least 1 h and then treated with DMSO (control), 1 µM AdipoRon, 5 µM AdipoRon, and 5 µM AdipoRon plus 10 µM compound C for 30 min. The cells were washed with cold PBS and collected by gentle scraping from the plate. Next, the cell pellet was lysed in RIPA lysis buffer (Thermo Fisher Scientific) with inhibitors (Thermo Fisher Scientific) for 30 min on ice and vortexed at 10 min intervals. The supernatant was collected after a 10 min centrifuge at 13,000 rpm. A bicinchoninic acid (BCA) assay was used for the total protein quantification following the manufacturer’s instructions of Pierce™ BCA protein assay kit (Thermo Fisher Scientific). A sample of 10 µg of total protein from each sample was used to determine the phosphorylation of AMPK, following the simple step-by-step protocols of the AMPKα [pT172] ELISA kit (Invitrogen). ## 4.7. CD36 Translocation Assay HuFF cells were grown in 96-well plates until about $90\%$ confluent and serum-starved for at least 1 h prior to treatment with DMSO (control), 1 µM AdipoRon, 5 µM AdipoRon, and 5 µM AdipoRon plus 10 µM compound C for 5 and 30 min. The cells were fixed with $3\%$ paraformaldehyde for 10 min and blocked with blocking buffer ($5\%$ goat serum, $1\%$ bovine serum albumin, $0.05\%$ Tween-20 in PBS) for 1 h. Following incubation with rabbit polyclonal anti-CD36 antibody for 2 h, the cells were washed three times with blocking buffer and incubated with secondary HRP-conjugated goat anti-rabbit antibody for 1 h. Next, they were washed another three times with PBS and incubated with 100 µL of 3,3′,5,5′-tetramethylbenzidine solution (TMB, pre-warmed to room temperature, TCI Chemicals, Portland, OR, USA) for 30 min. To terminate the reaction, 100 µL of 1 N hydrochloric acid was added and the absorbance of each well was measured at 450 nm using a Synergy 4 microplate reader (BioTek Instruments, Winooski, VT, USA). The entire assay was performed at room temperature. ## 4.8. Data Analysis Calcium imaging data analyses were based on the amplitude of the intracellular calcium concentration and analyzed in Origin 9.6 (Version 9.6.0.172, OriginLab, Northampton, MA, USA). Statistical analysis was performed using either a one-sample t-test, unpaired Student’s t-test, or a one-way ANOVA with Tukey test for post hoc multiple comparisons in GraphPad Prism 9 (Version 9.5.0 [730], GraphPad Software, Boston, MA, USA) as appropriate and described in each experiment above. The level of significance was set at α = 0.05 for all experiments. All data are presented as mean ± SEM. ## 5. Conclusions The plasticity of the peripheral taste system is currently of great interest, and the taste responses originating in the oral cavity appear to be influenced by dietary experience and hormonal and nutritional status. Our present study in a human taste cell line indicates a potential effect of adiponectin signaling in the modulation of fat taste. We demonstrate that AdipoRon increases the translocation of CD36 to the plasma membrane of HuFF cells via the activation of AMPK and therefore selectively enhances their responses to fatty acids. Fat sensing is essential for the detection of essential fatty acids and the hormonal regulation of fat taste sensitivity may contribute to the regulation of fat intake in healthy subjects. Obese subjects display a diminished ability to detect fat concomitant with a much stronger preference for fat-rich foods [42,43]. 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--- title: 'The Presence of Ultra-Traces of Persistent Organic Pollutants (POPs) and Heavy Metals in Some Areas of Molise: The Importance of a “Blank” in Public Health Studies' authors: - Ivan Notardonato - Francesca Fantasma - Pamela Monaco - Cristina Di Fiore - Gabriella Saviano - Carmen Giancola - Pasquale Avino - Vincenzo De Felice journal: Toxics year: 2023 pmcid: PMC10059250 doi: 10.3390/toxics11030250 license: CC BY 4.0 --- # The Presence of Ultra-Traces of Persistent Organic Pollutants (POPs) and Heavy Metals in Some Areas of Molise: The Importance of a “Blank” in Public Health Studies ## Abstract The emission of chemicals into the environment has increased in a not negligible way as a result of the phenomenon of globalization and industrialization, potentially also affecting areas always considered as “uncontaminated”. In this paper, five “uncontaminated” areas were analyzed in terms of the presence of polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs), comparing them with an “environmental blank”. Chemical analyses were carried out using standardized protocols. The ‘environmental blank’ results revealed the presence of Cu (<64.9 μg g−1), Ni (<37.2 μg g−1), and Zn (<52.6 μg g−1) as HMs and fluorene (<17.0 ng g−1) and phenanthrene (<11.5 ng g−1) as PAHs. However, regarding the results of the pollution status of the areas under study, fluorene (#S1, 0.34 ng g−1; #S2, 4.3 ng g−1; #S3, 5.1 ng g−1; #S4, 3.4 ng g−1; #S5, 0.7 ng g−1) and phenanthrene (#S1, 0. 24 ng g−1; #S2, 3.1 ng g−1; #S3, 3.2 ng g−1; #S4, 3.3 ng g−1; #S5, 0.5 ng g−1) were found in all areas, while the other PAHs investigated were detected at a concentration averaging less than 3.3 ng g−1. HMs were found in all of the investigated areas. In particular, Cd was detected in all areas with an average concentration of less than 0.036 μg g−1, while Pb was absent in area #S5, but present in the other areas with an average concentration of less than 0.018 μg g−1. ## 1. Introduction The environment has been significantly affected by human activities, which can be considered as the main source of pollutant emissions. Particularly, among the different human activities, the construction of the urban environment and industrial elements has contributed to the release of high concentrations of heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) into the environment [1,2]. The reduction of so-called “green areas” for “grey areas” has also occurred in Italy, particularly in the last few decades. According to the ISTAT data from 2016, in 111 provincial capitals, urban greenery accounts for only $2.7\%$ of the entire territory [3]. A multitude of chemicals are released into the environment, seriously affecting ecological equilibrium and human health [4]. The scientific literature has reported that, on a daily basis, significant release of persistent organic pollutants (POPs) and heavy metals occurs in several areas of Italy. For example, concentrations exceeding the legal limit values of mercury as well as the high concentration of PAHs have been detected in Augusta-Melilli-Priolo (Sicily, South of Italy) [5]. Significant concentrations of PAHs were also detected in Monopoli and Torre a Mare (Puglia, Southern Italy) [6]. In addition, an article by Imperato and collaborators revealed a pollution phenomenon in Naples (Campania, Southern Italy), where a high accumulation of MM in soils was found [7]. Recent scientific evidence has, in fact, shown a significant accumulation of HMs in both urban and rural areas in Naples. In rural areas, the main contribution is agricultural activities. The experimental data, in fact, underline the not negligible impact of the activities of fertilization with phosphates that have released not negligible concentrations of Cd [8]. On the other hand, urban and industrial areas have been affected by increased levels of vehicle traffic and industrial activities. Experimental data suggest that levels of POPs are higher near heavy traffic roads, next to the railway station, bus stations, and commercial port, underlining the strong impact of human activities on pollution phenomena [9]. Scientific based-research evidence proved that in the last 100 years, heavy metals and PAHs concentrations have, in fact, increased in all biosphere environmental media as a direct response of human activities [10]. Furthermore, the co-contamination of HMs and PAHs has been widely demonstrated and their co-existence is a matter of a great concern due to their synergistic cytotoxic effects [11,12]. Effects on humans due to an acute and/or chronic exposure to these environmental chemicals have been investigated. Heavy metals and PAHs have been, in fact, associated with a wide range of adverse effects such as illness (i.e., cancer, cardiovascular, nervous, kidney, and bone disease) and death [13]. Reactive oxygen species (ROS) levels can significantly increase as a response to heavy metals and PAH exposure. ROS can thus lead to oxidative stress and oxidative DNA damage, which basically consist of the formation of lesions to DNA filaments [14]. However, the effects of exposure to heavy metals and PAH may be different, potentially depending on the health status of the individual [15]. Therefore, it is possible to assume that an exposure may induce different effects, more or less severe, depending on the health status of the individual. A class of population that should be particularly monitored is that defined as “vulnerable”, as it is at risk of poor physical, physiological, and/or social health. There is a lack of research on the effects of heavy metals and PAHs on vulnerable populations and data about their exposure are very limited [16]. Vulnerable people, in fact, can also be seriously affected by low levels of pollutants [17]. The so-called “poorly contaminated” areas are generally characterized by low-levels of contamination; as it is not possible to exclude a priori the impact of low concentrations of contaminants in the environment on specific classes of population (i.e., vulnerable population such as elderly, children, low-income families, newcomers, and ethnic minorities) [17,18], these areas should be carefully monitored. The purpose of this work is to examine the levels of contamination by POPs such as polycyclic aromatic hydrocarbons (benzo[a]pyrene, bap; benzo[a]anthracene, Baa; benzo[k]fluoranthene, BkFA; chrysene, CHR; Indeno[1,2,3-cd]pyrene, IP; pyrene, PY; benzo[b]fluoranthanthene, BbFA; benzo[g,h,i]perylene, BghiP; dibenzo[a,h]anthracene, DhA) and inorganic pollutants such as heavy metals (i.e., Cd, Pb, Cu, Zn, and Ni) in different areas of the Molise region characterized by pollution sources of different degrees. In addition, a large area of the region considered as uncontaminated has been taken as a reference to assess the background levels of contamination. The study was conducted through a basic regional approach. Indeed, several studies have been carried out on the contamination phenomena in Italy, but most of them have been carried out on a local or small scale, while a basic regional approach is still rare [19]. The Molise region is characterized by low levels of contamination, but the monitoring of contamination levels should be a necessity to protect vulnerable people. As the levels of contamination in the Molise area is low, to provide precise data about the pollutant levels and to distinguish between natural and anthropogenic sources, an “environmental blank” was determined. In this work, the trace levels of contaminants in five areas of Molise were determined. To achieve this purpose, a “non-contaminated” area of Molise was chosen as an “environmental blank”. Analysis for the determination of contamination levels of the blank was performed on a soil sample as it is a major reservoir of heavy metals [11,12]. Instead, the determination of the contamination levels of areas under investigation was performed using honeybees, which have been used as bioindicators of the levels of pollution of the investigated areas. The reason why bees have been used as indicators of pollution status is based on the appropriateness of these living organisms to capture and trap pollutants in their bodies, as demonstrated in the scientific literature [20,21,22]. Finally, based on the scientific information, an assessment about the potential effects on vulnerable populations was carried out. ## 2.1. Study Sites and Sampling for Environmental Blank Analysis Soil samples for the environmental blank analysis were collected from six different sites of a rural area of the Molise region (Central of Italy), which are indicated in black on the map (Figure 1). Figure 1 also shows the five areas investigated to study the levels of contamination in the Molise region (in orange). The six locations surveyed had a total extension of about 0.960 km2. Two representative sites were identified for each of the six locations. Systematic sampling was carried out at each site, drawing two squares (5 × 5 m2). The herbaceous cover of each square was carefully removed. For each square, five soil aliquots were taken, then sieved on the spot with a sieve with large meshes (1 cm) and mixed. In this way, for each locality, 20 soil samples were taken, reduced to two representative samples for each locality. The total number of samples in the whole sample area was 12. Therefore, the soil samples were transported to the chemistry laboratory of the University of Molise for the chemical analysis. ## 2.2. Study Sites and Sampling for HMs and PAHs Analysis For the determination of the pollution levels in the Molise region, five areas were taken into account with different levels and sources of contamination. Area 1 is an urban center of Termoli, where one monitoring station (#S1) was positioned. This area is characterized by a significant intensity of vehicular traffic. Area 2 is an industrial area, where two monitoring stations (#S2–#S3) were positioned, as the number of stations was established according to the extension of the territory to be monitored. The industrial area has food, chemical, and metal industries, which are a significant source of pollutants. Station #S4 was positioned in a rural area. The rural area of Termoli and its surroundings is characterized by intense agricultural activity using agricultural machinery. The area was selected on the basis of the impact that rural activities have on the release of pollutants. Station #S5 was placed at the Lipu Oasis, an area known to be sparingly polluted. However, this area is used for recreational activities (i.e., barbeques) that may have an impact, albeit minimal, on the release of pollutants. Sampling of HMs and PAHs was conducted collecting honeybees. Sampling lasted for about 7 months (March-October), and during it, no chemicals were used to treat the honeybees to not invalidate the results. After collection, the bee samples were stored in the freezer at −20 °C. ## 2.3. Extraction and Determination of HMs from Soil Samples For the extraction of heavy metals (i.e., Cd, Pb, Zn, Ni and Cu), 0.5 ± 0.05 g of soil was processed by means of a digester tube using 3 mL of hydrogen peroxide to remove the organic matter. Soil samples were then mineralized with 9 mL of hydrochloric acid (Baker Instra-Analyzed, Fisher Scientific, Waltham, MA, USA) and 3 mL of nitric acid ($68\%$) for 40 min at 180 °C and then filtered by means of Whatman no. 42 filters (pore size: 2.5 µm). An atomic absorption spectrophotometer (SpectrAA 220 FS, Varian, Santa Clara, CA, USA) was used for the determination of heavy metals. The concentrations of heavy metals in the soil samples were determined by means of calibration curves, and procedural blanks were used to ensure the absence of contamination in the laboratory. Calibration curves were prepared by diluting a multi-Element standard mix of heavy metals in $10\%$ HNO3 (O2Si Smart Solutions, North Charleston, SC, USA). The chemical analyses were carried out in triplicate. ## 2.4. Extraction and Determination of PAHs from Soil Samples To determine the PAHs, the soil samples were extracted by means of a Soxhlet extractor. In brief, 10 ± 0.05 g of soil was mixed with 10 g of sodium sulfate anhydrous and then placed into a cellulose thimble. Thus, the soil samples were dived in an acetone–hexane mixture (1 + 1, v/v) at 140 °C for 60 min. After, the soil samples were washed with the solvent mixture vapors for 60 min. The extraction solvent was then recovered and dried under a gentle flow of nitrogen in a fume hood. Analytes were then recovered with 1.0 mL of n-hexane and an appropriate volume of the experimentally determined internal standard (octacosane, C28H58) was added. Then, 1 μL was injected into the gas chromatograph-mass spectrometer (gas chromatograph, Trace 1310, equipped with a triple quadrupole mass spectrometer, QqQ, 7000D, Agilent Technologies, Santa Clara, CA, USA) for the analysis. Quantification was carried out by means of calibration curves. Calibration curves were prepared by diluting a standard solution of PAHs in methanol/dichloromethane (1 + 1 v/v) (Certified Reference Material, CAPChem Ltd., Belgium). The chemical analyses were carried out in triplicate. ## 2.5. Extraction and Determination of HMs from Honeybee Samples For the analysis of HMs from the honeybee samples, 4 g of each bee sample was placed into a porcelain capsule and then in a muffle at 130 °C. After each hour, the temperature of the muffles was increased up to 380 °C (50 °C every hour). Afterward, the samples were left to cool and placed into a flacon (50 mL), and 5 mL of nitric acid ($5\%$) was used to recover the samples. Finally, the samples were transferred into the ED36S Digiblock digester (LabTech, Boston, MA, USA) for 30 minutes at 120 °C. After cooling, Milli-Q ultrapure water was added to each sample up to a volume of 25 mL and analyzed by means of an ICP-OES (5110 Agilent Technologies, Santa Clara, CA, USA). Wavelengths used for each analyte for ICP-OES analysis were as follows: Zn 213.857 nm, Cd 228.802 nm, Pb 405.781 nm, Ni 361.939, and Cu 324.754 nm. Calibration curves were prepared by diluting a multi-element standard mix of heavy metals in $10\%$ HNO3 (O2Si Smart Solutions, USA). The chemical analyses were carried out in triplicate. ## 2.6. Extraction and Determination of PAHs from Honeybee Samples Briefly, 5 g of shredded honeybee samples were mixed with anhydrous sodium sulfate and diatomaceous earth and transferred into the cells for the accelerated solvent extraction technique (ASE). Cellulose filters were used to pack the cells and then they were placed into the ASE system. A mixture of dichloromethane/acetone (1 + 1, v/v) was used as the extraction solvent with the following extraction parameters: temperature was set to 150 °C, pressure to 2000 psi kept constant through a nitrogen flow for each extraction cycle. At the end of the extraction cycle, each organic extract was collected in a vial and then transferred into a glass flask for evaporation, using filter paper with hygroscopic sodium sulfate and Florisil in order to remove any possible traces of water in the extract. The solvent was then dried using a rotavapor R-200 BÜCHI at a temperature up to 40 °C and the extract was dissolved in cyclohexane (500 μL). Afterward, solid phase extraction (SPE) was used to clean up the samples. Prior to use, SPE cartridges were rinsed with ethyl acetate (6 mL) and cyclohexane (6 mL). The sample was placed into the SPE system for cleaning up and the elution was obtained by using cyclohexane (6 mL). The eluate was thus collected in a vial and concentrated up to 500 μL under a gentle nitrogen flow. A total of 1 μL of the solution was used for the analysis, which was conducted using a GC (Trace 1310) equipped with a triple quadrupole mass spectrometer detector (GC/QqQ 7000D, Agilent Technologies). ## 3.1. Soil Samples Results: Environmental Blank The results on the HMs and PAHs obtained from the analysis of soil samples collected from the six localities of the Molise region are reported in Table 1 and Table 2. As shown in Table 1, only three of the five heavy metals investigated were found in the study areas. Particularly, Cu, Ni, and Zn were detected. Cu was present with an average concentration of 43.6 μg g−1, Ni in an average concentration of 20.1 μg g−1, and Zn in an average concentration of 40.6 μg g−1. Cd and Pb were below the LOD values. Concerning the PAHs, of the 18 PAHs investigated, only fluorene and phenanthrene were revealed. Particularly, phenanthrene was greater than the LOD value only in Verrino and Guado Cannavina, whereas fluorene was detected in all areas under study, except for Monteforte. Particularly, the highest value was detected in Guardata (17.0 ng g−1), whereas the lowest one was in Macchia Bassa and Verrino (2.5 ng g−1). The analysis of the “environmental blank” showed that both PAHs and HMs detected were under the legal limits established by Italian environmental law (Legislative Decree No. $\frac{152}{2006}$), which regulates the threshold values of some contaminants in the soil [23]. The LOD values for each parameter studied are reported in Table 3. ## 3.2. Honeybee Sample Results Honeybee samples were used to analyze the levels of HMs in the five areas of the Molise region under study. The results obtained are shown in Figure 2. The HM levels detected by means of honeybees were lower than those found in the areas considered as the “environmental blank” for Zn (#S1 0.013; #S2 0.011; #S3 0.012; #S4 0.019; #S5 0.014 μg g−1), Cu (#S1 0.018; #S2 0.060; #S3 0.176; #S4 0.079; #S5 0.032 μg g−1), and Ni (#S1 0.039; #S2 0.049; #S3 0.039; #S4 0.044; #S5 0.028 μg g−1). Pb and Cd were not detected in the areas of the “environmental blank”, but they were in the areas under study. Particularly, Cd was revealed in the following concentrations: 0.014 μg g−1 for #S1, 0.0036 μg g−1 for #S2, 0.0035 μg g−1 for #S3, 0.0044 μg g−1 for #S4, and 0.019 μg g−1 for #S5. Likewise, Pb was not detected in the environmental blank area, but it was present in the following concentrations in the areas under study: 0.013 μg g−1 for #S1, 0.011μg g−1 for #S3, 0.01 μg g−1 for #S4 and 0.018 μg g−1 for #S5, and below the LOD value in #S2. The PAH levels detected by means of honeybee were lower than those found in the areas considered as the “environmental blank” for Fle (#S1 0.34; #S2 4.3; #S3 5.1; #S4 3.4; #S5 0.7 ng g−1) and Phe (#S1 0.24; #S2 3.1; #S3 3.3; #S4 3.2; #S5 0.5 ng g−1) (Figure 3). All of the other PAHs investigated were not detected in the areas considered as the environmental blank, but they were present in some areas under investigation. Particularly, BaP, BaA, BkFA, CHR, PY, Fle, and Phe were detected in #S2 in concentrations of 0.5, 0.6, 0.5, 0.6, 1.8, 4.3, and 3.1 ng g−1, respectively. PY, Fle, and Phe were revealed in area #S1, in concentrations of 0.8, 0.34, and 0.24 ng g−1, respectively. Area #S3 was characterized by the presence of BkFA, CHR, PY, BbFA, DBahA, Fle, and Phe in the following concentrations: 0.8, 3.3, 1.0, 2.6, 0.5, 5.1, and 3.2 ng g−1, respectively. Area #S4 was contaminated by PY, Fle, and Phe in the following concentrations: 1.0, 3.4, and 3.3 ng g−1, respectively. In area #S5, CHR, PY, Fle, and Phe were detected in the following concentrations: 0.6, 0.9, 0.7, and 0.5 ng g−1. ## 4.1. Environmental Contamination Levels In this paper, an analysis of the levels of contamination in some areas of Molise was carried out. Basically, the main purpose of the work was to assess whether, even in areas known to be “poorly polluted”, they are affected by the presence in traces or ultra-traces of PAHs and MHs that can have adverse effects on human health. According to the scientific literature, the assessment and determination of low levels of contamination is necessary to understand, and understand in depth, the metabolic effect that may occur in humans after exposure to low concentrations, but persistent over time, to pollutants [11]. As a matter of fact, the evaluation of the effects on humans after exposure to pollutants can be divided in two steps: the first step consists of a screening process, which aims to collect and analyze data on site-specific contamination levels. The second step focuses on characterizing the effects of contaminants, usually based on the literature, trying to employ conservative assumptions [24]. First, an environmental blank was taken into account to clearly understand the background contamination value of the areas under investigation. Hence, the first step of the screening process was carried out by determining the environmental blank and the contamination levels of the five areas under study. The analysis of the environmental blank showed that only fluorene and phenanthrene were detected in low concentrations. Based on the scientific knowledge, fluorene and phenanthrene are considered as the two prevalent PAHs as they have been detected in various areas [25]. However, the contamination by fluorene and phenanthrene can be due to road surface renovation works carried out a few days before the start of the sampling. Furthermore, the environmental blank area was located next to rural areas. Hence, the agricultural vehicles released PAHs into the environment as the combustion of fossil fuels is one of the main sources [25]. In addition, their hydrophobic nature and their preference to be adsorbed by solid matrices makes them capable of accumulating in the soil [26]. Therefore, it is plausible to hypothesize that their presence in the area is not due to the presence of a fixed source, but to spot events. Areas under study presented low levels of contamination. PAHs were detected in all five areas investigated. The lowest levels were found in areas #S1 and #S5, whereas an increase in the PAH concentration values were observed in areas #S2, #S3, and #S4. However, considering the contamination levels of other rural areas in Italy, values found in the Molise region were much lower. For example, rural areas of the Campania region showed a PAH concentration between 276 and 11,353 ng g−1; the Sicily countryside also showed PAH concentrations within 52.45–74.25 ng g−1. Another study conducted in soils from Naples identified as the most present PAHs were fluorene, pyrene, and chrysene [27]. This is consistent with the results obtained in the present study. Italian urban areas are characterized by high levels of PAHs. More specifically, Rome showed a PAH concentration of 755 ng g−1, which was close to the values detected in Naples of 715 ng g−1 [19]. The levels of HMs detected in the environmental blank area were all below the legal limits established by the Italian Environmental law for a public or private “green” area (e.g., Ni, 120 μg g−1, Cu, 120 μg g−1 and Zn 150 μg g−1, Cd, 2 μg g−1, Pb, 100 μg g−1). HMs were detected in the five areas of Molise. More specifically, Cd and Pb were detected in all areas under study, except for area #S2, where Pb was not revealed. Among the HMs, Cu was present in the highest concentrations. Fertilizers used in the sampled areas can determine an increase in the Cu concentration [20]. The levels of pollutants tend to vary according to the anthropic characteristics of the area considered. A work by Perna and co-authors, in fact, showed a statistically significant difference of some heavy metals between a rural and an urban area. Differences in the toxic element content between areas are due to environmental factors with an important contribution of the anthropic impact typology [28]. In our study, the anthropic impact was mainly found in the presence of Cu. Basically, all areas analyzed in this study are surrounded by farmland and the use of Cu as a fertilizer is quite widespread. As for the Pb, Zn, and Cd found in the #S1 area, an important source of contamination is the train station. Scientific literature reveals that friction processes between wheelsets and rails during rail transport cause railways to release heavy metals including Zn, Cd, and Pb into the environment [29,30]. The industrial area (#S2–#S3) is characterized by industries of different types. However, of greater importance, by size, is the metallurgical industry. The emissions of Pb, Cd, and Ni are due to the metallurgical industry, active for years in the area examined [31,32]. Unexpectedly, area #S5, considered as a little contaminated area, showed the presence of Pb, Cd, Ni, Zn, and Cu, with a higher average concentration than area #S1. Despite the low industrialization of the #S5 area, human activities (i.e., railway passage, agricultural activities) [33] are sufficient to release heavy metals. However, it is worth noting that it is currently not possible to define whether the PAH and HM values found in the five areas under study (i.e., #S1, #S2, #S3, #S4, and #S5) were below the values considered as tolerable by law. Both the Italian and European legislation, in fact, do not provide limits of pollutants for sampling carried out through the use of living organisms (e.g., bee) [34]. For this reason, if it is possible to define that the values of the “environmental white” are below the legal limit established by the Environmental Italian Law (Legislative Decree No. $\frac{152}{2006}$), given that the determination was carried out on soil samples, and no formally recognized legal limits are available for bees. ## 4.2. Exposure to Environmental Chemical of the Vulnerable Populations Exposure to environmental chemicals is a topic of concern, as different toxic effects can be associated with them. Endocrine related cancers, obesity, type 2 diabetes, immune related disorders, decrease in fertility, and adverse pregnancy outcomes are some examples of endocrine related disorders resulting from exposure to chemicals [35]. Environmental chemicals affect vulnerable populations, particularly with regard to pregnant women, children, toddlers, and individuals with low socioeconomic status [36]. Among them, fetus health status is often considered as an important segment of the vulnerable population [35]. Research by Karttunen et al. [ 2010] showed that maternal exposure to BaP led to exposure of the fetus to it and/or its metabolites. Indeed, the use of the human placenta perfusion allowed us to understand that a concentration from 0.1 to 1 μM of BaP is able to reach the fetal compartment. Furthermore, the concentrations of BaP used simulated the exposure of the pregnant woman and fetus to low levels of contaminants, underlying the impact on a vulnerable segment of populations to low levels of pollutants [37]. PAHs and HMs also showed a negative effect on vulnerable populations; furthermore, it has been reported that vulnerable populations tend to be more exposed to environmental chemicals. For example, another important segment of vulnerable populations are low-income families as they are more exposed to contaminants that come from industrial areas, but environmental policies do not seem to protect these populations [18]. For example, due to different behavioral habits (i.e., hand-finger sucking), children are more exposed to heavy metals [38]. ## 5. Conclusions The present work aimed to identify the trace and ultra-trace levels of PAH and HM in five areas of the Molise region, comparing them with the concentrations of the same present in a notoriously “non-polluted” area and considered as an “environmental blank”. In the first place, the identification of an “environmental blank” is essential to correctly define the pollution levels of the area. The sampling of the area identified as “blank” was carried out on soil samples, both to be able to define the pollution status in relation to the reference legislation, and because the soil is the main sink for pollutants. The five areas studied instead showed the presence of PAHs and HMs in traces, due to anthropic agricultural and industrial activities. Although the level of pollution is low, the continuous presence of pollutants over time could, in the long run, be harmful to vulnerable individuals. 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--- title: Gastrodin and Gastrodigenin Improve Energy Metabolism Disorders and Mitochondrial Dysfunction to Antagonize Vascular Dementia authors: - Sha Wu - Rong Huang - Ruiqin Zhang - Chuang Xiao - Lueli Wang - Min Luo - Na Song - Jie Zhang - Fang Yang - Xuan Liu - Weimin Yang journal: Molecules year: 2023 pmcid: PMC10059574 doi: 10.3390/molecules28062598 license: CC BY 4.0 --- # Gastrodin and Gastrodigenin Improve Energy Metabolism Disorders and Mitochondrial Dysfunction to Antagonize Vascular Dementia ## Abstract Vascular dementia (VD) is the second most common dementia syndrome worldwide, and effective treatments are lacking. Gastrodia elata Blume (GEB) has been used in traditional Chinese herbal medicine for centuries to treat cognitive impairment, ischemic stroke, epilepsy, and dizziness. Gastrodin (p-hydroxymethylphenyl-b-D-glucopyranoside, Gas) and Gastrodigenin (p-hydroxybenzyl alcohol, HBA) are the main bioactive components of GEB. This study explored the effects of Gas and HBA on cognitive dysfunction in VD and their possible molecular mechanisms. The VD model was established by bilateral common carotid artery ligation (2-vessel occlusion, 2-VO) combined with an intraperitoneal injection of sodium nitroprusside solution. One week after modeling, Gas (25 and 50 mg/kg, i.g.) and HBA (25 and 50 mg/kg, i.g.) were administered orally for four weeks, and the efficacy was evaluated. A Morris water maze test and passive avoidance test were used to observe their cognitive function, and H&E staining and Nissl staining were used to observe the neuronal morphological changes; the expressions of Aβ1-42 and p-tau396 were detected by immunohistochemistry, and the changes in energy metabolism in the brain tissue of VD rats were analyzed by targeted quantitative metabolomics. Finally, a Hippocampus XF analyzer measured mitochondrial respiration in H2O2-treated HT-22 cells. Our study showed that Gas and HBA attenuated learning memory dysfunction and neuronal damage and reduced the accumulation of Aβ1-42, P-Tau396, and P-Tau217 proteins in the brain tissue. Furthermore, Gas and HBA improved energy metabolism disorders in rats, involving metabolic pathways such as glycolysis, tricarboxylic acid cycle, and the pentose phosphate pathway, and reducing oxidative damage-induced cellular mitochondrial dysfunction. The above results indicated that Gas and HBA may exert neuroprotective effects on VD by regulating energy metabolism and mitochondrial function. ## 1. Introduction Vascular dementia (VD) is a syndrome of severe cognitive impairment caused by vascular risk factors, the incidence of which increases with age [1]. Risk factors include atherosclerosis, thrombosis, or other vascular lesions [2]. In addition, VD pathology is usually accompanied by cerebral microinfarction, vascular damage, and neuronal atrophy, except for Alzheimer’s disease (AD)-like lesions [3]. Current studies on the pathogenesis of VD include neuronal loss [4], energy metabolism [5], mitochondrial dysfunction [6], glutamate neurotoxicity [7], and toxic substance accumulation [8]. Among these, energy metabolism and mitochondrial dysfunction have raised widespread concern because the brain, as the most active organ of energy metabolism, requires a continuous supply of energy from ATP. When VD occurs, cerebral ischemia and hypoxia can produce various toxic substances that impair mitochondrial homeostasis and energy production, and the brain’s high demand for energy can lead to the further development of dementia [9]. Normal mitochondrial homeostasis plays a vital role in stabilizing energy metabolism in the brain [10], although commonly used dementia drugs can show cognitive benefits in some patients with VD. However, few patients achieve the desired therapeutic outcomes [11]. The rhizome of Gastrodia elata Blume (GEB) is a Chinese herbal medicine that has the effects of regulating the circulatory system, sedation, anti-epilepsy, anti-convulsion, anti-depression, anti-inflammation, anti-oxidation, improving memory, and anti-aging [12]. Gastrodin (p-hydroxymethylphenyl-b-D-glucopyranoside, Gas) and Gastrodigenin (p-hydroxybenzyl alcohol, HBA) are active components of the rhizome of Gastrodia elata and are of interest for their various pharmacological activities in the central nervous system. Previous studies have reported that VD rats can cause cognitive impairment and VD-like pathogenesis characterized by Aβ and Tau deposition in the hippocampus [13,14]. Gas improves cognitive deficits in VD rats by reducing toxic substance accumulation (Aβ and Tau proteins) [15] and by reducing excessive autophagy and apoptosis of neuronal cells [16]. After entering the central nervous system, Gas is metabolized to HBA [17]. Previously, HBA treatment was reported to prevent hypomnesis [18] and significantly inhibit oxidative stress and excitotoxicity to suppress neuronal death [19,20]. Despite solid evidence of their beneficial effects against nervous system diseases, studies of Gas and HBA on energy metabolism and mitochondrial function in VD brain tissue are limited. This study aimed to investigate the pharmacological effects of Gas and HBA on VD and the molecular mechanisms. The VD model was established by bilateral common carotid artery occlusion (2-VO), characterized by cerebral ischemia and hypoxia-induced by chronic hypoperfusion and can better simulate human VD caused by atherosclerosis and arterial lumen stenosis. Bilateral common carotid artery ligation (2-vessel occlusion, 2-VO) is characterized by chronic hypoperfusion-induced cerebral ischemia and hypoxia, which better simulates VD in humans due to atherosclerosis and arterial lumen narrowing [21]. In the context of the beneficial intervention of Gas and HBA, the molecular mechanism of the improvement of VD in mitochondria and bioenergetics was proposed. ## 2.1. Gas and HBA Improve Behavioral and Cognitive Alterations in VD Rats We observed apparent local atrophy and necrosis in the brain tissue of VD rats, and the morphology was improved after the intervention of Gas and HBA (Figure 1A). A Morris water maze (MWM) test was used to evaluate the spatial learning memory function after Gas and HBA treatment. The localization navigation test lasted five days, and the escape latency of animals in the Model group was significantly longer than in the Sham group, while the MWM test was significantly relieved by Gas and HBA treatment (Figure 1B). Subsequently, in the probe trial on day 7, a long time was spent in the platform and target quadrant, and more search times were observed in the Gas and HBA group compared to the Model group (Figure 1C–F). No difference was observed in the swimming speed covered among all groups indicating normal motor functions (Figure 1G) and a representative picture of the swimming tracks (Figure 1H). Subsequently, a passive avoidance test was performed to examine the learning and short-term memory abilities of the Model rats. The step-through latency of the rats in the Gas and HBA group was significantly higher than that of the Model group (Figure 1I), while there was no significant difference in the electric time and the number of errors (Figure 1J,K). In conclusion, Gas and HBA can prevent cognitive decline in VD rats. ## 2.2. Gas and HBA Reduce Attenuates 2-VO-Induced Neuronal Damage in the Hippocampus The results of H&E staining in VD rats’ hippocampi showed neuronal disturbances in CA1 and CA3 regions, including loss, degeneration, pyknotic nuclei, and severe cellular edema. Notably, these pathological characteristics were attenuated following Gas and HBA administration, especially in the high dose (50 mg/kg) (Figure 2A,C). We subsequently examined the neuronal integrity by Nissl staining (Figure 2B,D), and the results showed that the VD rats had significantly reduced neuron function with a few Nissl bodies (blue). In contrast, Gas and HBA treatment significantly attenuated the neuronal loss. These data suggest that Gas and HBA treatment mitigates neuronal damage in VD rats. ## 2.3. Gas and HBA Reduce Aβ and Tau Protein Expression in the Brain of VD Rats 2-VO induces Aβ and Tau protein deposition [22,23], and our previous study [15] showed that Gas ameliorates cognitive deficits in VD rats by inhibiting abnormal phosphorylation of Aβ and Tau. Thus, we found that Gas and HBA reduced the protein levels of Aβ1-42 (Figure 3A,C), p-tau396 (Figure 3B,D), and p-tau217 (Figure 3E) in the brain tissue of VD rats. ## 2.4. Gas and HBA Inhibit the Changes in Energy Metabolism in VD Rats The above results show that 2-VO can lead to significant cognitive impairment in rats, while the intervention with Gas and HBA can effectively improve cognitive function. It has been reported that normal energy metabolism is closely related to common cognitive responses, and therefore any defect in energy metabolic processes can lead to a decrease in cognitive function [24]. With the premise that Gas and HBA interventions are effective, we quantified 40 metabolites that target brain energy metabolism (glycolysis, TCA cycle, and pentose phosphate pathway) (Supplementary Materials, Figure S1). In the Sham, Model, HBA-50, and Gas-50 groups, principal component analysis (PCA) characterized a distinct trend of separation of metabolic profiles among the groups, suggesting differences in metabolic patterns (Figure 4A). The heat map was used to visualize the metabolite profiles among the groups (Figure 4B). Orthogonal partial least squares discriminant analysis (OPLS-DA) and variable importance projection (VIP) were used to screen for differential metabolites between groups with screening criteria: VIP > 1 and p ≤ 0.05. There were 16 differential metabolites in the Sham vs. Model group (Figure 4C), of which five were downregulated and 11 were upregulated. Among the metabolites that were abnormally elevated or decreased in the Mode group, 13 metabolite levels were significantly back-regulated after Gas and HBA intervention. In the Gas group, seven were upregulated and six were downregulated, respectively (Figure 4D). In addition, eight metabolite levels were significantly regulated after HBA intervention, four upregulated and four down-regulated (Figure 4E). ## 2.5. Gas and HBA Protect HT-22 Cells from H2O2-Induced Damage As shown, treatment of HT-22 cells with concentrations ranging from 12.5–100 μM Gas and HBA had no significant effect on cell viability (Figure 5A,B). Using 500 μM H2O2 treatment of HT-22 cells for 12 h caused oxidative damage model (Figure 5C,D). Treatment with 12.5–100 μM Gas and HBA significantly improved the H2O2-reduced HT-22 cell viability (Figure 5E,F). ## 2.6. Gas and HBA Attenuated Mitochondrial Dysfunction in HT-22 Cells Induced by H2O2 Previous energy metabolomics analysis suggested changes in brain tissue energy metabolism in VD rats; we therefore determined the mitochondrial respiratory efficacy of H2O2-treated HT-22 cells. Mitochondrial respiratory efficacy was significantly reduced in H2O2-treated cells, whereas Gas and HBA pretreatment partially mitigated the H2O2-induced inhibition of mitochondrial respiration in HT-22 cells (Figure 6A). Gas and HBA pretreatment significantly countered the H2O2-induced reduction in basal respiration (Figure 6B), maximal respiration (Figure 6C), and ATP production (Figure 6D) in HT-22 cells. These results suggest that Gas and HBA partially attenuated H2O2-induced mitochondrial dysfunction in HT-22 cells. Gas and HBA may exert neuroprotective effects by antagonizing VD through ameliorating energy metabolism disorders in VD rats and attenuating oxidative damage-induced cellular mitochondrial dysfunction (Figure 7). ## 3.1. Chemicals and Materials Gas (C13H18O7; molecular weight: 286.28; purity ≥ $98\%$) and HBA (C13H18O7; molecular weight: 286.28; purity ≥ $98\%$) were purchased from Nanjing Zelang Medical Technology Co. Gas, and HBA was dissolved in normal saline (NS). All reagents were of analytical reagent grade. Oligomycin, FCCP (2-[2-[4-(trifluoromethoxy)phenyl]hydrazinylidene]-propanedinitrile), and rotenone were purchased from Sigma-Aldrich (St. Louis, MO, USA). Anti-beta Amyloid (1:200, Proteintech, Wuhan, China) and P-Tau 396 (1:100, Abcam, Shanghai, China). ## 3.2. Animals Adult male Sprague–Dawley (SD) rats weighing 270 ± 10 g were purchased from the Experimental Animal Center of Kunming Medical University. Before the experiment, all animals were allowed adaptive feeding for a week. The rats were kept under a 12 h light/dark cycle at 22–24 °C with free access to food and water. The animals were divided into the following six groups: control group (Sham), 2-VO group (Model), Gas 25 mg/kg group (Gas-25), Gas 50 mg/kg group (Gas-50), HBA 25 mg/kg group (HBA-25), and HBA 50 mg/kg group (HBA-50). All animals were given Gas, HBA, or NS orally on day 7 after surgery, daily for 28 days. The progress of the experiment is shown in Scheme 1. ## 3.3. VD Rats Model Preparation 2-VO prepared the animal model of VD. SD rats were continuously anesthetized with 200 g, 0.2 mL/min of $2\%$ isoflurane gas. After disinfection with $75\%$ ethanol, the skin was cut in the middle of the neck, and the subcutaneous tissue was bluntly separated. The common carotid artery pulsated at the angle between the trapezius muscle and the trachea exactly below the incision and was then ligated and severed with surgical suture. Control rats underwent the same surgical procedure, with the exception that the common carotid artery was exposed but not ligated. Aseptic operation was kept during the operation. After the operation, antibiotics were dropped to prevent infection and then sutured, and sodium nitroprusside injection was injected into the abdominal cavity. The intraoperative temperature was about 37 °C until the rats woke up. ## 3.4. Morris Water Maze Test The Morris water maze (Shanghai Xin Luan MDT infotech LTD., Shanghai, China) test assessed spatial learning and memory and was carried out as previously described. The MWM consists of a large round pool (120 cm in diameter and 50 cm in height) filled with white non-toxic powder. The pool was divided equally into four quadrants, with a 20 cm-diameter round platform hidden in the center of the target quadrant. Before the experiment, the rats were adaptively trained for one day; the positioning navigation experiment then lasted for five days, and the system automatically recorded the track of the rats as they were placed into the water from the edge of the pool. Rats who failed to find the platform within the 90 s would be guided to the platform and allowed to stay there for 10 s. For the probe trial, the platform needs to be removed, and the track of the rat within the 90 s is recorded. ## 3.5. Passive Avoidance Test The cognitive abilities of rats were tested using a SUPERAS shuttle box (Shanghai Xin Luan MDT infotech LTD., Shanghai, China). The test equipment consisted of a light and dark box and an electrical stimulation controller for three days of testing. On the first day, the rats were placed in the light box, and after 30 s, the door between the light and dark boxes was opened. Rats have solid exploratory behaviour and prefer darkness to light. Therefore, the rats would enter the dark box quickly; once they were fully inside, we immediately shut the door and they were given an electric shock. The intensity of the electric shock was the minimum current (0.6 mA for 10 s) that could cause the rat to flinch and vocalize. Having allowed the rats to remain in the dark box for 30 s (to allow the animals to form an association between the box and the electric shock), we placed them back in the cage. On the second day, the rats moved freely in the shuttle box for 5 min, and the electrical stimulator would automatically activate after entering the dark box. Day 3 was a repeat test. ## 3.6. Brain Tissue Staining For each group of six rats, brain tissue was removed and placed in $4\%$ paraformaldehyde for 24 h fixation, dehydrated, and embedded as wax blocks. Sections were cut to a thickness of 4 μm, dewaxed with xylene for 20 min, and hydrated with $100\%$, $95\%$, $80\%$, and $70\%$ for 5 min for subsequent staining. ## 3.6.1. Hematoxylin and Eosin (H&E) Staining After dewaxing and hydration, the sections were stained with hematoxylin for 4 min, Hydrochloric acid alcohol differentiated for 5 s, and washed with running water for 5 min. Next, eosin staining was performed for 3 min, followed by gradient alcohol dehydration, xylene transparency, and sealing with neutral adhesive. All reagents were obtained from Solarbio Biotechnology Co., LTD. ( Beijing, China). Tissue staining was observed under a light microscope (Nikon, Tokyo, Japan). ## 3.6.2. Nissl’s Staining We operated according to the manufacturer’s instructions (Beyotime Biotechnology, Shanghai, China). Sections were dewaxed and hydrated, placed in an oven at 60 °C, stained with toluidine blue stain for 30 min, dehydrated by gradient alcohol, and finally ylene transparency and sealing with neutral adhesive. Photographs were taken using an optical microscope (Nikon, Tokyo, Japan). ## 3.6.3. Immunohistochemical Staining (IHC) Brain tissue sections were dewaxed and placed in a repair kit filled with EDTA (PH 8.0) antigen repair solution for antigen repair in a microwave oven for 8 min at medium heat until boiling and then held for 8 min at a ceasefire and then turned to medium-low heat for 7 min. Sections were incubated sequentially with $3\%$ H2O2 for 25 min and $3\%$BSA for 30 min. The primary antibodies were added dropwise, incubated overnight at 4 °C and incubated with secondary antibodies (HRP-labeled) at room temperature for 50 min. Finally, the cells were developed with DAB (Beyotime Biotechnology, Shanghai, China), re-stained with hematoxylin for 3 min, and photographed using a light microscope (Nikon, Tokyo, Japan). Immunofluorescence-positive areas were assessed using Image J analysis software (National Institutes of Health, Bethesda, MD, USA). ## 3.7. P-Tau217 ELISA Test A measurement of 100 mg of brain tissue was weighed, PBS was added, homogenized thoroughly, and centrifuged at 2000 r/min for 20 min, and the supernatant was collected. An ELISA kit (Jianglai Biologicals, Shanghai, China) was used for the assay according to the manufacturer’s instructions. The absorbance values of the samples were measured at 450 nm by a Scientific Multiskan GO enzyme marker (Thermo, Shanghai, China), and the concentration of each sample was obtained from the standard curve. ## 3.8. Absolute Quantification of Targeted Energy Metabolism We weighed the brain tissue at 100 mg, added pre-cooled extraction solution 1000 μL, sonicated it in an ice bath, centrifuged it at 16,000× g for 30 min at 4 °C, and removed the supernatant. An equal amount of standard internal L-Glutamate_D5 was added to each sample and then vacuum-dried. For mass spectrometry detection, 80 μL of acetonitrile-water solution (1:1, v/v) was added for re-dissolution, and the supernatant was centrifuged at 16,000× g for 30 min at 4 °C, and the supernatant was taken into the sample for LC-MS/MS analysis. UHPLC was used for the separation by ShimadzuNexeraX2LC-30AD. QC samples were inserted in the sample queue for monitoring and evaluating the system’s stability as well as the experimental data’s reliability. Mass spectrometry was analyzed using a QTRAP5500 mass spectrometer in positive/negative ion mode. The MRM mode was used to detect the ion pairs to be measured. Data processing was performed using Multi Quant software to extract the chromatograms’ peak areas and retention times. Metabolite identification was performed using energy metabolite standards corrected for retention time. The standard internal L-Glutamate_D5 normalized the peak areas of metabolite-extracted ions for subsequent analysis. Metabolomics statistical analysis was performed using the MetaboAnalyst (http://www.metaboanalyst.ca/, accessed on 17 April 2022), the online statistical platform. ## 3.9. Cell Culture Mouse hippocampal neuronal cells (HT-22 cells) were purchased from Shanghai QiDa Biotechnology Co., Ltd. (Shanghai, China) and maintained in Dulbecco’s Modified Eagle Medium (DMEM) in the presence of $10\%$ fetal bovine serum and Pen/Strep antibiotics (GIBCO/Life Technologies, Grand Island, NY, USA) in a humidified incubator ($5\%$ CO2 at 37 °C). ## 3.10. MTT Assay for Cell Viability HT-22 cells (1 × 104 cells/well) were cultured in 96-well plates at 37 °C with $5\%$ CO2 and exposed to 500 μM H2O2 for 12 h. Cells treated with a culture medium were used as a control only. After removing the supernatant of each well and washing it twice with PBS, 20 μL of 5 mg/mL MTT reagent (Biovision Inc., Milpitas CA, USA) was introduced and incubated for 4 h. After the supernatant had been removed and 200 μL of DMSO had been added, the wells were well mixed. The absorbance intensity was measured at 570 nm with the Scientific Multiskan GO enzyme marker (Thermo, Shanghai, China). Relative cell viability was expressed as a percentage relative to untreated control cells. ## 3.11. Mitochondrial Respiration Assay The oxygen consumption rate (OCR) was measured with a Seahorse XF96 Extracellular Flux Analyzer (Seahorse Bioscience, North Billerica, MA, USA). HT-22 cells were inoculated at 1 × 105 cells/well density into XFe96 cell culture microplates (Seahorse Bioscience). After treatment, the medium was changed to unbuffered DMEM (pH 7.4) supplemented with 1 mM pyruvate, 2 mM glutamine and 10 mM D-glucose 1 h before the assay. After the basal respiration was measured, oligomycin (1 μM), FCCP (1 μM), and rotenone (0.5 μM) with antimycin A (0.5 μM) were injected sequentially into each well. The OCR was recorded and normalized to 1000 cells per well, and the data were analyzed using Wave desktop software provided by Seahorse Bioscience. ## 3.12. Statistical Analysis Values are expressed as the mean ± standard error of the mean (SEM). All statistics were analyzed using Sigma stat3.5 statistical analysis software, and comparisons between multiple groups were made using two-way ANOVA or one-way ANOVA. If the data were non-normally distributed or had uneven variances, ANOVA on Ranks was used for comparison. p-Values ≤ 0.05 were considered statistically significant. Graphs were prepared using GraphPad Prism 7.0 software. ## 4. Discussion Rats subjected to 2-VO form a chronic hypoperfusion blood supply state, a common VD model [25]. The results of the MWM and passive avoidance test showed significant cognitive impairment in rats treated with 2-VO and that Gas and HBA had an ameliorating effect on the learning memory capacity of VD rats. The function of the neuronal cell was assessed by pathology, and the intervention of Gas and HBA reduced neuronal necrosis and edema. VD has many commonalities with AD, and VD can also induce Aβ and Tau protein deposition, further contributing to the development of dementia [26]. Previous studies have reported that Gas can exert neuroprotective effects by reducing the expression of Aβ and Tau proteins [22,27]. Our results follow expectations that Aβ1-42, p-tau396, and P-tau217 proteins were expressed in VD rat brain tissue and antagonized by Gas and HBA, most significantly at 50 mg/kg. The evaluation results showed no significant difference in the improvement of VD rats treated with 50 mg/kg of Gas and HBA. Previous studies have found that Gas has less brain exposure after entering the body, which is thought to be due to the rapid metabolism of Gas to HBA and poor permeability across the blood–brain barrier (BBB) [28]. The results of HBA metabolic distribution showed that the BBB had high permeability, but due to its small molecular weight, HBA would be rapidly metabolized to the body, and the content in the brain would also decrease [29]. Although Gas and HBA have limitations in their effects on the CNS, our results showed that both Gas and HBA had neuroprotective effects in VD rats. Glucose is the primary energy source of brain tissue, and neurons cannot produce and store glucose and perform normal aerobic metabolic activities when the brain is ischemic and hypoxic [30]. Normal energy metabolism is closely related to general cognitive responses, with the consequence that any deficiency in the energy metabolism process may lead to a decline in cognitive function [24]. Based on the clarification that Gas and HBA have ameliorative effects on VD, we performed the quantitative metabolomic analysis of energy metabolites to investigate the changes induced in the glycolytic pathway, TCA cycle, and pentose phosphate pathway after drug intervention. The results showed that the metabolite levels of glucose 6-phosphate, fructose 1,6-bisphosphate, and phosphoenolpyruvate were significantly increased in the brain tissue of VD rats in the glycolytic pathway. Phosphoenolpyruvate is a substrate for pyruvate kinase, which irreversibly converts phosphoenolpyruvate to pyruvate. Although the phosphoenolpyruvate concentration increased, the downstream pyruvate concentration did not change significantly, whereas the end-product of glycolysis, lactate, was significantly increased. We consider that the increase in upstream and downstream metabolites of glycolysis indicates that many substrates have flowed into the pathway. Additionally, because of the lack of oxygen, the entry of NADH into the respiratory chain is blocked, and the concentration increases. When pyruvate is decarboxylated to acetyl-CoA by oxidation, this enters the TCA cycle [31]. The TCA cycle is the main metabolic pathway for ATP production by the electron transport chain [32] as metabolites of the TCA cycle, citric acid, oxaloacetic acid, and acetyl-CoA, were significantly down-regulated in VD. The analysis results also showed that the levels of ATP and AMP in the brain tissue of VD rats were significantly down-regulated. The above results suggest that brain energy requirements are substantially reduced after ischemia and hypoxia, but glycolysis persists, indicating that complex energy metabolism changes may affect neuronal responsiveness to ischemia and hypoxia [33]. Brain tissue metabolites in VD rats changed after Gas and HBA intervention, where Gas and HBA reduced glucose 6-phosphate content, but intermediate metabolites of the glycolytic pathway, such as 2-phosphoglycerate and 3-phosphoglycerate, were elevated, while lactate, the end-product of glycolysis, was not significantly changed. It has been suggested that although the brain requires large amounts of energy, neurons with truncated glycolytic pathways may serve as a protective mechanism after brain injury [34]. We suggest that Gas and HBA may influence the flux of the glycolytic pathway. In addition, in the analysis of metabolites in the TCA cycle, we found that although there were no significant changes in key metabolites in the brain tissue of VD rats, Gas and HBA significantly increased the content of critical metabolites such as citric acid, succinic acid and fumaric acid in the TCA cycle. We significantly increased the content of ATP, and we consider that Gas and HBA rescued the energy of VD rats which had to some extent been depleted. On the other hand, Gas increases the content of ribose 5-phosphate involving changes in the pentose phosphate pathway. The pentose phosphate pathway produces ribose 5-phosphate for nucleotide synthesis, which controls the metabolic synthesis and redox homeostasis [35]. Some findings suggest that enhancing the pentose phosphate pathway is a potential target for treating ischemic brain injury [36]. Energy metabolism occurs mainly in mitochondria [37], and mitochondrial dysfunction has been well documented as an early event in dementia [38]. The assessment of the mitochondrial function is crucial for understanding energy metabolism-related diseases and the development of corresponding drugs, and mitochondrial respiration is an essential indicator for assessing mitochondrial function. To simulate the in vivo situation in a VD model, we used H2O2 to stimulate HT-22 cells leading to oxidative stress damage [39], and H2O2-induced oxidative damage in neuronal cells can lead to cellular mitochondrial damage, resulting in dysregulated mitochondrial respiration and ATP production [40]. Mitochondrial OCR is one of the most important indicators for assessing mitochondrial respiration [41]. Our results showed a significant decrease in cell viability after H2O2 treatment, and Gas and HBA increased the cell viability of HT-22 cells in a dose-dependent manner. Measuring real-time mitochondrial respiration in HT-22 cells using Seahorse XF extracellular flux analysis showed that H2O2 significantly inhibited the mitochondrial respiratory capacity of HT-22 cells, and Gas and HBA ameliorated this inhibitory effect, including increasing neuronal ATP production. Previous studies have shown that repair of mitochondrial dysfunction prevents hippocampal neuronal damage [42] and that maintenance of mitochondrial function by Gas and HBA may underlie the protection of HT-22 cells from oxidative damage. These data suggest that Gas and HBA enhance neuronal energy metabolism and improve neuronal mitochondrial function. ## 5. Conclusions VD rats showed significant impairment in learning memory function, prominent accumulation of Aβ and Tau proteins, and disturbances in brain energy metabolism and mitochondrial dysfunction. Gas and HBA can exert neuroprotective effects by improving learning memory abilities and neuronal damage, reducing Aβ deposition and Tau protein phosphorylation, improving brain energy metabolism disorders in rats, and reducing mitochondrial dysfunction induced by H2O2 oxidative damage to cells. ## Figures and Scheme Figure 1: Gas and HBA treatment prevent cognitive deficits in VD rats. (A) Representative images of dissected brains; (B–H) Morris water maze results. (B) The escape latency(s) of rats to find the platform during the five days of training; (C–F) time spent and the search times in the platform and target quadrant during the probe trial; (G) average swimming speed of rats during the probe trial; (H) Typical swimming tracks of VD rat in the Morris water maze test. (I–K) Passive avoidance test. (I) step-in latency(s); (J) electric shock time(s); (K) number of errors. Data are presented as the mean ± SEM. # p < 0.05, ### p < 0.001 vs. Sham, p < 0.05, p < 0.01, * p < 0.001 vs. Model. Gas-25, gastrodin 25 mg/kg; Gas-50, gastrodin 50 mg/kg; HBA-25, gastrodigenin 25 mg/kg; HBA-50, gastrodigenin 50 mg/kg.* Figure 2: Effect of Gas and HBA on 2-VO-induced morphological changes of neuronal cells in CA1 and CA3 regions of the hippocampus. (A) Representative pictures of H&E staining to observe the morphology of hippocampal neurons; (B) Representative micrographs of Nissl staining experiments. (C) Quantitative graph of H&E staining; (D) Quantitative graph of Nissl staining. 200× magnification, scale bar = 100 μm. Arrows point to the nuclear chromatin condensation. Values are expressed as means ± SEM. ### p < 0.001 vs. Sham, p < 0.05, *** p < 0.001 vs. Model.* Figure 3: Effect of Gas and HBA on Aβ1-42 and p-tau217 protein expression in CA1, CA3 region, and hippocampus cortex. (A,C) Representative IHC images and statistical histograms of Aβ1-42; (B,D) Representative IHC images and statistical histograms of p-tau217, red arrows point to positive cells; (E) Protein concentration of p-tau217 in brain tissue homogenates. IOD values are expressed as mean ± SEM, ### p < 0.001 vs. Sham, p < 0.05, p < 0.01, * p < 0.001 vs. Model.* Figure 4: Gas and HBA improve the energy metabolism pattern of the brain. (A) PCA model score plot; (B) Heat map of 40 energy metabolites in brain tissue (red indicates upregulation, blue indicates downregulation); (C) VIP plot of Sham vs. Model; (D) VIP plot of Model vs. HBA-50; (E) VIP plot of Model vs. Gas-50. Figure 5: Gas and HBA protect HT-22 cells from H2O2-induced oxidative damage. (A) Cell viability of HT-22 cells treated with different concentrations of Gas for 24 h; (B) cell viability of HT-22 cells treated with different concentrations of HBA for 24 h; (C) cell viability of HT-22 cells treated with different concentrations of H2O2 for 24 h. (D) HT-22 cells treated with 500 μM H2O2 for different times; (E,F) Viability of HT-22 cells treated with 500 μM H2O2 for 12 h under conditions with or without Gas and HBA. Data are presented as the mean ± SEM. ### p < 0.001 vs. Control, p < 0.05, p < 0.01, * p < 0.001 vs. H2O2.* Figure 6: Gas and HBA attenuate H2O2-induced mitochondrial dysfunction in HT-22 cells. (A) The mitochondrial respiratory efficiency of cells treated with 37.5 and 50 μM Gas and HBA and 500 μM H2O2 was determined with a Seahorse XF96 analyzer; (B) Basal respiration quantification analysis; (C) Maximal respiration quantitative analysis; (D) ATP production quantitative analysis. 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--- title: Quercetin Reprograms Immunometabolism of Macrophages via the SIRT1/PGC-1α Signaling Pathway to Ameliorate Lipopolysaccharide-Induced Oxidative Damage authors: - Jing Peng - Zhen Yang - Hao Li - Baocheng Hao - Dongan Cui - Ruofeng Shang - Yanan Lv - Yu Liu - Wanxia Pu - Hongjuan Zhang - Jiongjie He - Xuehong Wang - Shengyi Wang journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10059595 doi: 10.3390/ijms24065542 license: CC BY 4.0 --- # Quercetin Reprograms Immunometabolism of Macrophages via the SIRT1/PGC-1α Signaling Pathway to Ameliorate Lipopolysaccharide-Induced Oxidative Damage ## Abstract The redox system is closely related to changes in cellular metabolism. Regulating immune cell metabolism and preventing abnormal activation by adding antioxidants may become an effective treatment for oxidative stress and inflammation-related diseases. Quercetin is a naturally sourced flavonoid with anti-inflammatory and antioxidant activities. However, whether quercetin can inhibit LPS-induced oxidative stress in inflammatory macrophages by affecting immunometabolism has been rarely reported. Therefore, the present study combined cell biology and molecular biology methods to investigate the antioxidant effect and mechanism of quercetin in LPS-induced inflammatory macrophages at the RNA and protein levels. Firstly, quercetin was found to attenuate the effect of LPS on macrophage proliferation and reduce LPS-induced cell proliferation and pseudopodia formation by inhibiting cell differentiation, as measured by cell activity and proliferation. Subsequently, through the detection of intracellular reactive oxygen species (ROS) levels, mRNA expression of pro-inflammatory factors and antioxidant enzyme activity, it was found that quercetin can improve the antioxidant enzyme activity of inflammatory macrophages and inhibit their ROS production and overexpression of inflammatory factors. In addition, the results of mitochondrial morphology and mitochondrial function assays showed that quercetin could upregulate the mitochondrial membrane potential, ATP production and ATP synthase content decrease induced by LPS, and reverse the mitochondrial morphology damage to a certain extent. Finally, Western blotting analysis demonstrated that quercetin significantly upregulated the protein expressions of SIRT1 and PGC-1α, that were inhibited by LPS. And the inhibitory effects of quercetin on LPS-induced ROS production in macrophages and the protective effects on mitochondrial morphology and membrane potential were significantly decreased by the addition of SIRT1 inhibitors. These results suggested that quercetin reprograms the mitochondria metabolism of macrophages through the SIRT1/PGC-1α signaling pathway, thereby exerting its effect of alleviating LPS-induced oxidative stress damage. ## 1. Introduction The oxidation–reduction (redox) system plays an important role in maintaining cellular redox homeostasis and preventing oxidative damage to DNA, proteins and lipids caused by free radicals. The latest research suggest that the redox system is closely intertwined and interdependent with changes in cellular metabolism. Activated immune cells undergo specific metabolic reprogramming and participate in the regulation of the redox system, which ultimately determines the function of immune cells [1]. The level of cellular oxidative stress can be effectively reduced by modulating the immune metabolism of cells [1,2,3]. Therefore, reducing the hyperresponsiveness of the innate immune system, by regulating immune metabolism with the addition of antioxidants, can reduce the damage to the organism caused by oxidative stress due to overactivation of the immune system. Inflammation is the host’s natural defense response to pathogens or tissue damages and is important for elimination of harmful stimuli and initiation of the healing process [4]. Lipopolysaccharide is one of the major inflammation-causing substances. It stimulates the production of reactive oxygen species (ROS) by macrophages and infiltrating neutrophils through a variety of mechanisms, including activation of NADPH oxidase and inhibition of antioxidant enzymes involved in ROS scavenging [5,6]. ROS act as intracellular messengers that activate redox-sensitive transcription factors, such as nuclear factor κB, thereby stimulating the production of pro-inflammatory cytokines [7,8]. The release of these cytokines may trigger the production of ROS by non-phagocytes [9]. Excessive production of ROS may lead to cellular and tissue damage and trigger many metabolic diseases associated with chronic inflammation and oxidative stress, such as neurodegenerative diseases, cardiovascular diseases, etc. [ 10,11]. Macrophages are heterogeneous cells that play a key role in inflammatory and tissue repair responses. Changes in cellular metabolism are important determinants of macrophage function and phenotype [12]. It has been reported that cellular requirements in specific microenvironments (e.g., inflamed tissues, tumors, etc.), such as survival, growth and proliferation, or specific effector functions, such as phagocytosis execution and cytokine production, would be met by reprogramming the metabolic phenotype. The function of immune cells, especially macrophages, has the potential to assist in the treatment of diseases with a high macrophage load by regulating metabolism. Therefore, it is a promising approach for the treatment of oxidative stress and inflammation-related diseases by metabolic reprogramming of macrophages, such as cancer, atherosclerosis, etc. [ 13,14]. Macrophages play the critical and plastic role in host defense, immune regulation and wound healing by adapting to the local environment and adopting different phenotypes [15]. Generally, macrophages are divided into two main phenotypes based on different activation pathways that are the “classically activated”, pro-inflammatory M1 type, and the “alternatively activated”, anti-inflammatory M2 type. Macrophages in different activation states have different metabolic characteristics and are involved in a variety of pathophysiological processes [16]. Macrophages can cause a variety of diseases when the complex balance of macrophage activity is disrupted [15]. For example, the important relationship between specific steps in the development of colon cancer and obesity-induced inflammation has been pointed out to be mediated by inflammatory cytokines secreted by macrophages, such as interleukin 6 (IL-6) and tumor necrosis factor-alpha (TNF-α) [17,18]. In addition, static macrophages undergo pro-inflammatory differentiation in response to bacteria and LPS characterized by the release of large amounts of cytokines, such as TNF-α, interleukin 1β (IL-1β), IL-6, as well as ROS [19]. These pro-inflammatory mediators are essential for the immune defense of organisms and the killing of microorganisms. However, sustained inflammatory activation of macrophages may lead to collateral tissue damage and chronic inflammation. Therefore, preventing abnormal activation of macrophages and keeping them in the appropriate range of activation is essential to avoid diseases related to inflammatory activation caused by macrophages. Flavonoids have been reported to possess antioxidant, anti-inflammatory, anti-allergy, anti-mutation and anti-cancer effects [20,21,22,23,24]. Studies have shown that flavonoids exert antioxidant effects mainly through scavenging ROS, chelating metal ions, regulating GSH levels, increasing the expression of endogenous antioxidant enzymes, improving the antioxidant properties of low-molecular antioxidants, and regulating various signal transduction pathways, such as the nuclear factor erythroid 2-related factor 2 (NRF2) pathway [21,25,26]. This redox-sensitive transcription factor promotes the induction of phase II detoxification enzymes and other cytoprotective proteins by binding to antioxidant response elements (ARES). NRF2 has been demonstrated to be an important regulatory factor of the inflammatory response. Peritoneal macrophages of NRF2-deficient mice exhibited the increased expression of binding activity genes of proinflammatory cytokines and NF-κB after administration of bacterial endotoxin. Numbers of natural flavonoids, including quercetin, kaempferol, paclitaxel and proanthocyanidins, have been identified as NRF2 activators and therefore show potential for the treatment of certain diseases, such as inflammation, cancer and cardiovascular disease [27]. Quercetin is a naturally occurring flavonoid that is widely found in a variety of fruits and vegetables, including blueberries, broccoli, onions, green tea, etc. It has been illustrated to be one of the most active scavengers of ROS and RNS in vitro and in vivo [21,28,29]. The antioxidant activity of quercetin has been reported to not only prevent oxidative stress, but also reduce inflammation by blocking the ROS-inflammatory cycle [30]. Furthermore, quercetin can alleviate acute lung injury by reducing the levels of oxidative stress markers and increasing the activity of antioxidant enzymes [31]. In the LPS-induced rat model, the levels of superoxide dismutase and catalase increased, and the levels of malondialdehyde decreased after treatment with quercetin, indicating that quercetin enhanced the antioxidant defense system of the rat model [32]. Researchers have conducted studies on the alleviating effect of quercetin on diseases characterized by altered immune response. For example, GSH has been indicated to be involved in the antioxidant process of quercetin’s inhibition of endotoxin-induced oxidant production by human aortic endothelial cells (HAEC) [33]. Activation of bone-marrow-derived dendritic cells and production of cytokines could be reduced by quercetin [34]. The renal inflammation and functional impairment caused by cisplatin could be significantly reduced by quercetin [35]. Alongside that, due to the natural compound properties of quercetin, it is reasonable to predict that it can exert its pharmacological effects with minimal side effects. This was also confirmed by the results of the study on the gene protective and cytoprotective effects of quercetin [36]. Therefore, quercetin is a promising drug for clinical application. However, few studies have reported whether quercetin can inhibit oxidative stress in LPS-induced inflammation by influencing the immune metabolism. Herein, the purpose of this study was to determine the antioxidant effect and mechanism of quercetin in LPS-induced macrophage inflammation. Firstly, the effects of quercetin on the viability and proliferation of LPS-induced RAW264.7 cells were evaluated. Then, the relationship between quercetin and ROS production, mRNA expression of pro-inflammatory cytokines, antioxidant enzyme activity and mitochondrial function in inflammatory macrophages was investigated. Further, the effect of quercetin on the protein expression levels of SIRT1 and PGC-1α in each treatment group was examined by Western blotting. In addition, the SIRT1 inhibitor EX527 was used to explore whether the protective effect of quercetin was related to SIRT1. The results suggested that quercetin may exert its protective effect against oxidative stress in LPS-induced inflammatory macrophages through the SIRT1/PGC-1α signaling pathway. ## 2.1. Quercetin Increases the Viability and Decreases the Differentiation of LPS-Induced RAW264.7 Cells To assess the role of quercetin in LPS-induced macrophages, we first evaluated the effect of quercetin on RAW264.7 cell viability. Cells were treated with 0 to 160 µM of quercetin for 24 h. Cell viability was measured using an MTT assay, which is commonly used for assessing the viability of cells and measuring the cytotoxicity of compounds. As shown in Figure 1B, the cell viability was significantly decreased compared to the blank control group when the concentration of quercetin reached 20 µM ($p \leq 0.01$). This indicated that quercetin was not toxic to cells in the concentration range of 2.5 to 10 µM, while it showed cytotoxicity at 20 µM. Therefore, 10 µM was considered as the maximum non-cytotoxic dose of quercetin and was selected for the subsequent experiments. In addition, 1 µg/mL of LPS was used to induce a cellular oxidative stress model, based on the literature reported [37]. Interestingly, although many types of adherent cells are known to detach from the surface during cell death, macrophages appear to remain strongly attached to the plate even after substantial morphological changes and loss of viable function. As shown in Figure 1C, LPS-treated RAW264.7 cells exhibited significant morphological changes compared to the blank control group, most of which were irregular, and these changes were ameliorated by quercetin. Our results suggested that quercetin can reduce LPS-induced cell spreading and pseudopodia formation by inhibiting cell differentiation. Since the cell morphological changes were obtained by LASEZ microscope image software-assisted imaging, we sought to provide clearer evidence to support these findings. An EdU assay was used to determine the effect of quercetin in the proliferation of LPS-induced RAW264.7 cells. As illustrated in Figure 1D,E, the number of EdU-positive cells was significantly reduced by $93\%$ in LPS group compared to the blank control group ($p \leq 0.01$), while the number of EdU-positive cells in the quercetin-treated group was 5.13 times higher than that in LPS group (Figure 1D,E, $p \leq 0.05$), suggesting that quercetin attenuated the effect of LPS on macrophage proliferation. The above data support the protective effect of quercetin against LPS-induced macrophage damage, cell morphological changes and cell proliferation reduction. ## 2.2. Quercetin Inhibits ROS Production and Pro-Inflammatory Cytokine Expression, and Improves the Antioxidant Capacity of LPS-Induced RAW264.7 Cells ROS is the key executor in cellular and tissue damage caused by oxidative stress, and is closely associated with diseases [38]. The fluorescent probe (DCFH-DA) was employed to determine the effect of quercetin on ROS production. Compared to the blank control group, the fluorescence intensity of DCF (the oxidation product of DCFH-DA) in the LPS group was significantly increased by 1.08 times ($p \leq 0.01$). In contrast, the fluorescence intensity of DCF in quercetin-treated group was significantly reduced by 0.25 times compared to the LPS group ($p \leq 0.01$, Figure 2A,B). These results suggested that quercetin has an inhibitory effect on LPS-induced ROS production in macrophages. For further understanding of the antioxidant capacity of quercetin, the effects of quercetin on the enzyme activity in LPS-induced RAW264.7 cells were evaluated. As presented in Figure 2C,D, LPS significantly reduced the level of GSH by $37\%$ compared to the blank control group ($p \leq 0.05$), while the quercetin-treated group showed a significant 0.82-fold increase in the level of GSH compared to the LPS group ($p \leq 0.01$). The opposite results were observed at the MDA level, that was, LPS significantly increased the level of MDA by $41\%$ compared to the blank control group ($p \leq 0.01$), while the quercetin-treated group showed a significant decrease of $32\%$ in MDA level ($p \leq 0.01$). The results indicated that quercetin could exert its antioxidant effect by increasing intracellular GSH levels and decreasing MDA levels. To verify the role of quercetin in the pro-inflammatory cytokine expression, the mRNA levels of TNF-α, IL-6, IL-1β and NF-κB in LPS-induced RAW264.7 were determined by quantitative real-time PCR. As demonstrated in Figure 2E–H, the mRNA expression of TNF-α, IL-6, IL-1β and NF-κB showed similar trends. That was, LPS significantly increased their mRNA expression compared to the blank control group, with a fold increase of 17.21, 57,143, 2222.76 and 0.87, respectively ($p \leq 0.01$). On the other hand, the high expression of these pro-inflammatory cytokines was significantly decreased by $31\%$, $56\%$, $35\%$ and $41\%$, respectively, after treatment with quercetin ($p \leq 0.01$). Results indicated that quercetin can reduce the high expression of inflammatory cytokines caused by LPS, and thus inhibit the inflammatory response. ## 2.3. Quercetin Protects Mitochondrial Function and Prevents LPS-Induced Mitochondrial Morphological Damage Mitochondrial membrane potential is one of the indicators of mitochondrial function. The dysfunction of mitochondrial morphological potential in LPS-induced RAW264.7 cells was detected by JC-1 staining in this study. As shown in Figure 3A, cells in the blank control group and quercetin group exhibited strong red fluorescence under inverted fluorescence microscope, while the intensity of red fluorescence of cells in the LPS group was significantly decreased. Notably, the red fluorescence intensity of the quercetin-treated group was significantly enhanced compared to that of the LPS group. The results of JC-1 ratio analysis (Figure 3B) showed that the mitochondrial membrane potential in the LPS group was significantly reduced by $48\%$ compared to the blank control group ($p \leq 0.01$), while that of the quercetin-treated group was significantly increased by $49\%$ compared to the LPS group ($p \leq 0.01$). The experimental results demonstrated that quercetin inhibits the LPS-induced decrease in mitochondrial membrane potential, thus reducing mitochondrial damage and protecting mitochondrial function. Further, the mitochondrial ultrastructure in RAW264.7 cells was observed by transmission electron microscopy, to visualize the effect of quercetin on LPS-induced changes in cellular mitochondrial morphology. As displayed in Figure 3C, mitochondrial morphology of the blank control group and quercetin group was normal, with round or oval shape, continuous outer membrane, tightly arranged inner cristae and uniform matrix density. However, the mitochondria of the LPS-treated cells were obviously swollen, the matrix was thin and contained a small amount of flocculent material, the matrix particles disappeared, cristae lysed and fractured, and a large number of vacuoles appeared. LPS-treated cells exhibited obvious damaged mitochondria relative to the blank control. Meanwhile, the electron microscopic images of mitochondrial morphology in the quercetin-treated group showed that some of the mitochondria in this group of cells had normal morphology, and some of the mitochondria were mildly swollen, and the intercristae space was enlarged. According to the degree of mitochondrial morphological alterations in each group, it could be deduced that quercetin protects against mitochondrial damage caused by LPS to some extent. Mitochondrial DNA (mtDNA) damage, as well as the decline in mitochondrial RNA (mtRNA) transcription, protein synthesis, and mitochondrial function, can reflect mitochondrial damage. The possible reasons that mtDNA is more susceptible to oxidative stress damage than nuclear DNA are that it is close to the respiratory chain of the inner mitochondrial membrane, lacks protective histone-like proteins and has less repair activity for damage [39]. Mitochondrial dysfunction could be assessed by the quantification of mtDNA copy number [40]. In this study, the mtDNA copy number was expressed as the ratio of 18S RNA to mtDNA. As presented in Figure 3D, the mtDNA copy number in the quercetin group was significantly increased by $33\%$ compared to the blank control group ($p \leq 0.01$), while the decrease of mtDNA copy number in the LPS group was not significant ($p \leq 0.05$). Notably, the mtDNA copy number of the quercetin-treated group was not significantly different from that of the LPS group, suggesting that the protective effect of quercetin against cell damage caused by LPS was not significantly related to mitochondrial dysfunction. To further investigate the effect of quercetin on mitochondrial function, ATP content, which depends on the cellular mitochondrial activity, was measured. As illustrated in Figure 3E, treatment with quercetin alone significantly increased the ATP content by $13\%$ ($p \leq 0.01$), and stimulation with LPS alone significantly decreased the ATP content by $17\%$ ($p \leq 0.01$) compared to the blank control group. Alongside that, the ATP content of the quercetin-treated group was significantly increased by $15\%$ compared to that of the LPS group ($p \leq 0.01$). Thus, it can be concluded that quercetin contributes to the increase the intracellular ATP production. Meanwhile, the content of ATP synthase, which is an important enzyme involved in mitochondrial oxidative phosphorylation [41], was measured to monitor the mitochondrial function in LPS-induced RAW264.7 cells. As shown in Figure 3F, the content of ATP synthase in the LPS group was significantly decreased by $25\%$ compared to the blank control group ($p \leq 0.01$), whereas in the quercetin-treated group, it was significantly increased by $22\%$ compared to the LPS group ($p \leq 0.05$). This is consistent with the experimental results of ATP content measurement described above. These results indicated that quercetin attenuates the adverse effects of LPS on ATP production and ATP synthase, thereby protecting mitochondrial function. ## 2.4. Quercetin Suppresses LPS-Induced ROS Production and Mitochondrial Damage in RAW264.7 Cells via the SIRT1/PGC-1a Signaling Pathway The SIRT1/PGC-1a signaling pathway is closely related to the regulation of cellular oxidative stress and inflammation [42,43]. To investigate the mechanism by which quercetin exerts its antioxidant effects in inflammatory macrophages, the expression of SIRT1 and PGC-1α proteins was measured. Western blotting analysis showed that SIRT1 and PGC-1α protein levels in RAW264.7 cells stimulated with LPS were significantly downregulated by $25\%$ and $31\%$, respectively, compared to the blank control group ($p \leq 0.05$, Figure 4A–C). Simultaneously, compared to stimulation with LPS alone, the protein expression of SIRT1 and PGC-1α was significantly elevated by $18\%$ and $51\%$, respectively, when quercetin was added for co-treatment after LPS stimulation ($p \leq 0.05$, Figure 4A–C), indicating that the protection of quercetin against LPS-induced oxidative damage in macrophages may be regulated through the SIRT1/PGC-1α signaling pathway. To further assess the role of SIRT1 in the signaling mechanism of quercetin, EX527 was administered to inhibit SIRT1. As demonstrated in Figure 4D, the fluorescence intensity of DCF was obviously enhanced in the EX527 group compared to the quercetin-treated group. Consistent with this, the intracellular ROS content of the EX527 group was $23\%$ higher than that of the quercetin-treated group ($p \leq 0.05$, Figure 4E). Therefore, the inhibition of SIRT1 attenuated the inhibitory effect of quercetin on LPS-induced ROS production in macrophages. The determination of mitochondrial membrane potential showed that, compared to the quercetin-treated group, the red fluorescence intensity of the EX527 group was obviously diminished (Figure 4F) and the JC-1 ratio ($p \leq 0.05$, Figure 4G) was significantly decreased by $48\%$, indicating that inhibition of SIRT1 reversed the protective effects of quercetin on mitochondrial membrane potential. In addition, transmission electron micrographs (Figure 4H) of the mitochondrial ultrastructure showed that the mitochondria in the EX527 group were significantly swollen, with a large number of vacuoles and severe morphological damage compared to the quercetin-treated group. Thus, it can be seen that the inhibition of SIRT1 reversed the protection of quercetin on the mitochondrial morphology of inflammatory macrophages. ## 3. Discussion Inflammation is a host defense mechanism of the organism against harmful stimuli from pathogens and is characterized by excessive production of ROS by activated immune cells (macrophages, plasma cells and lymphocytes, etc.) [ 44]. Adducts produced by the reaction of ROS and lipids, proteins and DNA lead to oxidative stress and induces the release of cytokines, growth factors and chemokines that stimulate pathways leading to amplified inflammation [44,45]. The cycle of inflammation can be perpetuated by ROS production and oxidative stress, which leads to a chronic state that drives a variety of inflammatory pathologies, ultimately leading to cellular damage and death [46,47]. Given the inseparable and closely linked relationship between inflammation and oxidative stress, modulating the redox balance of inflammatory immune cells and therapeutically inhibiting the inflammation–oxidative stress cycle may become an effective approach for the treatment of inflammation-related diseases. Here, we examined the effects of quercetin on the cell morphology and cell proliferation of LPS-induced inflammatory macrophages. The results showed that quercetin significantly ameliorated both the morphological alterations (including cell differentiation, spreading and pseudopod formation) and cell proliferation inhibition of macrophages caused by LPS. It is thus known that quercetin protects macrophages in the LPS environment, but its specific action and mechanism remain unclear. To further elucidate the role of quercetin in inflammatory macrophages, we examined the production of ROS, the contents of MDA, GSH and the mRNA expression of pro-inflammatory cytokines in LPS-induced RAW264.7 cells. The results demonstrated that quercetin inhibited ROS production and reduced the mRNA expression of pro-inflammatory cytokines in inflammatory macrophages. These results confirmed that quercetin positively regulates the REDOX balance of inflammatory macrophages and improves the antioxidant capacity of LPS-induced RAW264.7 cells by inhibiting the production of ROS, MDA and the expression of pro-inflammatory cytokines and promoting the production of antioxidant enzymes. Mitochondria are organelles surrounded by bilayer membranes found in most cells and are the main site of aerobic respiration. Their functions include energy conversion, tricarboxylic acid cycle, oxidative phosphorylation, calcium ion storage, etc. [ 48]. Mitochondrial stability is critical for the reduction of apoptosis and the promotion of cell growth. Excess ROS generated by mitochondrial oxidative stress leads to dysfunction of the electron transport chain and disrupts the regulation of energy production, ultimately causing mitochondrial damage characterized by reduced mitochondrial membrane potential and disruption of mitochondrial membrane proteins [49,50,51]. Mitochondria-dependent apoptotic pathways are activated when mitochondria are damaged, leading to cellular dysfunction [52]. In order to explore the effect of quercetin on the mitochondria of inflammatory macrophages, transmission electron microscopy was used to observe the morphology of mitochondria in each treatment group. As expected, we found that quercetin mitigated LPS-induced mitochondrial morphological abnormalities in macrophages, suggesting that quercetin has a protective effect on mitochondrial macrophages in an LPS environment. The reduction in mitochondrial membrane potential is generally considered to be a late event in the apoptotic pathway, and it is therefore also regarded as an important biomarker of oxidative-stress-induced apoptosis [53]. The main bioenergetic function of mitochondria is ensured by mitochondrial membrane potential, which decreases with mitochondrial damage and eventually leads to the loss of cellular function [54,55]. JC-1 is one of the common mitochondrial fluorescent probes, it forms aggregate in healthy cells that stain mitochondria red. In contrast, when the mitochondrial membrane potential is reduced, the dye leaks from the mitochondria and appears in a green monomeric form. In this study, JC-1 was used to determine the effect of quercetin on the mitochondrial membrane potential of inflammatory macrophages. The results illustrated that quercetin inhibited the decrease of mitochondrial membrane potential in macrophages caused by LPS. mtDNA is highly susceptible to oxidative stress due to its intimate relationship with high concentration of ROS, increasing the risk of mitochondrial dysfunction. mtDNA copy number is related to the production of ATP and the activity of mitochondrial enzymes, and is the substitute marker of mitochondrial dysfunction [56,57]. Our study found that there is no significant difference in the mtDNA copy number among different treatment groups, indicating that the protective effect of quercetin on the mitochondria of inflammatory macrophages was not significantly related to the mtDNA copy number. This might be due to the fact that mtDNA copy number changes depend on strict tissue-specific regulation, the mechanism of which is largely unknown [58], and quercetin plays a minor role in this specific regulation, and thus has no significant effect on the downregulation of mtDNA copy number caused by LPS. In addition, the mtDNA copy number is dynamically changing with time [59]. Literature reported that the mtDNA copy number of human embryonic kidney cells (HEK) was reduced to $30\%$ within 48 h under the influence of 2′–3′-dideoxycytidyne (ddC), and returned to the baseline level within 32 h in the absence of ddC [60]. The treatment time of our experiment was 24 h, therefore the experimental results of quercetin’s effect on the mtDNA copy number might be affected by the length of the experimental time and need to be further investigated. Energy for the maintenance of physiological functions and survival of the organism is mainly supplied by ATP, and this requirement is an unstable process. In addition to their signaling properties, ROS are also degenerative agents that result in aging and disease [61]. Both of them are produced mainly by mitochondria, and their excess determines the fate of cells [62]. According to our experimental results, quercetin has a significantly positive regulatory effect on ATP content in inflammatory macrophages and the opposite effect on ROS. Therefore, quercetin regulates the balance of ATP and ROS in inflammatory macrophages tending to maintain the energy supply of cells. Mitochondrial ATP synthase is a proton-powered ATP generator that uses the mitochondrial electron transport chain and is the main enzymatic complex that produces cellular ATP under aerobic conditions [63,64]. Its defects are directly or indirectly associated with a variety of diseases, including neurodegenerative diseases, retinitis pigmentosa syndromes, cardiomyopathies, etc. [ 65,66]. It has been reported that the upregulation of ATP synthase activity can alleviate mitochondrial oxidative stress [67]. Consistent with this, our results also demonstrated that quercetin significantly upregulated ATP synthase content in inflammatory macrophages. It could be concluded that the effect of quercetin in alleviating LPS-induced oxidative stress damage may be achieved by protecting the mitochondrial function of inflammatory macrophages. However, in addition to the decrease in ATP synthase activity, the increase in ATP consumption may also be responsible for the decrease in ATP content. Specifically, LPS-induced ROS overproduction led to mitochondrial dysfunction characterized mainly by the disruption of mitochondrial membrane potential. Loss of mitochondrial membrane potential leads to the defective mitochondrial electron transport chain, reduced metabolic oxygen consumption and excessive ATP depletion, and put it into a hypoenergetic metabolic state, thus triggering mitochondrial oxidative stress [68]. In addition, mitochondrial ATP content is also affected by calcium overload [69], hypoxia [70], increased mitochondrial membrane permeability [71] and mitochondrial DNA mutations [72]. The relationship between the effect of quercetin on mitochondrial ATP content and these factors remains to be further studied. Sirtuin 1 (SIRT1) is a conserved nicotinamide adenine dinucleotide (NAD)-dependent mammalian protein deacetylase, with multiple biological functions. It is commonly described to perform critical functions in cell differentiation, senescence, metabolism and apoptosis [73,74,75]. In recent years, an increasing number of studies have reported that SIRT1 can coordinate inflammatory signaling, so it is considered an important target for immune microenvironment regulation. In the study of a murine hepatic ischemia/reperfusion injury model [76], SIRT1 activation alleviated leukocyte infiltration, and higher SIRT1 levels were associated with a lower proinflammatory cytokine profile. In osteolysis models, SIRT1 activation by hydrogen sulfide mitigated the particle-induced inflammatory response and prevented bone resorption [77]. PGC-1α is a multifunctional protein present in the anti-oxidative stress system, which plays a key role in transcriptional regulation by activating most nuclear receptors and co-activating multiple transcription factors [78]. In addition, PGC-1α is an important transcriptional regulator of mitochondrial function, and its activation contributes to increasing the expression of nuclear coding subunits of the mitochondrial respiratory chain [79]. In the presence of oxidative stress, SIRT1 is deacetylated with increasing NAD+/NADH ratio, thereby activating PGC-1α [80]. The increase of PGC-1α regulates cellular response to oxidative stress and induces a significant increase in the gene expression of antioxidant enzymes, including SOD, GPX1, etc. [ 81]. Notably, the transcriptional activity of PGC-1α is very low when it is not bound to transcription factors, but significantly elevated when it is bound to SIRT1 [82]. Our study found that the protein expression of SIRT1 and PGC-1α was significantly decreased in RAW264.7 cells treated with LPS, while their protein expression was significantly increased by the exogenous use of quercetin. To further demonstrate the role of SIRT1 in the process of quercetin protection of inflammatory macrophages from oxidative stress, we used SIRT1 inhibitor, EX527. Inhibition of SIRT1 significantly attenuated the inhibitory effect of quercetin on LPS-induced ROS production in macrophages, and reversed the protective effect of quercetin on mitochondrial membrane potential and morphological structure of inflammatory macrophages. These results suggest that the protection of inflammatory macrophages from oxidative stress by quercetin is associated with the increased expression of SIRT1. In conclusion, quercetin can ameliorate LPS-induced oxidative damage in inflammatory macrophages via the SIRT1/PGC-1α signaling pathway (Figure 5). ## 4.1. Materials and Reagents Quercetin and LPS were purchased from Sigma-Aldrich (St. Louis, MO, USA). The mouse macrophage-like cell line, RAW264.7 (CSTR:19375.09.3101MOUTCM13), was acquired from the National Collection of Authenticated Cell Cultures, the Chinese Academy of Sciences (Shanghai, China). Fetal bovine serum (FBS) and Dulbecco’s modified eagle’s medium (DMEM) high glucose were purchased from Gibcol Life Technology (Thermo Fisher, Waltham, MA, USA). An enhanced ATP Assay Kit was acquired from Beyotime® Biotechnology (Shanghai, China). anti-PGC1 (Cat# ab191838), anti-glutathione peroxidase 4 (Cat# ab125066), anti-AMPK alpha 1 (Cat# ab32047) and anti-SIRT1 (Cat# ab110304) antibodies were purchased from Abcam Biotechnology (Cambridge, MA, USA). Phospho-AMPK (Thr172) (Cat# 2535s) antibody was purchased from Cell Signaling Technology (Danvers, MA, USA). The 3-4,5-dimethylthiazole-z-yl-3,5-diphenyltetrazolium bromide (MTT), trypsin, dimethyl sulfoxide (DMSO), phosphate-buffered saline (PBS), LA Assay Kit, Micro Pyruvate (PA) Assay Kit and Mitochondrial Membrane Potential Assay Kit with JC-1 were purchased from Solarbio Science & Technology Co. Ltd. (Beijing, China), and stored at −20 °C. EX-527 and compound C were obtained from Med Chem Express (Monmouth Junction, NJ, USA). ## 4.2. Cell Culture RAW264.7 macrophages were cultured in DMEM containing $10\%$ FBS at 37 °C, in a fully humidified incubator containing $5\%$ CO2. Once grown as a dense monolayer, the cells were routinely passed to a third generation. ## 4.3. Cell Viability Assay The cell viability was determined by an MTT assay according to a previous procedure, with minor modifications [83]. RAW264.7 cells were seeded in 96-well plates, at a density of 1 × 104 per well in a culture medium. The cells were treated with 0 to 160 µM quercetin for 24 h, then 20 µL of $0.5\%$ MTT was added to each well. Absorbance values were measured at 490 nm after 4 h of MTT addition, by using a spectrophotometer (Epoch Microplate Spectrophotometer, BioTek Instruments, Inc., Winooski, VT, USA). The cell viability was calculated according to the following formula:Cell Viability (%) = [(absorbance of treatment − absorbance of blank)/(absorbance of control − absorbance of blank)] × $100\%$ ## 4.4. Observation of Cell Morphological Changes RAW264.7 cells were plated in 6-well plates with a density of 6 × 105 per well, and cultured for 24 h. Subsequently, the blank control group was treated with PBS for 24 h; the quercetin group was treated with quercetin for 24 h; the LPS group was treated with PBS for 12 h at first, followed by adding LPS (1 µg/mL) for another 12 h stimulation; the quercetin-treated group was treated with quercetin alone in the first 12 h and then LPS (1 µg/mL) was added with quercetin for co-treatment in the second 12 h. The morphological changes of the cells in each group were observed by the LASEZ Microscope Assisted Imaging System. ## 4.5. Cell Proliferation Assay The changes of cell proliferation were determined using a previously described procedure [84], with some modifications. RAW264.7 cells were treated as described in Section 2.4. EdU staining was conducted using the BeyoClick™ EdU Cell Proliferation Kit with Alexa Fluor 594 (Beyotime, Shanghai, China, Cat. No. C00788L). The treated cells were washed with PBS and then fresh DMEW was added, containing 10 μM EdU. After incubation at 37 °C for 2 h, the cells were washed again with PBS to remove DMEM and free EdU probes. Cells were then fixed with $4\%$ paraformaldehyde for 30 min at room temperature, followed by DAPI staining for 3 min. After an additional wash in PBS, the cells were observed under a laser-scanning confocal microscope (Model: ZEISS LSM800). The intensities of fluorescence were analyzed by the ImageJ software (version No. 1.53e). The percentage of EdU-positive cells was calculated according to the following formula:EdU-positive cell (%) = EdU (Red fluorescence)/Hoechst (Blue fluorescence) × $100\%$ ## 4.6. Determination of Cellular ROS Production The ROS production in RAW264.7 cells was determined by dichloro-dihydro-fluorescein diacetate (DCFH-DA) assay according to an earlier reported method [85], with slight modifications. Briefly, cells inoculated on the confocal dish were cultured at 37 °C for 24 h. The confocal dish was washed with PBS (100 μL), and the growth medium was later removed. Then, different concentrations of PCA were added to pre-protect for 30 min, followed by 12 h of treatment with quercetin (10 uM). Finally, the cells were incubated with DCFH-DA (Jiancheng Bioengineering Institute, Nanjing, China), with a final concentration of 10 μM for 30 min at 37 °C, and then washed twice with PBS. DCFH-DA was hydrolyzed to DCFH carboxylate anion by cellular esterases and then oxidized by ROS to highly fluorescent dichlorofluorescein (DCF). Fluorescence was observed by confocal microscopy. ## 4.7. Evaluation of Enzyme Activity The levels of oxidative stress in cell samples were assessed by measuring enzyme activity. RAW264.7 cells were treated as described in Section 2.4. The cells of each group were lysed and their concentrations of total protein were measured with the BCA protein assay kit (TaKaRa Bio, Shiga, Japan), respectively. The activity of reduced glutathione (GSH) and the content of malondialdehyde (MDA) in cells were determined by using commercial kits, according to the manufacturer’s instructions (Nanjing Jiancheng Technology Co., Ltd., Nanjing, China). ## 4.8. Detection of mRNA Expression The mRNA expression levels of inflammatory factors (IL-1β, TNF-α, IL-6 and NF-κB) were detected by quantitative real-time polymerase chain reaction (qRT-PCR). RAW264.7 cells were treated as described in Section 2.4. Total RNA of each group of cells was extracted using the TRIzol reagent (Vazyme, Nanjing, China), and reverse transcribed into cDNA using the Prime Script RT reagent kit (Thermo Fisher, Waltham, MA, USA). Quantitative PCR was performed using ChamQ Universal SYBR qPCR Master Mix (Vazyme, Nanjing, China). The reaction was performed at a total volume of 10 μL, with the assay solution containing 5 μL ChamQ Universal SYBR qPCR Master Mix, 3.6 μL deionized H2O, 1 μL cDNA template, and 0.2 μL each of the forward and reverse primers. The fold changes in mRNA expression were calculated by comparing the β-actin normalized threshold cycle numbers (Ct), using the 2−ΔΔCT method. Triplicate wells were run for each experiment and two independent experiments were performed. The primer sequences designed for qRT-PCR analysis are listed in Table 1. ## 4.9.1. Detection of Mitochondrial Membrane Potential The changes in mitochondrial membrane potential (Δψm) were observed with JC-1 staining dye assay kit (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China), according to the method described by early literature [86]. JC-1 dye is a lipophilic cationic fluorescent dye with dual (red and green) emission wavelengths, and the attenuation of its red/green fluorescence intensity ratio is commonly used to represent an increase in mitochondrial membrane depolarization. The cells were cultured on the confocal dish with different treatments. Then, the old medium was replaced with fresh medium containing JC-1. Cells continued to incubate at 37 °C for 25 min and were then washed twice with ice-cold PBS. Cell morphology and staining were observed and photographed by an inverted fluorescence microscope (ZEISS Axio Observer A1, Oberkochen, German) and the intensities of fluorescence were analyzed by the ImageJ software (version No. 1.53e). ## 4.9.2. Observation of Mitochondrial Morphology The morphological changes of mitochondria were observed by transmission electron microscopy (TEM). RAW264.7 cells were treated as described in Section 2.4. The medium of the treated cells in each group was discarded and $3\%$ glutaraldehyde was rapidly added. The cells were gently scraped and collected into centrifuge tubes, then centrifuged at 1000 rpm for 5 min after discarding glutaraldehyde. Glutaraldehyde ($3\%$) was added again to fix the cells, followed by graded alcohol dehydration, resin embedding, and ultrathin section staining with uranyl acetate and citric acid. Autophagosomes and cellular mitochondria were observed by transmission electron microscopy (JEM-1400 Flash, Tokyo, Japan). ## 4.9.3. Determination of Mitochondrial DNA Copy Number RAW264.7 cells were treated as described in Section 2.4. After treatments, total DNA of the cells in each group was extracted by the Animal Tissues/Cells Genomic DNA Extraction Kit (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China), according to the manufacturer’s instructions. The concentrations of extracted DNA were quantified by measuring absorbance at 260 nm, and then quantitative PCR of DNA was performed using ChamQ Universal SYBR qPCR Master Mix (Vazyme, Nanjing, China). Mitochondrial DNA copy numbers were assessed by using primers targeting mitochondria-encoded mtDNA genes (forward: 5′-ATCCTCCCAGGATTTGGAAT-3′; reverse-5′ACCGGTAGGAATTGCGATAA-3′). Primers designed against the nuclear-encoded 18s RNA gene (forward: 5′-TTCGGAACTGAGGCCATGATT-3′; reverse: 5′-TTTCGCTCTGGTCCGTCTTG-3′) were used for normalization. The mitochondrial DNA copy number was calculated by using the 2−ΔΔCT method. ## ATP Contents RAW264.7 cells were treated as described in Section 4.4. Lysis solution (200 µL) was added to each well after removing the medium, the cells were lysed and then collected into centrifuge tubes. The lysed cells were centrifuged at 4 °C with 12,000 rpm for 5 min. The supernatant was collected and the ATP content was measured by the enhanced ATP assay kit, according to the manufacturer’s instructions (Beyotime® Biotechnology, Shanghai, China). ## ATP Synthase Content RAW264.7 cells were treated as described in Section 4.4. Briefly, the treated cells were collected and lysed, and the supernatant was collected by centrifugation. The content of ATP synthase was determined by the ATP synthase assay kit, according to the manufacturer’s instructions (Jiangsu Meimian Industrial Co., Ltd., Yancheng, China). ## 4.10. Western Blotting Analysis RAW264.7 cells were treated as described in Section 2.4. After treatment, the culture medium of each group was discarded, and RIPA lysis buffer, containing PMSF, was added. The cells were scraped gently and collected into centrifuge tubes. After centrifugation at 4 °C with 12,000 rpm for 30 min, the supernatants were collected and their concentrations of total protein were measured by BCA protein assay kit. The obtained samples were mixed with 5 × loading buffer and heated in boiling water for 10 min to denature proteins, then resolved in $10\%$ SDS-PAGE gels and transferred to NC membranes. The membranes were blocked with QuickBlock™ Blocking Buffer for 15 min after TBST buffer washing, and then incubated for 12–16 h at 4 °C with corresponding antibody solutions (1:1000). After washing, the membranes were incubated with secondary antibodies for 1 h at 37 °C. The chemiluminescence-positive signals were detected by the ECL Western blotting detection reagent (Cat. No. 34079, Thermo Scientific, Waltham, MA, USA), the protein band images were scanned and analyzed as the integrated absorbance (IA = mean OD × area) using the ImageJ software (version No. 1.53e), and the relative levels of target proteins were normalized to β-actin (target protein IA/β-actin IA). ## 4.11. SIRT-1 Inhibition Assay In this section, the EX-527 group was added in addition to the four cell treatment groups described in Section 2.4. The EX-527 group was treated with quercetin for 12 h, and then LPS (1 µg/mL) and EX-527 (10 μM) were added to co-treat for 12 h. The ROS expression content, mitochondrial membrane potential and mitochondrial morphological changes of the cells in each treatment group were detected and observed according to methods described in Section 4.6, Section 4.9.1 and Section 4.9.2, respectively. ## 4.12. Statistical Analysis Statistical analyses were performed by the GraphPad Prism software (version No. 9.0; GraphPad Software, Inc.). The data of experiments were expressed as the mean ± standard deviation of three independent experiments, and comparisons between groups were first tested for normal distribution using the Shapiro–Wilk test, then parametric testing using the Brown–Forsythe test, and finally, a one-way ANOVA with Tukey’s post hoc test. $p \leq 0.05$ was considered statistically significant. ## 5. Conclusions In summary, the present study revealed that quercetin alleviates LPS-induced oxidative stress damage in macrophages by promoting antioxidant enzyme activity, inhibiting ROS production and inflammatory factor overexpression, and protecting mitochondrial function. Furthermore, SIRT1 and PGC-1α have been shown to play important roles in the reprogramming of inflammatory macrophage metabolism by quercetin. The alleviating effect of quercetin on LPS-induced oxidative stress damage in macrophages is exerted through the SIRT1/PGC-1α signaling pathway, which participates in the mitochondrial metabolism reprogramming. However, the discussion of quercetin’s oxidative stress alleviating effect in this study is limited to in vitro experiments, the in vivo mechanism verification experiments will be conducted in the next research work. 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--- title: 'Towards the Sustainable Exploitation of Salt-Tolerant Plants: Nutritional Characterisation, Phenolics Composition, and Potential Contaminants Analysis of Salicornia ramosissima and Sarcocornia perennis alpini' authors: - Maria Lopes - Ana Sanches Silva - Raquel Séndon - Letricia Barbosa-Pereira - Carlos Cavaleiro - Fernando Ramos journal: Molecules year: 2023 pmcid: PMC10059647 doi: 10.3390/molecules28062726 license: CC BY 4.0 --- # Towards the Sustainable Exploitation of Salt-Tolerant Plants: Nutritional Characterisation, Phenolics Composition, and Potential Contaminants Analysis of Salicornia ramosissima and Sarcocornia perennis alpini ## Abstract Increasing soil salinisation represents a serious threat to food security, and therefore the exploitation of high-yielding halophytes, such as Salicornia and Sarcocornia, needs to be considered not merely in arid regions but worldwide. In this study, Salicornia ramosissima and Sarcocornia perennis alpini were evaluated for nutrients, bioactive compounds, antioxidant capacity, and contaminants. Both were shown to be nutritionally relevant, exhibiting notable levels of crude fibre and ash, i.e., 11.26–15.34 and 39.46–$40.41\%$ dry weight (dw), respectively, and the major minerals were Na, K, and Mg. Total phenolics thereof were 67.05 and 38.20 mg of gallic acid equivalents/g extract dw, respectively, mainly p-coumaric acid and quercetin. Both species displayed antioxidant capacity, but S. ramossima was prominent in both the DPPH and ß-carotene bleaching assays. Aflatoxin B1 was detected in S. ramosissima, at 5.21 µg/Kg dw, which may pose a health threat. The Cd and Pb levels in both were low, but the 0.01 mg/Kg Hg in S. perennis alpini met the maximum legal limit established for marine species including algae. Both species exhibit high potential for use in the agro-food, cosmetics, and pharmaceutical sectors, but specific regulations and careful cultivation strategies need to be implemented, in order to minimise contamination risks by mycotoxins and heavy metals. ## 1. Introduction Worldwide, there are about 400,000 plant species [1], of which more than 50,000 are regarded as edible [2]. Yet, of these only about 150 are grown on a large scale for human consumption, $10\%$ of which provide $90\%$ of global dietary energy needs [2]. Clearly, the limited number of crops on which agriculture currently depends contrasts markedly with the entirety of plant bioavailability that the planet offers. This deserves our utmost attention, considering that, in 2020, $10\%$ of the world’s population suffered from severe hunger [3]. In recent years, economic and health crises, conflicts, and the harmful effects of climate change have undermined food security all over the world [3]. Biodiversity can undoubtedly help address challenges such as these, but greater knowledge and a more comprehensive view of available resources are required. Among the various plant resources currently underutilised, halophytes stand out as relatively rare, i.e., about 1–$2\%$ of the total angiosperms, but capable of tolerating salinity levels beyond those with which most plants could cope [4,5]. Climate change is leading to rising sea levels and increased drought stress, which in turn contribute to an increasingly salinised environment. This has tremendously negative consequences for agriculture, as traditional crops cannot withstand severe salinisation and so either brutally reduce their yields or simply wither [4]. By contrast, halophytes are capable of thriving in such adverse conditions, still providing high yields [6]. Moreover, they exhibit a wide range of applications for dealing with severe famine situations, as traditional and gourmet food, animal feed, and as functional ingredients, and finally as sources f bioactive compounds such as polyphenols—compounds of high value due to their antioxidant properties [5]. Despite this, the full potential of halophytes largely remains to be studied and exploited, principally in relation to their role in human nutrition and health. Among all halophytes, Salicornia L. and Sarcocornia L., both belonging to the Amaranthaceae family, have been singled out as yielding particularly promising food crops, especially owing to their extreme inherent salt tolerance, superior to 500 mM [6]. The two genera comprise about 30 species each, although there is currently no absolute consensus on the exact number of accepted species [7,8]. Actually, Salicornia and Sarcocornia species are morphologically and ecologically very similar, which makes their distinction complex [9]. The major difference is related to their habit, as Salicornia species have an annual life cycle and are of the herbaceous type, whilst Sarcocornia species have a perennial life cycle and are woody at least at the base [10]. Both exhibit a peculiar appearance, i.e., fleshy, juicy stems with barely perceptible scale-like leaves [9]. An important morphological difference between Sarcocornia and Salicornia is that the flowers of the former are always arranged in a horizontal row, whilst those of the latter form a triangle with a larger central flower and two smaller lateral ones [9]. Salicornia and Sarcocornia spp. thrive all over the world, essentially in zones with brackish water, along coastal areas such as salt marshes and mangroves, and in some semi-arid and arid regions such as saline deserts [5,6]. To survive and reproduce in these challenging environments, Salicornia and Sarcocornia, two extreme dicotyledons, have developed a set of adaptive mechanisms to maintain water and ionic homeostasis and protect against abiotic and biotic stress, including (i) selective ion uptake and transport; (ii) ion compartmentalisation; (iii) succulence; (iv) synthesis and accumulation of osmolytes; and (v) synthesis and accumulation of protective compounds such as phenolic compounds [10]. Our study focuses on Salicornia ramosissima and Sarcocornia perennis subspecies alpini, two species widely distributed in European salt marshes, including those along the Portuguese coast. Both have a long history of consumption by coastal communities for seasoning or as substitutes for more conventional vegetables; more recently they have been used as gourmet ingredients in sophisticated salads and dishes. As Salicornia and Sarcocornia are hard to tell apart, their mixed consumption is frequent, since consumers favour Salicornia on account of its more refined flavour and less fibrous texture, whereas, due to its higher yield and year-round availability, producers are partial to Sarcocornia. It is important, however, to assess the differences between these two species, namely in their nutritional and phytochemical composition, as well as in terms of consumption safety, to better understand how these plants can contribute to the mitigation of the problems that the world faces today. Therefore, the present study aims to evaluate the nutritional composition, including the mineral constituents, phenolic profile, and antioxidant potential of Salicornia ramosissima and Sarcocornia perennis alpini from the Mondego estuary (in the central region of Portugal). The levels of contamination by mycotoxins―aflatoxins (AFs) B1, B2, G1, G2, and ochratoxin A (OTA)—and essential and non-essential heavy metals (HMs)—copper (Cu), zinc (Zn), manganese (Mn), cadmium (Cd), lead (Pb), chromium (Cr), nickel (Ni), cobalt (Co), and mercury (Hg)—were also determined. With these contributions, we aim to increase the knowledge about Salicornia and Sarcocornia, particularly concerning their potential as a sustainable solution to mitigate food shortages and improve nutrition and health at a global level, while drawing attention to the importance of not neglecting safety aspects. ## 2.1.1. Proximate Composition The aerial parts of the commonly available but largely underutilised S. ramosissima and S. perennis alpini were analysed for their nutrient composition. The results are presented in Table 1. Moisture content has a major impact on the quality attributes of vegetables. The shoots of both halophytes showed a high moisture content, but S. ramosissima excelled in this parameter (89.7 vs. $87.8\%$ fw). For Salicornia and Sarcocornia, high water content is essential to dilute the high concentration of NaCl present in their tissues and thereby lessen the osmotic pressure, thus allowing them to survive even in extreme saline stress conditions [11]. In a study conducted by Castañeda-Loaiza et al. [ 11], wild and cultivated specimens of Sarcocornia fruticosa were nutritionally characterised, and the cultivated variety exhibited a higher moisture content (see Supplementary Material Table S2), arising from greater water availability. High juiciness is a characteristic that attracts consumers, as it reflects freshness and is associated with a crunchy texture, but it also increases the plants’ susceptibility to both biochemical and microbiological deterioration, for which reason this parameter should be carefully monitored. The 6.61 and $4.28\%$ dw crude protein values exhibited by S. ramosissima and S. perennis alpini, respectively, are relatively close to those previously reported for the same species collected in southern Portugal [12] (see Supplementary Material Tables S1 and S2). Furthermore, in a previous study of ours on the nutritional composition of wild S. ramosissima from a salt marsh in the southern arm of the Mondego estuary [8], the identified protein content was lower (see Supplementary Material Table S1), which suggests that factors such as geographic location, as well as soil and water composition, may greatly affect the chemical composition of the plant, as reported by other authors (e.g., [13]). The wild Salicornia herbacea from southwestern Tunisia exhibits a remarkable protein content, as reported by Essaidi et al. [ 14] (see Supplementary Material Table S1). Although the protein levels that we found in S. ramosissima and S. perennis alpini were modest, these halophytes may still be useful to supplement other sources of protein in human and animal diets. Furthermore, higher protein values can be achieved under optimal growth conditions. By way of example, in the work by Castañeda-Loaiza et al. [ 11], S. fruticosa cultivated in a soilless system under optimised conditions exhibited a protein content higher than that obtained for spontaneous growth specimens (see Supplementary Material Table S2). Likewise, Bertin et al. [ 13] reported a lower protein content for Sarcocornia ambigua from southern Brazil when harvested in its natural habitat, than what was found for the same halophyte when obtained from an experimental crop irrigated with seawater and fertilised with sludge from shrimp production ponds (see Supplementary Material Table S2). Interestingly, Benjamin et al. [ 15] conducted a study in which the protein profile of the halophytes Salicornia brachiata and Suaeda maritima was assessed under different concentrations of NaCl (0, 200, 500 mM), and a coordinated, even if distinct, response to salinity was observed in both halophytes. For example, the exposure of S. brachiata to 200 mM NaCl induced an up-regulation of several proteins linked to photosynthesis, whereas in S. maritima a down-regulation of those proteins was found after addition of 200 and 500 mM NaCl. This is one of the phenomena that may explain the greater salinity tolerance of S. brachiata compared with S. maritima. Also, proteins related to osmotic and oxidative stress, as well as signalling, transcription, and translation processes were shown to be affected by salinity [15]. Altogether, these data reveal that through the optimisation of growth conditions it should be possible to manipulate, at least partially, the nutritional profile, namely the protein content of Salicornia and Sarcocornia spp., in accordance with the intended application, so as to maximise its practical potential. The total lipid content revealed, $1.32\%$ dw in S. ramosissima vs. $1.52\%$ dw in S. perennis alpini, was within the range of total lipid content reported for most species of Salicornia and Sarcocornia of spontaneous growth (see Supplementary Material Tables S1 and S2). In a previous work of ours, the $0.5\%$ dw total lipid levels found for S. ramosissima from the southern arm of the Mondego estuary were considerably lower [8]. Although the values obtained in the present study were moderately low for both halophytes, they remain significant when compared with those reported for several commonly consumed vegetables, which have less than $1.0\%$ dw lipid content [16,17]. In the study by Castañeda-Loaiza et al. [ 11], cultivated S. fruticosa specimens exhibited considerably higher lipid content than wild ones (see Supplementary Material Table S2). The same trend was observed in the study by Bertin et al. [ 13] on S. ambigua (see Supplementary Material Table S2). Membrane proteins, whose functionality is strongly dependent on the lipid microenvironment, are a key factor in plants’ salinity tolerance, therefore changes in the lipid profile in accordance with salt concentrations are plausible [18]. In the study by Tsydendambaev et al. [ 18], the lipid composition of the halophyte Suaeda altissima was evaluated under different salinity levels, and the total membrane lipid content in aerial tissues was twice as high in specimens grown under optimal concentrations of 250 mM NaCl than in those grown at concentrations of 1 or 750 mM NaCl. In all, if plants—whether glycophytes or halophytes—are grown under suboptimal conditions, major changes can occur in the lipid composition of their organs. The calculated total carbohydrate content—$51.3\%$ dw in S. ramosissima and $52.3\%$ dw in S. perennis alpini—was consistent with reports in other studies (see Supplementary Material Tables S1 and S2). In plants, soluble carbohydrates produced through the Calvin cycle function as energy sources and components for the synthesis of other organic metabolites. Additionally, they play a major role as signalling molecules involved in immune response, and as osmoprotectants and antioxidants [19,20]. Environmental stress, specifically salt stress, has a harmful effect on the carbohydrate metabolism of vegetal species, and in the case of halophytes, the accumulation of sugars plays a crucial role in osmotic balance, carbon storage, and free radical scavenging [21], in line with the high content of carbohydrates found. Regarding crude fibre, both halophytes showed important levels, but the S. perennis alpini $15.3\%$ dw outperformed the S. ramosissima $11.2\%$ dw. There is a broad scientific consensus that an adequate intake of dietary fibre offers multiple health benefits, contributing to reduced risk of cardiovascular, metabolic, and digestive diseases through effects such as the lowering of blood pressure and serum cholesterol levels, the improvement of glycaemia and insulin sensitivity, and the regulation of bowel function. Halophytes such as Salicornia and Sarcocornia can thus play an important role in improving health by contributing to an increase of fibre consumption, at present clearly below the desired levels in developed countries [22]. On the other hand, the fibre content may hinder the consumption of the aforementioned halophytes in the fresh form, since—particularly in their natural habitat—they tend to lose juiciness with the ageing process and develop a marked fibrousness, which in excess discourages consumers. However, this problem does not arise in the case of consumption in the powder form. Halophytes in their wild state, being subjected to greater environmental stress, tend to produce more fibre to increase the strength of the stem [13,23,24]. The ash content, that is the total mineral content, was remarkably close to $40\%$ dw for each halophyte. The literature data reveal that the ash levels of Salicornia and Sarcocornia species are much higher than those reported for common vegetables (see Supplementary Material Tables S1 and S2). As Salicornia and Sarcocornia are both obligate halophytes of the accumulator type, they adjust osmotically to soil and water salinity through the accumulation and sequestration of ions in vacuoles, mainly Na and Cl, whilst organic solutes are accumulated in the cytoplasm to avoid deleterious effects on plant metabolism [8,25]. This saline stress tolerance mechanism should explain the high ash content revealed. Regarding the differences between wild and cultivated specimens, it has been observed that Salicornia and Sarcocornia species from cultivation tend to exhibit higher ash content (see Supplementary Material Tables S1 and S2). Overall, S. ramosissima and S. perennis alpini displayed energy values of interest, about 244 and 240 kcal/100 g dw, respectively, and proximal composition suitable for human consumption. ## 2.1.2. Mineral Profile Owing to the high ash content that characterises S. ramosissima and S. perennis alpini, knowledge of the composition of their mineral fractions is of particular interest. Table 2 depicts the mineral profile of the investigated halophytes. The results show that both S. ramosissima and S. perennis alpini accumulate not only Na, but also other minerals of nutritional interest such as Mg, K, and Ca. Specifically, the mineral accumulation pattern observed in S. ramosissima was Na >> Mg > K >> P > Ca, whilst in S. perennis alpini it was Na >> K > Mg >> P > Ca. For the different species of Salicornia and Sarcocornia, Na has been reported as the most abundant mineral, followed by Mg or K, and then Ca and P (see Supplementary Material Tables S1 and S2). One of the factors shown to have a major influence on the mineral profile of accumulator-type halophytes is the salinity level to which they are exposed in their growing environment. By way of illustration, we refer to the work by Ushakova et al. [ 26], in which the effect of the NaCl concentration on the mineral composition of S. europaea was evaluated, and it was found that as the amount of NaCl increased in the substrate, the levels of K, Mg and Ca in the aerial parts of the plant significantly decreased. The same trend was observed in a more recent study on S. ramosissima, carried out by Lima et al. [ 23]. This phenomenon is related to a mechanism of competitive inhibition [8,27]. Other factors identified as having an important influence on the composition of the mineral fraction of these species include the level of irradiation to which they are subjected [26] and the level of nitrogen fertilisation [28]. In this context, through adjustments in growth conditions, it should be possible to obtain an even more advantageous mineral profile. ## 2.2.1. Extraction Yield, Total Phenolic Content (TPC), and Total Flavonoid Content (TFC) The extraction yields for the aerial parts of S. ramosissima and S. perennis alpini were $14.50\%$ and $13.74\%$, respectively. The results of the TPC and TFC analysis are shown in Table 3. Both halophytes had a high content of phenolics, but the S. ramosissima extract exhibited a noteworthy TPC of 67.1 mg GAE (256.2 mg ECE)/g of extract dw compared with the 38.2 mg GAE (146 mg ECE)/g of extract dw of S. perennis alpini. These values are considerably higher than those reported in the literature for the different Salicornia and Sarcocornia species (see Supplementary Material Tables S1 and S2). Analysing the studies by Castañeda-Loaiza et al. [ 11], Bertin et al. [ 13], and Riquelme et al. [ 24], it can be observed that spontaneously growing specimens tend to present TPC values markedly higher than cultivated ones. Furthermore, works such as those by Lima et al. [ 23], Ventura et al. [ 29], and Ventura et al. [ 30] have recounted increases in the phenolic content of Salicornia and Sarcocornia species with their exposure to increasing levels of salinity, up to a maximum level after which they begin to lose the ability to produce these compounds and/or shift their energy resources to other protection mechanisms. In general, exposure to abiotic and biotic stressors tends to lead to higher TPC values [5]. However, it should be borne in mind that a number of additional factors influence the processes of synthesis, accumulation, and degradation of phenolic compounds, such as the composition of the soil and water, the irrigation regime, the level of exposure to ultraviolet radiation, the life stage and part of the plant analysed, as well as the post-harvest conditions [5,31]. Moreover, the analytical strategy adopted, including the power of the selected extraction solvent, may also affect the TPC results [5,32]. Essentially, plant extracts are regarded as of interest when they display a TPC greater than 20 mg GAE/g dw [5]. Considering that the results obtained in our study for S. perennis alpini almost doubled that reference value and those for S. ramosissima more than tripled it, these extracts can be regarded as highly relevant. Furthermore, the TFC values indicated 186 and 99.3 mg ECE/g extract dw for S. ramosissima and S. perennis alpini, respectively, revealing the high significance of these extracts, especially S. ramosissima. By way of example, the values reported in the literature for green tea (Camellia sinensis L.), a plant known for its particular richness in flavonoid compounds, were between 139 and 184 mg ECE/g extract dw [33]. As a general rule, extracts with total flavonoid contents above 100 and 125 mg ECE/g are considered very rich and exceptionally rich [5], respectively, and therefore of high application value in the food, pharmaceutical, and cosmetic industries. ## 2.2.2. Phenolic Profile Since the TPC estimated by the Folin–Ciocalteu assay and the TFC estimated by the aluminium chloride method do not provide a complete overview of the quantity and quality of the different phenolic constituents, the adoption of more advanced analytical techniques―such as chromatographic ones―is crucial to obtain more information about the individual phenolic components. Table 4 describes the phenolic compounds identified by UHPLC-ESI-MS/MS in the extracts of S. ramosissima and S. perennis alpini. The identification was achieved by assessing the elemental composition data determined from mass measurements in negative ionisation mode, in comparison with data available in the literature and those obtained from the available standards. Exceptionally, compound 25 (quercetin) was measured in the positive mode (m/z 274), as described by Andrade et al. [ 39]. Each compound was characterised by its retention time (tr), maximum absorption wavelengths (λmax), structural class, molecular formula, molecular ion, and main MS/MS fragments. A total of 33 compounds were identified in the extracts, belonging to the families of phenolic acids and flavonoids: among the first category were hydroxybenzoic acids (compound 1) and esters of hydroxybenzoic acids with quinic acid (compounds 2 and 11), hydroxycinnamic acids (compounds 4, 10 and 12), hydroxycinnamic acid glycosides (compounds 6 and 8) and esters of hydroxycinnamic acids with quinic acid, also named chlorogenic acids (compounds 3, 5, 7 and 9); in the latter, we refer to flavonols (myricetin, quercetin, kaempferol, and isorhamnetin) and their glycosides (compounds 13, 14, 15, 16, 18, 20, 21 and 22), flavanones (naringenin) and their glycosides (compounds 16, 19 and 33), flavones (luteolin and apigenin) and their glycoside derivates (compounds 18, 23 and 32) and flavanols (B-type proanthocyanidins). Almost all of these compounds were found in both analysed extracts, except for compounds 1, 9, 13, 19, 22, and 30, which were tentatively identified only in the S. ramosissima extract, while compounds 11 and 31 were detected in only in the S. perennis alpini extract. However, considering the content of the main phenolic compounds identified and quantified, some differences were observed in the extracts analysed. From the 33 chemical compounds described in Table 4, 12 polyphenols were confirmed by the commercial standards and were quantified in both S. ramosissima and S. perennis alpini extracts according to the parameters described in Table 5. S. ramosissima extract exhibited a higher total amount of phenolic compounds, which is in agreement with the results obtained by the Folin–Ciocalteu method. Among the extracts analysed, S. ramosissima presented a higher proportion of phenolic acids than flavonoids, whereas in the S. perennis alpini extract flavonoids were the principal polyphenols quantified. The results revealed that p-coumaric acid and chlorogenic acid were the most abundant phenolic acids in both extracts, while the most abundant flavonoids were quercetin and rutin. S. ramosissima extract also contained high amounts of kaempferol when compared with S. perennis alpini extract. Regarding the literature data, we refer, by way of example, to the study conducted in S. fruticosa by Castañeda-Loaiza et al. [ 11], according to which the main compounds detected were chlorogenic acid, catechin hydrate, and 3,4-dihydroxybenzoic acid, the cultivated specimens displaying in a higher content of phenolic compounds than the wild ones. The content of phenolic compounds determined in that study [11] for both cultivated and wild S. fruticosa was generally higher than that obtained in the extract of S. perennis alpini in the present study, although the caffeic acid, p-coumaric acid, rutin, and quercetin levels were substantially lower. As for S. ramosissima, it is worth noting the study by Silva et al. [ 40], which reported myricetin, gallic, ferulic, and protocatechuic acids, and catechin as major phenolics in a sample of this species from the Ria de Aveiro, central Portugal. It should be noted that in the said study [40], the content of the identified phenolic compounds was markedly lower than that obtained in the present research for S. ramosissima from the Mondego estuary. Altogether, it is clear that there is important intra- and inter-species variability within the phenolic profiles of Salicornia and Sarcocornia. All things considered, our results indicate that S. ramosissima and S. perennis alpini have not only important nutritional value but also numerous bioactive compounds, namely of the polyphenol type. These molecules are particularly interesting owing to the beneficial antioxidant properties that have been attributed to them, which are highly relevant for the plant species they are part of as well as for those who consume them. ## 2.2.3. Antioxidant Capacity Antioxidants have been reported to have a major role in the prevention and mitigation of a multitude of pathologies, through their ability to protect organisms from the excessive production of free radicals [5]. Furthermore, in the food and dermo-pharmaceutical industries, there is currently a growing interest in the replacement of synthetic antioxidants by natural ones, as the latter tend to be regarded as safer [5]. In the present work, the antioxidant potential of the halophytic species under study was evaluated by both DPPH radical scavenging activity assay and the ß-carotene bleaching inhibition test, and the results are summarised in Table 6. Note that the combination of different methods for evaluating antioxidant capacity should provide more reliable results than a single method alone, since oxidative stress is produced by the action of several reactive species, which have different reaction mechanisms [5]. In the obtained results, S. ramosissima, which presented the highest content of phenolics and flavonoids, also exhibited the highest antioxidant capacity measured by the DPPH assay, 30.2 mg TE/g extract dw (vs. 11.0 for S. perennis alpini), and by the ß-carotene method with an AAC of almost 1700 (vs. 1403 for S. perennis alpini). Our findings are in line with several research studies that have demonstrated the antioxidant capacity of extracts from different Salicornia and Sarcocornia species, such as those conducted by Barreira et al. [ 12], Essaidi et al. [ 14], Clavel-Coibrié et al. [ 41], and Cho et al. [ 42]. These authors attributed these activities mainly to the content of phenolic acids and flavonoids, which is consistent with our results. However, it should be noted that the global antioxidant capacity in extracts may depend not only on the quantity of these molecules, but also on the variability of their chemical structures, as well as on their synergistic or antagonistic interactions [5,43]. Additionally, the presence of other antioxidant compounds may also influence the total antioxidant capacity of the extracts [5]. ## 2.3.1. Mycotoxins Mycotoxins are a series of secondary metabolites produced by a variety of fungi that grow on plant products, either in the field or during transport, processing, and storage [44]. For spices and seasoning vegetables, there are two groups of mycotoxins of major concern: AFs and OTA [44]. AFs are produced by some Aspergillus species and are considered the most harmful class of mycotoxins [45]. The most important members of this family, i.e., AFB1, AFB2, AFG1, and AFG2, in addition to being hepatotoxic and immunotoxic, have been classified as group I carcinogens by the International Agency for Research on Cancer (IARC) [45,46]. OTA is produced by Aspergillus and Penicillium species and is classified as a probable human carcinogen (group 2B) [45]. Thus, owing to their high toxicity and thermostability, several countries have set limits for the occurrence of these compounds in various foods intended for human or animal consumption, although such limits are yet to be established for halophyte plants [44]. In the present research work, the determination of AFs and OTA levels was carried out in the two target halophytes to assess the risk of contamination, and the results are shown in Table 7. Important levels of contamination by AFB1 were found in S. ramosissima, that is, 5.21 μg/Kg dw, whereas no AF contamination was observed in S. perennis alpini, and no OTA contamination was detected in any sample of either species. The risk of contamination by mycotoxins in halophytes was reported in a previous study of ours, in which samples of different species of Salicornia exhibited levels of total AF contamination greater than 10 µg/Kg [44]. The European Commission, through regulation no. $\frac{1881}{2006}$ and its amendment no. $\frac{165}{2010}$, stipulates maximum levels of AFs allowed in some spices (Capsicum spp., Piper spp., Myristica fragrans, Zingiber officinale, Curcuma longa, and their mixtures) as 5 µg/Kg for AFB1 and 10 µg/Kg for the total AFB1, AFB2, AFG1, and AFG2 [47]. Therefore, we may assume that contamination levels higher than these in halophytes should also represent a threat to public health. To guarantee the safe consumption of halophytes, it is on the one hand utterly crucial that the legislation specifically considers this type of food, while on the other hand producers are duly trained to adopt measures that lessen the contamination risk, including elimination of diseased specimens, avoidance of contact of shoots with the soil, rinsing with potable water, transportation under refrigeration, processing under hygienic conditions, and prevention of prolonged storage, as discussed in more detail in Lopes et al. [ 44]. Furthermore, it will be important to conduct further studies to explain the differences in the levels of contamination in the two halophytes studied, given that both species have the same provenance and were subject to the same processing in identical conditions. One hypothesis is that S. perennis alpini may be less susceptible to contamination by mycotoxigenic fungi because it is a more fibrous species and has a stronger cell wall, which creates an improved barrier against invasion by pathogenic microorganisms. Another aspect that deserves our attention in this context is the relationship between phenolic content and mycotoxin contamination. Phenolics, in particular phenolic acids and flavonoids, have been reported to exhibit important antifungal properties in several plant species and against a wide variety of pathogenic fungi (e.g., [48,49]). Moreover, various studies have shown the ability of these compounds to inhibit the biosynthesis of various mycotoxins, namely AFs (e.g., [50,51,52]). Consistent with this are the findings of the study conducted on rice by Giorni et al. [ 53], in which it was observed that the TPC and phenolic profile varied significantly depending on the level of fungal infestation and the presence of mycotoxins. In particular, the authors of that study reported that the phenolic content tends to be higher in the early stages of plant development and decrease during the growing season; however, when a fungal infestation occurs, the decrease in phenolic levels is less noticeable, attributed to the fact that the plant needs a high content of these compounds to defend itself against the fungal infection [53]. Bearing this in mind, the phenolic content of the halophytes under analysis may have been affected by the level of exposure to mycotoxigenic fungi, particularly in the case of S. ramosissima which was considerably contaminated by AFB1. ## 2.3.2. Essential and Non-Essential Heavy Metals The definition of the term “HM” is still controversial [54,55]. According to Csuros and Csuros [56], HM designates a metal with a density above 5 g/cm3. Ali and Khan [54] proposed a broader definition, in which HMs are considered naturally occurring metallic elements with atomic numbers greater than 20 and elemental densities above 5 g/cm3. This latter definition yields a total of 51 elements to be designated as HMs [54]. By this definition, the term HMs should not necessarily be associated with pollution nor toxicity [54]. Yet, analysing the literature, it is observed that the term HM is often used as a group name for metals and metalloids that have been associated with contamination and (eco)toxicity [57]. Clearly, an unambiguous definition of the term HM is sorely needed, but while such is not available and for the purposes of the present manuscript, the definition of HM based on both atomic number and element density proposed by Ali and Khan [54] is adopted here. HMs can be divided into two main groups: [1] essential and [2] non-essential. The former includes elements of biological relevance, i.e., Fe, Zn, Cu, Mn, and Co, which function as protein cofactors in a wide range of biological processes. These, not being toxic when present in the trace amounts required by the organism, can induce toxicity beyond a certain limit [58,59]. Essential HMs are also commonly referred to as essential trace elements. Non-essential HMs, such as Cd, Pb, and Hg, have no known biological function and are toxic even at lower levels of exposure [58,59]. The latter are considered a particularly worrying category of contaminants owing to their toxic, non-biodegradable and bioaccumulative character [58,60]. While naturally present in the environment in trace concentrations, pollution caused by anthropogenic activities has greatly intensified HMs’ presence in ecosystems, making them a major threat to global health [58,59]. In plants, excessive concentrations of HMs can cause damage through phenomena such as hyper-generation of reactive oxygen species, disruption of enzymatic processes, alteration of membrane permeability, inactivation of photosystems, and disturbance of mineral metabolism [58,61]. In animals, the consequences of the accumulation of HMs have been well studied, with reported effects such as oxidative stress and inflammation (e.g., Pb, Cd, and Ni) [62,63], changes in gene expression (e.g., Pb, Cd, and Mn) [64,65], destruction of the mucosa of the intestinal tract, and changes in the microbiota (e.g., Pb) [66]. Toxicity occurs through processes such as the inhibition of antioxidant enzymes, substitution of native metal ions in enzymes involved in metabolic processes, disruption of protein structures, inhibition of DNA repair, and formation of protein and/or DNA cross-links [60,67]. Hence, consumption of food and water contaminated by HMs can lead to serious neuronal, hepatic, renal, immunological, cardiovascular, reproductive, and gastric damage, as has been recounted in multiple studies [68]. Coastal wetlands are included among the most polluted ecosystems [69]. They are subject to high input of materials from adjacent environments, including HMs from various terrestrial, marine, and atmospheric sources [69]. Activities such as agriculture, aquaculture, sewage discharge, transportation, and oil spills are considered the main causes of HMs deposition in these areas [69]. Upon reaching the salt marshes, these contaminants spread and interact with the local biota community [70]. Halophytes are highly resistant, not only to salinity but also to HMs, and this resistance depends at least partly on common protective mechanisms such as the synthesis of phenolics [71]. The main route of uptake of HMs for most halophytes is through the root system, with subsequent translocation to the aerial parts. In general, most toxic metals tend to accumulate in the roots and do not reach the shoots, which are the more frequently consumed parts of the plant. However, it should be noted that there is great variability in the uptake rate, depending on both the HMs and halophytes involved [71]. The results of the HMs analysis of S. ramosissima and S. perennis alpini samples are summarised in Table 8. Cu, Cd, Pb, and Cr levels did not vary significantly between the two species under study, whilst significant variation was observed for Zn, Mn, Ni, Co, and Hg levels ($p \leq 0.05$). Barreira et al. [ 12] also reported an important variation in the concentration of the different HMs in Salicornia and Sarcocornia species, even when differences in environmental factors were minimal. These differences may be related to factors such as, among others: (i) differences in the life cycle, as S. ramosissima is annual and S. perennis alpini is perennial, and as a consequence, the metabolic requirements for certain macronutrients and micronutrients at the time of harvest may differ; (ii) the presence of root exudates, which can improve the solubility of certain HMs and thus increase their accumulation [72]; and (iii) differences in the microbiome [73]. The order of HM concentrations determined in this study for S. ramosissima was Mn > Zn > Cr > Cu > Co > Ni > Cd > Pb > Hg, whilst that for S. perennis alpini was Mn > Zn > Ni > Cr > Cu > Co > Pb > Cd > Hg. S. ramosissima showed a slightly higher total concentration of the HMs analysed, mainly due to the higher Mn content. In this regard, S. ramosissima was previously identified by Barreira et al. [ 12] as an excellent source of this trace mineral, which has a major role in amino acid, carbohydrate, and lipid metabolism, and bone development, among other functions [74]. By way of example, the consumption of 100 g of S. ramosissima shoots from the Mondego estuary would mean an intake of about 0.7 mg of Mn, and the World Health Organisation recommends a consumption of 2 to 3 mg/day [75]. This capacity for Mn accumulation might pose a health risk if the plant’s growth environment is heavily contaminated with this element, given that it can induce neurotoxicity at excessive levels [74,75]. Moreover, Mn, which until now has gone unnoticed as a contaminant due to its role as a micronutrient and its ubiquity in the environment, has recently gained prominence owing to its presence in ecosystems at increasing levels resulting from human activities [75]. Another important difference between samples was observed in their comparative levels of Ni accumulation, almost twice as high in S. perennis alpini. Note that foods contain on average less than 500 μg/Kg of Ni [76], thus the 1750 μg/Kg determined for S. perennis alpini should be borne in mind, even if it is within reported levels for more conventional vegetables regarded as Ni accumulators [76]. Although the extent of the toxic effects resulting from the consumption of Ni-contaminated food is not yet well established, caution is advised, as it has consistently been shown to play an important role in inducing oxidative stress [76]. In addition, it is important to point out that exposure to Ni is a major cause of contact dermatitis, and for some individuals the allergic reaction can occur even at very low levels of exposure [77]. Therefore, the adoption of protective measures such as the use of gloves is strongly recommended when handling food contaminated by this HM. Likewise, the higher level of Hg accumulation in S. perennis alpini compared with S. ramosissima is also worth mentioning, mainly due to the risk of neurological damage caused by exposure to high concentrations of this element [68]. As a whole, the data indicate that the levels of HMs in S. ramosissima and S. perennis alpini are acceptable. In particular, the content of Cd and Pb are well below the maximum established in the European Union through Regulation no. $\frac{1881}{2006}$ and amendments, Regulation no. $\frac{2021}{1317}$, and Regulation no. $\frac{2021}{1323}$, i.e., 0.2 [78] and 0.3 [79] mg/Kg fw, respectively. The level of Hg detected in S. perennis alpini matches the maximum limit allowed for algae according to Regulation no. $\frac{396}{2005}$, i.e., 0.01 mg/Kg [80]. We emphasise that this regulation defines the maximum levels of pesticide residues allowed in different categories of foodstuffs, and that, owing to the absence of a more specific regulation for halophytes or even for algae, we use this as the basis for discussion, similarly to other authors [81,82]. In this context, it is furthermore important to note that the Mondego estuary is considered a less polluted estuary, due to the limited industrialisation of the area [83,84]. However, with climate change, phenomena such as forest fires have intensified dramatically in Portugal, and a direct relationship has been documented between the mobilisation and accumulation of elements such as Hg, Mn, and Zn in ecosystems and the occurrence of these events [84,85], which could ultimately lead to a greater accumulation of these HMs in the species under study. Finally, as shown in the studies by Yang et al. [ 86] and Sanjosé et al. [ 72], in the case of specimens from highly contaminated areas, the risk of accumulation by HMs at levels that represent a health risk is real and should not be overlooked. Hence, the introduction of specific legislation for halophytes is a fundamental step to guarantee the safety of their consumption. ## 3.1. Sampling Area The Mondego estuary comprises a 16 km2 polyhaline and well-mixed mesotidal system located on the Atlantic coast, that benefits from a temperate climate [87]. It consists of northern (deeper and more hydrodynamic) and southern arms (shallower with extensive intertidal mudflats), separated by an island—Morraceira—the provenance of the samples analysed in this study [88]. This estuarine system supports industrial activities such as fishery, salt production, and aquaculture [87]. In total, it comprises an area of 8452 km2 of salt marshes [88], an important part of which is abandoned land, contributing to its degradation and the alteration of ecological conditions. Thus, the cultivation of halophyte species can be an important rehabilitation strategy for these saline areas, and make an important contribution to the local economy. ## 3.2. Sample Collection and Preparation Specimens of S. ramosissima (Figure 1a) and S. perennis alpini (Figure 1b) were obtained from a small local producer on the aforementioned Morraceira island (Mondego estuary), who collects the specimens that grow in his salt marsh. The identification of the said species was conducted by a taxonomy specialist based on the criteria of Valdés and Castroviejo [89]. The harvest was carried out manually using gloves, during July 2021. July is the time when the first adult Salicornia specimens can be collected, whilst November typically marks the onset of the senescence phase of this species, in other words, the end of its life cycle. Sarcocornia, being an annual species, can be harvested at any time of the year. Traditionally, both species tend to be collected in the spring and summer months, when their consumption is highest. Regarding the harvesting process for this research work, only specimens of identical maturity, regular size, and healthy appearance were selected, those with a less than ideal appearance being rejected. Still at the producer location, the plants were washed with marsh water to remove sediment and other foreign materials. The aerial parts were then separated and placed in hygienised plastic boxes, and the remaining plant material discarded. In order to obtain results comparable with those common in the sector, the aforementioned procedure was identical to the method usually adopted by small producers. Transport between the collection and sample analysis sites took 45 min under ordinary conditions. On arrival at the laboratory, the plant material was carefully washed with deionised water, externally dried with a paper towel and dehydrated or immediately frozen, depending on subsequent analysis. The dried samples were dehydrated at 40 °C ± 5 °C for 35 h in an oven, ground to a granulometry ≤ 1 mm, thoroughly homogenised, and stored at 4 °C in sterile, airtight plastic containers while awaiting chemical analysis. The frozen samples were first milled, homogenised, and then stored at −20 °C in the same type of container. Dried samples were utilised to determine centesimal composition (except moisture), mineral profile, and mycotoxin and HM contamination; frozen samples were employed to evaluate the phenolic composition and antioxidant capacity; and, finally, fresh samples were used only for moisture content analysis. ## 3.3. Chemicals and Reagents Reagents used for proximate composition analysis were Kjeldahl tablets (3.5 g potassium sulphate plus 3.5 mg selenium) from Foss (Höganäs, Sedwen), sulphuric acid (H2SO4) and sodium hydroxide (NaOH) from PanReac AppliChem ITW Reagents (Darmstadt, Germany), methyl red (C15H15N3O2) and saccharose (C12H22O11) from Merck (Darmstadt, Germany), and petroleum ether (C6H14) from VWR Chemicals (Fontenay-sous-Bois, France). For the evaluation of the mineral profile, standard solutions of sodium (Na) at a concentration of 10,000 mg/L, and of potassium (K), calcium (Ca), phosphorous (P), and magnesium (Mg) at concentrations of 1000 mg/L were purchased from Sigma-Aldrich (Madrid, Spain). The calibration curves were prepared with the aforementioned standard stock solutions diluted with ultrapure deionised water obtained using a Milli-Q water purification system from Millipore (Bedford, MA, USA). The measurement of the target minerals was performed on an Architect ci8200 chemical auto-analyser, with an Abbott reagent kit (Chicago, IL, USA). For the total phenolic content and antioxidant capacity assessment, the reagents used were absolute ethanol, Folin & Cioucalteu’s phenol reagent, gallic acid, 2,2-diphenyl-1-picrylhydrazyl (DPPH) (C18H12N5O6), 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (trolox) ($97\%$ purity), linoleic acid (C18H32O2), and polyoxyethylene sorbitan monopalmitate (Tween® 40) (C62H122O26) from Sigma-Aldrich (Steinheim, Germany), sodium carbonate (Na2CO3) and β-carotene from Fluka Chemicals (Sintra, Portugal), and methanol from VWR Chemicals (Fontenay-sous-Bois, France). For determination of the total content of flavonoids, the reagents used were sodium nitrite (NNaO2) and sodium hydroxide (NaOH) both from Merck (Darmstadt, Germany), aluminium chloride (AlCl3) from Fluka Chemicals (Sintra, Portugal), and epicatechin from Sigma-Aldrich (Madrid, Spain). For the identification and quantification of the phenolic compounds, standards of protocatechuic acid, caffeic acid, ferulic acid, p-coumaric acid, rutin, myrecetin, naringenin, luteolin, kaempferol, and apigenin were purchased from Sigma-Aldrich (Madrid, Spain), and the standards of chlorogenic acid and quercetin were provided by Fluka Chemie AG (Buchs, Switzerland). The standard stock solutions of the aforementioned phenolics were each prepared at a concentration of 1000 mg/L using methanol, which was obtained from Merck (Darmstadt, Germany). Regarding the study of the occurrence of mycotoxins, the standards of the AFs, OTA, and zearalanone (ZAN) were supplied by Sigma-Aldrich (Madrid, Spain). The standard stock solutions for AFB1, AFG2, and OTA were prepared via dissolution in methanol, and those for AFB2, AFG1, and ZAN were prepared in acetonitrile. Acetonitrile and methanol were from Merck (Darmstadt, Germany), as well as formic acid (CH2O2) used in the mobile phase. For the determination of the HMs levels, the hydrochloric acid (HCl) ($37\%$, v/v) used for ash dissolution was from Chem-Lab NV (Zedelgem, Belgium) and the standard stock solutions for each target element were from Merck (Darmstadt, Germany), with the exception of iron (Fe) which was purchased from Sigma-Aldrich (Madrid, Spain). ## 3.4.1. Proximate Composition The aerial parts of S. ramosissima and S. perennis alpini were analysed for their nutritional content, following the Association of Official Analytical Chemists (AOAC) procedures [90]. Moisture was determined by measuring the amount of water removed from the fresh samples after direct heating in a forced air circulation oven at 105 °C until a constant weight was achieved (AOAC 934.01). Ash was determined via incineration of the samples in a muffle furnace at 550 °C for 7 h (AOAC 930.05). Total lipids were quantified by the Soxhlet extraction method (AOAC 991.36). Crude fibre was quantified using a F-6P fibre extraction unit (Raypa, Barcelona, Spain) through successive hydrolysis with 100 °C 0.26 N sulphuric acid and 0.32 N sodium hydroxide for 30 min each (AOAC 962.09). Crude protein content was calculated by multiplying the nitrogen (N) value by a conversion factor of 6.25. Nitrogen was quantified via the Kjeldahl procedure (AOAC, 2000.11). Total carbohydrates were obtained by difference. Energy was estimated using the Atwater conversion factors, i.e., carbohydrates: 4.0 kcal/g; proteins: 4.0 kcal/g, and lipids: 9.0 kcal/g. The ash, total lipids, crude fibre, and crude protein contents were expressed as percentages of dry weight (% dw), whilst moisture content was expressed as a percentage of fresh weight (% fw). ## 3.4.2. Mineral Profile The extraction and quantification of minerals from S. ramosissima and S. perennis alpini was performed according to the “green” method by Lopes et al. [ 8]. Briefly, 200 mL of deionised water were added to 6.0 ± 0.5 g of each powdered sample, and the mixtures were placed under sonication in a 35 kHz ultrasound bath for an optimised time of 5 min. Thereafter, the solutions were homogenised and filtered through 0.45 µm nylon membranes. Sample processing was performed on an Architect ci8200 chemical autoanalyser (Abbott Laboratories, Chicago, IL, USA); Na and K concentrations were determined by indirect potentiometry, and those of Ca, Mg, and P by photometry. The results obtained are expressed in milligrams per gram of plant (aerial parts) on a dry weight basis (mg/Kg dw). ## 3.5.1. Extraction Procedure Previously crushed and frozen samples of S. ramosissima and S. perennis alpini were thawed at room temperature (≈23 °C). Thereafter, the extraction procedure was performed following the method described by Robalo et al. [ 91]. Briefly, 5 ± 0.5 g of each sample was transferred to a Falcon tube, and 50 mL of absolute ethanol was added. The tubes containing the mixtures were placed on a shaker at 400 rotations per minute (rpm) at room temperature for 30 min, and then centrifuged at 5000× g at 15 °C for 15 min. Afterwards, the resulting supernatant was collected and transferred to a pyriform flask, and the ethanol evaporated at 35 °C until dry. The extracts were scraped from the flasks and placed in sterile, airtight tubes, and stored at 5 °C until further use. The extracts yield (%) was calculated using Equation [1]:[1]Yield=EmSm×100 Em represents the mass of the obtained extract after solvent evaporation and Sm the mass of the fresh plant sample used for the extraction process. Ethanolic solutions with final concentrations of 5 mg/mL of each extract were prepared in order to evaluate their total content of phenolic compounds and antioxidant capacity. For the study of the detailed phenolic profile of these extracts, methanolic solutions were prepared at a final concentration of 5 mg/mL for each. ## 3.5.2. Total Phenolic Content (TPC) The determination of the TPC was carried out through the Folin–Ciocalteu colourimetric method described by Singleton et al. [ 92]. Thus, 7.5 mL of the Folin–Ciocalteu reagent (1:10, v/v) was added to a 1 mL aliquot of each plant sample extract and the mixtures were then homogenised. After 5 min of incubation, 7.5 mL of an aqueous solution of sodium carbonate (60 mg/mL) was added. Thereafter, the reaction mixtures were vortexed and allowed to stand for colour development in the dark at room temperature for 2 h. After the reaction period, the absorbance was measured at 725 nm. A standard calibration curve was plotted using different concentrations of gallic acid ($y = 7.8057$x + 0.0109; r2 = 0.9986; range: 5–100 µg/mL). The TPC was expressed as milligrams of gallic acid equivalent per gram of extract dry weight (mg GAE/g extract dw). ## 3.5.3. Total Flavonoid Content (TFC) The measurement of the TFC was conducted according to the methodology proposed by Yoo et al. [ 93]. In brief, 1 mL of each plant extract was mixed with 4 mL of ultrapure water and 0.3 mL of an aqueous solution of sodium nitrite ($5\%$, w/v), followed by an incubation period of 5 min and the addition of 0.6 mL of aluminium chloride ($10\%$, w/v). After a further 6 min incubation period, 2 mL of sodium hydroxide (1 M, w/v) and 2.1 mL of ultrapure water were added, and the solution was homogenised. Finally, the absorbance of the reaction mixture was determined at 510 nm. A calibration curve was plotted using different concentrations of epicatechin ($y = 2.0304$x + 0.017; r2 = 0.997; range: 5–200 µg/mL). The TFC results are expressed in milligrams of epicatechin equivalents per gram of extract dry weight (mg ECE/g extract dw). ## 3.5.4. Phenolic Profile The identification and quantification of phenolic compounds in the extracts were conducted using an UHPLC-ESI-PDA-MS/MS (Thermo Fisher Scientific, San José, CA, USA), equipped with an Accela quaternary pump, a degasser, an autosampler, a column oven, and a photodiode array detector (PAD), coupled to a triple quadrupole mass spectrometer TSQ Quantum Access MAX and an electrospray ionisation source (ESI). The instrument control and data collection and processing were performed with Xcalibur 2.1 software (Thermo Fisher Scientific, San José, CA, USA). The phenolic compounds were separated on a reverse phase Kinetex EVO C18 100 Å column (150 × 3 mm, 5 µm particle size) (Phenomenex, Torrance, CA, USA), thermostatically set at 30 °C. The injection volume was 10 μL. The mobile phase was composed of two solvents: water with $0.1\%$ formic acid (solvent A) and methanol with $0.1\%$ formic acid (solvent B). The flow of the mobile phase was set at 0.6 mL/min and the gradient elution method applied was as follows: $95\%$ solvent A; 3 min, $90\%$ solvent A; 10 min, $80\%$ solvent A; 18 min, $70\%$ solvent A; 25 min, $30\%$ solvent A; 33 min, $0\%$ solvent A; 33–40 min, $0\%$ solvent A and $100\%$ solvent B isocratic; and finally, the column was washed and reconditioned with $95\%$ solvent A (40–46 min). PDA spectra acquisition was performed continuously using a full scan modality during the run in the range of 200 to 600 nm. The mass spectrometer electrospray ionisation source was operated in both negative and positive modes, according to the nature of the phenolic compounds. The optimised MS/MS conditions were as follows: electrospray voltage: 2.5 kV; vaporiser and capillary temperatures: 340 °C and 350 °C, respectively; sheath gas pressure: 25 psi, and auxiliary gas pressure: 5 arbitrary units. Nitrogen (purity > $99.98\%$) was used as a sheath gas, ion sweep gas, and auxiliary gas, and argon was the collision gas (1.5 mTorr). After an initial screening in the MS scan range of 100–800 m/z, tentative identification of polyphenols was accomplished by comparing their precursor ions [M]- or [M-H]+ (depending on the phenolic) and mass spectrometry fragmentation patterns (MS/MS) with those previously described in the literature (see Table 4 and Table 5). The MS/MS data acquisition was performed in single reaction monitoring (SRM) mode. The confirmation of individual phenolic compounds’ identity was achieved by comparing the retention times, UV–Vis spectra (λmax), and MS/MS data with those obtained by injecting commercial standards under the same HPLC conditions. Quantification was performed by the external standard method with six-point calibration curves, using the most abundant fragments in SRM mode acquisition. ## DPPH (2,2-Diphenyl-1-Picryl-Hydrazyl) Radical Scavenging Assay The ability of S. ramosissima and S. perennis alpini extracts to scavenge DPPH free radicals was evaluated according to the procedure described by Martins et al. [ 33]. Briefly, 2 mL of a freshly prepared methanolic solution of DPPH (14.2 µg/mL) was added to 50 µL of each ethanolic plant extract solution (5 mg/mL), and the mixture was appropriately homogenised and incubated in the dark at room temperature for 30 min. For the control assays, 50 µL of ethanol and 2 mL of the DPPH solution were used. Afterwards, the absorbance of the resulting solution was measured at 515 nm. A calibration curve was drawn using different concentrations of trolox ($y = 0.6242$x + 0.467; r2 = 0.9984; range: 10–150 µg/mL), and the results were expressed as milligrams of trolox equivalent per gram of extract dry weight (mg TE/g extract dw). ## β-Carotene Bleaching Assay The procedure was carried out as described by Martins et al. [ 33]. First, an emulsion was prepared, in which 1 mL of a solution of β-carotene in chloroform (2 mg/mL) was added to 20 mg of linoleic acid and 200 mg of Tween® 40 in a round-bottomed flask. Then, chloroform was removed in a rotary evaporator at 40 °C. Then, 50 mL of ultrapure water saturated with oxygen was added to the obtained residue and the mixture was repeatedly shaken to form an emulsion. In the second stage of the procedure, 200 µL samples of each plant extract were transferred to test tubes and a 5 mL aliquot of the aforementioned β-carotene emulsion was added to each. For the control assays, 200 µL of ethanol were used instead of the plant extract. Finally, all samples and controls were vortexed and submitted to 50 °C for 2 h in a heating block. The resultant absorbances were measured at 470 nm. For the plant extracts, the measurement was performed after the 2 h heating period, whilst in the case of the control assays it was made both immediately after the addition of the emulsion to the ethanol and after 2 h of incubation. The antioxidant activity coefficient (AAC) was calculated using the following Equation [2]:[2]Antioxidant activity coefficient (AAC)=As2−Ac2Ac0−Ac2×100 As2 is the absorbance of the sample after the 2 h heating period, whilst Ac0 and Ac2 are the absorbances of the controls at time 0 and after 2 h of incubation, respectively. ## Extraction Procedure The extraction of AFs, i.e., AFB1, AFB2, AFG1, AFG2, and OTA, from the samples was carried out according to the method described in our previous work [44]. Briefly, samples of approximately 2 g were weighed into centrifuge tubes and 100 µL of the internal standard ZAN was added from a solution at a concentration of 10 µg/mL. Thereafter, the samples were treated with 10 mL of acetonitrile ($80\%$, v/v) and the tubes containing the mixture were placed on a shaker for 60 min at 110 rpm. Next, a centrifugation step was carried out at 12,669× g for 10 min, and after solid–liquid phase separation the supernatant layer was transferred to new tubes. Note that the extraction, centrifugation, and supernatant layer collection procedures were repeated, and all resulting supernatants were combined at the end of the process. Finally, an 8 mL aliquot of the obtained extract was evaporated, the residue redissolved in 1 mL acetonitrile ($40\%$, v/v), and the solution filtered through 0.2 µm PVDF mini-uniprep filters prior to chromatographic analysis. ## Ultra-High Performance Liquid Chromatography Coupled with Time-of-Flight Mass Spectrometry (UHPLC-ToF-MS) Analysis An ultra-high performance liquid chromatograph (UHPLC) Nexera X2 (Shimadzu, Kyoto, Japan) coupled with a time-of-flight mass spectrometer (ToF-MS) AB Sciex triple TOFTM 5600+ (Sciex, Foster City, CA, USA) was used for the separation and quantification of AFs and OTA. The aforementioned mycotoxins were run through a gradient on a Zorbax Eclipse Plus C18 column (2.1 × 50 mm, 1.8 µm particle size) from Agilent (Santa Clara, SA). The mobile phase system consisted of $0.1\%$ formic acid in water (solvent A) and acetonitrile (solvent B). The optimised gradient elution procedure was as follows: 0–12 min, $10\%$ solvent B; 12–13 min, 10–$90\%$ solvent B; 13–14 min, $90\%$ solvent B; 14–15 min, 90–$10\%$ solvent B; 17–17 min, $10\%$ solvent B. The injection volume was 20 µL, the flow rate was fixed at 0.5 mL/min, and the column temperature was maintained constant at 30 °C. The quantitative analysis was conducted by the peak area method, and the monitored ions were the protonated molecule [M + H]+ at m/z 313.07066 for AFB1, 315.08631 for AFB2, 329.06558 for AFG1, 331.08123 for AFG2, and 321.1696 for ZAN. The system was operated in the positive ion electrospray mode, and the MS parameters were set as follows: ion spray voltage: 5500 V; temperature: 575 °C; declustering potential: 100 V; curtain gas: 30 psig; nebuliser gas (gas 1) and heater gas (gas 2): 55 psig; mass range: 100–750 Da. Note that the method described was validated for linearity, limit of detection (LOD), limit of quantification (LOQ), accuracy and precision, and meets the requirements established by regulation (EC) no. $\frac{401}{2006}$ [94]; for more details on the validation of the analytical method please refer to Lopes et al. [ 44]. The results obtained regarding the occurrence of AFB1, AFB2, AFG1, AFG2, and OTA were expressed in micrograms per kilogram of dried plant (aerial parts) (μg/Kg dp). ## 3.6.2. Essential and Non-Essential Heavy Metals Iron was determined according to the same methodology used for Ca, Mg, and P (see Section 3.4.2 Mineral Profile). Cu, Zn, Mn, Cr, Ni, and Co were determined by flame atomic absorption spectrometry (FAAS), while Cd and Pb were quantified by graphite furnace atomic absorption spectrometry (GFAAS). The equipment used for this analysis was a PinAAcle 900T spectrophotometer (Perkin Elmer Inc., Waltham, MA, USA). Hg levels were determined using an AMA254 mercury analyser (LECO instruments Ltd., St Joseph, MI, USA). The LODs were Fe: 0.0512; Cu: 0.022; Zn: 0.005; Mn: 0.016; Cd: 0.010; Pb: 0.154; Cr: 0.022; Ni: 0.039; Co: 0.035; and Hg: 0.001 mg/L. The LOQs were Fe: 0.155; Cu: 0.068; Zn: 0.017; Mn: 0.048; Cd: 0.031; Pb: 0.469; Cr: 0.067; Ni: 0.117; Co: 0.107; and Hg: 0.005 mg/L. Note that for the determination of Cu, Zn, Mn, Cd, Pb, Cr, Ni, Co, and Hg the dry mineralisation method was used, in which approximately 1 g of each dehydrated and ground sample was incinerated in a muffle furnace and the obtained residues were dissolved in 5 mL of HCl ($20\%$, v/v). Thereafter, the plant extract stock solutions were prepared by filtering into 50 mL volumetric flasks and adjusting the volume with deionised water. Finally, the target elements were measured in the obtained extract solutions. Calibration standard solutions were prepared from 1000 mg/L single element standard stock solutions by suitable dilution with deionised water. The obtained results were expressed in milligrams of element per kilogram of plant (aerial parts) on a dry weight basis (mg/Kg dw). ## 3.7. Statistical Analysis The results were analysed by Student’s t-test to determine differences between S. ramosissima and S. perennis alpini, with $p \leq 0.05$ considered a significant difference. This statistical treatment was conducted with SPSS 26.0 statistical package for Windows (SPSS Inc., Chicago, IL, USA). ## 4. Conclusions Both S. ramosissima and S. perennis alpini prove to be valuable sources of nutrients—in particular minerals and fibre—and bioactive compounds—i.e., phenolic acids and flavonoids—which makes these halophytes highly eligible for application in the agro-food and pharmaceutical industries. In particular, S. ramosissima is remarkable for its phenolic richness and antioxidant potential, and can be used directly as a functional food or ingredient, or as extract, or even as a source of isolated/individual phenolic compounds. These can be applied as natural additives and components of bioactive packaging, thus taking advantage of their antioxidant potential, hence providing innovative and healthier products for consumers while contributing to the reduction of food waste by extending the shelf life of other food products. Furthermore, the development of new cosmeceuticals, nutraceuticals, and pharmacological agents could be an interesting field of application for these halophytes. From another point of view, since both Salicornia and Sarcocornia can be cultivated in very hostile environments, by exploiting marginal resources such as saline soils and brackish water, their cultivation presents a key strategy to improve nutrition globally, while—particularly in more arid regions—simultaneously providing an improvement in the economic well-being of the population. Meanwhile, food safety, nutrition, and food security are strongly interconnected, and controlling the presence of contaminants, namely mycotoxins and HMs, is essential to ensure the protection of the health and safety of consumers. One of the greatest dilemmas of this century by far is meeting food security needs while preserving global sustainability, a challenge in which the cultivation of halophytes can undoubtedly play a major role, but for all this potential to really bear fruit, it is essential that adequate cultivation strategies be implemented, preferably in controlled environments. 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--- title: 'Angiotensin II Receptor Blockers Reduce Tau/Aß42 Ratio: A Cerebrospinal Fluid Biomarkers’ Case-Control Study' authors: - Gemma García-Lluch - Carmen Peña-Bautista - Lucrecia Moreno Royo - Miguel Baquero - Antonio José Cañada-Martínez - Consuelo Cháfer-Pericás journal: Pharmaceutics year: 2023 pmcid: PMC10059654 doi: 10.3390/pharmaceutics15030924 license: CC BY 4.0 --- # Angiotensin II Receptor Blockers Reduce Tau/Aß42 Ratio: A Cerebrospinal Fluid Biomarkers’ Case-Control Study ## Abstract [1] Background: The role of antihypertensives in Alzheimer’s Disease (AD) prevention is controversial. This case-control study aims to assess whether antihypertensive medication has a protective role by studying its association with amyloid and tau abnormal levels. Furthermore, it suggests a holistic view of the involved pathways between renin-angiotensin drugs and the tau/amyloidß42 ratio (tau/Aß42 ratio); [2] Methods: The medical records of the participant patients were reviewed, with a focus on prescribed antihypertensive drugs and clinical variables, such as arterial blood pressure. The Anatomical Therapeutic Chemical classification was used to classify each drug. The patients were divided into two groups: patients with AD diagnosis (cases) and cognitively healthy patients (control); [3] Results: Age and high systolic blood pressure are associated with a higher risk of developing AD. In addition, combinations of angiotensin II receptor blockers are associated with a $30\%$ lower t-tau/Aß42 ratio than plain angiotensin-converting enzyme inhibitor consumption; [4] Conclusions: Angiotensin II receptor blockers may play a potential role in neuroprotection and AD prevention. Likewise, several mechanisms, such as the PI3K/Akt/GSK3ß or the ACE1/AngII/AT1R axis, may link cardiovascular pathologies and AD presence, making its modulation a pivotal point in AD prevention. The present work highlights the central pathways in which antihypertensives may affect the presence of pathological amyloid and tau hyperphosphorylation. ## 1. Introduction Alzheimer’s Disease (AD) is associated with alterations in the amyloid beta peptide (Aß) and tau proteins, as well as changes in cholinergic function [1,2,3]. The main AD cerebrospinal fluid (CSF) biomarkers are amyloid -ß42- (Aß42), total tau (t-tau), hyperphosphorylated tau (p-tau), and the tau/Aß42 ratio [4]. First, CSF Aß42 levels decrease in the development of the disease [5], which represents a reduced clearance from the brain into the blood, resulting in a higher accumulation of Aß plaques in the brain [6]. Second, the tau protein stabilizes microtubules in normal conditions as a compensatory mechanism against oxidative stress and Aß toxicity, and GSK3ß regulates its phosphorylation [7]. Elevated CSF tau levels are associated with neurodegeneration and are statistically associated with the progression from mild cognitive impairment to AD, and p-tau elevation reflects the formation of neurofibrillary tangles in the brain [8]. Since AD has a long asymptomatic period, risk factors such as hypertension are involved in its progression [1,9,10]. Hypertension is associated with a doubling in the likelihood of developing AD [2,9,11,12], and this risk increases if hypertension persists over the years [13]. In addition, hypertension causes oxidative stress and endothelial dysfunction, leading to blood vessel atrophy, which becomes particularly important with aging and is associated with cognitive impairment and increased Aß deposition in the brain [12]. Antihypertensives are of interest in dementia prevention due to their cerebrovascular structure protection and other mechanisms besides blood pressure control [13,14,15,16]. Nevertheless, not all antihypertensives have the same influence on AD, as their mechanisms of action differ. Antiadrenergic agents, such as the α-1-adrenoceptor antagonists, decrease peripheric vascular resistance [17] and are associated with (Aß) modulation [15,18]. On the other hand, diuretics may minimize cerebrovascular events and act on Aß peptides [15]. Vasodilator drugs enhance nitric oxide (NO), the role of which in AD is controversial [19]. Otherwise, diosmin stands out among the vascular vasoprotective agents because it reduces Aß and p-tau formation in mouse models [20], and ß-blockers may have the same effect on AD hallmarks [15]. Finally, calcium channel blockers (CCB) are highlighted due to their neuroprotective properties [15,21,22,23,24] and, along with the renin-angiotensin system (RAS)-acting agents, they both appear to be the most effective option in AD risk modulation [16]. In this sense, the angiotensin-converting enzyme inhibitors (ACEi) and the angiotensin II receptor blockers (ARBs) stand out as the main drugs acting on the RAS system. They both are associated with AD risk reduction, but their mechanisms of action differ. While the ACEi prevent the inactivation of bradykinin and the formation of Angiotensin II (1–8), affecting AT1R and AT2R [25,26], ARBs are AT1 receptor antagonists, and, therefore, they enhance AT2, Ang IV, and Ang (1–7) receptors [3,25,26,27,28,29]. For all the above, the present study aims to evaluate the associations between antihypertensive treatments and AD CSF biomarkers. ## 2.1. Participants and Study Design The present work is a retrospective case-control study conducted at the Neurology Unit of the University and Polytechnic Hospital La Fe (Valencia, Spain). The Ethics Committee for Biomedical Research at CEU Cardenal Herrera University and the Medicaments Research Ethics Committee at the Health Research Institute Hospital La Fe have approved this study (CEI$\frac{21}{052}$ and 202-705-1). The participants were recruited through a medical interview between January 2017 and December 2020. The enrolled patients received information and signed the informed consent, following the Declaration of Helsinki, the Good Clinical Practices, and local regulations. The inclusion criteria for this study were to be between 50 and 80 years old, sign the informed consent, and have medical records of CFS biomarkers (Aβ42, t-tau, p-tau), neuropsychological evaluation, and medication intake. The exclusion criteria for the present study were not to meet the inclusion criteria, be enrolled in a clinical trial, have other neurological diseases such as epilepsy, multiple sclerosis, or brain damage, or have psychiatric disorders, such as depression (major disorder) or bipolar disorder. In addition, patients with severe dementia or previous disabilities were excluded. The patients’ diagnoses were based on The National Institute on Aging-Alzheimer’s Association clinical criteria [30]. Therefore, a neuropsychological evaluation based on the Clinical Dementia Rating (CDR) [31], the Repeatable Battery for the Assessment of Neuropsychological Status-Delayed Memory (RBANS.DM) [32], the Mini-Mental State Examination (MMSE) [33], the Functionality Assessment Questionnaire (FAQ) [34], and the AD Cooperative Study ADL Scale for Mild Cognitive Impairment (SDCS-ADL-MCI) [35] were performed. In addition, neuroimaging and CFS biomarkers (ß42, t-tau, p-tau, tau/Aß42 ratio) were assessed. Patients were "and tau/Aß42 ratio were found. Neuropsychological evaluation was considered to optimize a patient’s diagnosis and establish a patient’s cognitive decline stage. Patients with normal CSF levels and who were cognitively healthy were classified as control participants. All efforts were made to include a biologically defined control group (CSF biomarkers) in the study. ## 2.2. Data Source and Variables The patients were anonymized, and the electronic health system was used to perform an exhaustive review of their medical records at the Polytechnic University Hospital La Fe (Valencia). Thus, age, sex, smoking history, and comorbidities such as hypertension were registered. Furthermore, total and high-density lipoprotein (HDL) cholesterol, as well as blood pressure levels, were calculated from the average of two or more measurements, preferably within six months before or after diagnosis. Those variables were gathered at the participant’s hospital and related healthcare centers. CSF samples were obtained as part of the diagnosis protocol at the Polytechnic University Hospital La Fe (Valencia). From 5 to 10 mL of CSF was collected and stored at −80 °C until analysis. Biochemical determinations (Aβ42, t-tau, p-tau) were carried out by a chemiluminescence immunoassay [36]. Specifically, the CSF biomarker cut-off established for t-tau/Aß42 was >0.51 and was >485, >56, and <725 pg/mL for t-tau, p-tau, and Aß42, respectively [37]. An antihypertensive treatment prescription was acquired by a medical history review, and it was registered by Yes/No using the Anatomical Therapeutical Chemical (ATC) code of the WHO Collaborating Centre for Drug Statistics Methodology (WHO) “https://www.whocc.no/atc_ddd_index/ (accessed on 1 May 2021)”. ATCs were firstly regrouped and analyzed by therapeutic subgroup (2nd ATC level) and, secondly, by introducing agents acting on the RAS as their pharmacological subgroup (3rd level). As for the C02 ATC group, only doxazosin was found. Thus, for greater clarity, reference to this group will be made directly to this active ingredient. The same situation was performed with vasoprotective medication, with calcium dobesilate as the representative drug. Finally, the duration of treatment was represented in months. ## 2.3. Statistical Analysis The data were summarized using the median (1st and 3rd quartiles) for the numeric variables and the absolute frequency (%) for the qualitative variables. The biomarkers were log-transformed to avoid skewed data. On the one hand, logistic regression models were performed to assess the relationship between clinical classification attending to CSF biomarkers (AD group, control group) and age, gender, and systolic and diastolic blood pressure. In addition, 2-way interactions with systolic blood pressure (SBP), X “antihypertensives”, diastolic blood pressure (DBP) X “antihypertensives”, and hypertension X “antihypertensives” were explored. Finally, conditional effects with their $95\%$ CI were depicted. On the other hand, elastic net linear regression models were adjusted for each biomarker (ß42 amyloid, t-tau, p-tau, and t-tau/ß42 ratio) to select their associated characteristics. The general model included the following variables: age, sex, SBP, DBP, diabetes mellitus type 2, total cholesterol, smoking habit, number of chronic treatments, and antihypertensive drugs intake (doxazosin, diuretics, peripheral vasodilators, calcium dobesilate, beta-blocking agents, calcium channel blockers, plain ACEI, combinations of ACEi, plain ARBs, and combinations of ARBs). The elastic net regularization method of the estimated beta coefficients improves upon ordinary least squares. It linearly combines the L1 and L2 penalties of the lasso and ridge methods. The regularization parameter λ determines the amount of regularization. An optimal value for λ was determined by performing a 10-fold cross-validation, which yielded the minimum cross-validated mean-squared error (CVM). A median of 1000 repetitions of the cross-validation was calculated to improve lambda’s robustness. The ARBs and ACEi and their relation to t-tau/ß42 amyloid were analyzed by multivariable logistic regression. Multiple comparisons were performed to assess the differences in the before-mentioned groups. The goodness of fit for the adjusted model was carried out using simulated scale residual diagnostics. All the statistical analyses were performed using R (V. 4.0.3.) and the packages glmnet (V.4.1-3), click (V.0.8.0), ggeffects (V.1.1.1), ggplot2 (V.3.3.5), and DHARMa (V. 0,4.4). ## 3.1. Participants Seven hundred and forty-six participants were enrolled in the present study. From these, duplicated records due to follow-up ($$n = 31$$), patients without CSF biomarkers ($$n = 143$$), those diagnosed with other dementias (non-AD), or those with moderate or severe dementia due to AD ($$n = 273$$) were not included. Finally, the patients without medical records of total cholesterol levels or blood pressure ($$n = 17$$) or with the simultaneous prescription of ARBs or ACEi ($$n = 2$$) were excluded (see Figure 1). From the initial cohort, 280 patients were included. They were classified as AD and cognitively healthy patients, according to their CSF levels. Thus, 57 participants were considered cognitively healthy patients (controls) and 223 were considered AD patients (cases), of whom 160 patients ($71.75\%$) had mild cognitive impairment due to AD and 63 patients ($28.25\%$) had mild dementia due to AD. ## 3.2. Demographic and Clinical Data of Participants Table 1 shows the demographic and clinical variables for each group of participants. As can be seen, the AD patients were older than the controls, were predominantly female, and had more chronic concomitant medications prescribed. Regarding cardiovascular risk factors, the patients with AD were predominantly non-smokers and had lower total cholesterol levels. In contrast, they had a greater rate of lipid-modifying prescription, SBP levels, and hypertension than the control patients. However, the control patients were more prone to taking antidiabetic drugs and having higher DBP than the case group (Table 1). ## 3.3. Hypertension and Alzheimer’s Disease Multivariate logistic regression was performed. In addition, age, gender, and blood pressure levels were analyzed and compared to the presence of AD. SBP and antihypertensive prescription statistical interaction were explored without significant differences. Thus, the [SBP x antihypertensive intake] interaction was removed. A positive association was found between the likelihood of suffering from AD and age (OR = 1.174, IC$95\%$ [1.105; 1.255], p-value < 0.001) and higher SBP (OR = 1.036, IC$95\%$ [1.004; 1.071], p-value = 0.033). On the contrary, men seemed less likely to develop AD than women despite the result being non-significant (OR = 0.513, IC$95\%$ [0.246; 1.051], p-value = 0.07). No differences were found regarding diastolic blood pressure and antihypertensive intake (see Table S1 of Supplementary Information). ## 3.4. Antihypertensive Drugs and Alzheimer’s Disease Biomarkers Each therapeutic subgroup prescription was examined to assess whether antihypertensive drugs are associated with AD (Table 2). As can be seen, the AD patients were older when the first antihypertensive drug was prescribed and took the medication for more years. In addition, ß -blocking agents and CCB were consumed more among the AD patients, whereas diuretics and agents acting on RAS were the most common drugs among the control patients. Moreover, all the models associated older age with impaired CFS biomarkers levels (Table 3). Additionally, a trend was observed between antidiabetic consumption and higher Aß42 and lower t-tau/Aß42, whereas being male seemed to be linked to lower t-tau levels. CCB seemed to be associated with a higher t-tau/ß42 amyloid ratio. Finally, plain ACEi drugs were associated with higher t-tau and t-tau/ß42 amyloid levels, whereas combinations of ARBs were related to lower levels of this biomarker. ## 3.5. ACEi and ARBs Pharmacological Subgroups Since ARBs and ACEi showed opposite t-tau/Aß42 ratio effects (Table 3), a deeper analysis was performed (Table 4). As a result, it was observed that a significant proportion of the patients with AD were taking ACEi, whereas ARBs were the most consumed drugs among the control patients. Moreover, almost all the control patients were taking plain ACEi. Firstly, it was observed that the consumption of ARBs was significantly associated with a lower t-tau/Aß42 ratio when compared to ACEi (see Figure 2). Secondly, multivariable logistic regression was performed to confirm the abovementioned results and predict the t-tau/Aß42 ratio association with ARBs and ACEi (see Table S2). The model included sex and age as covariables because they seemed to be the variables with the strongest association with AD. It was observed that combinations of ARBs consumption were associated with a $30\%$ lower t-tau/Aß42 ratio than plain ACEi consumption (estimate = −0.334, IC$95\%$, [−0.613, −0.055], p-value = 0.019). Thirdly, statistical differences in the t-tau/Aß42 ratio between patients taking combinations of ARBs and patients consuming plain ACEi were observed (estimate = −0.5242, IC$95\%$ (−0.1984; −2.643), p-value = 0.026), as well as between patients taking combinations of ARBs and those not taking plain ACEi or combinations of ARBs (estimate = −0.3339, IC$95\%$ (0.1418; −2.354), p-value = 0.0485) (Figure 3). ## 4. Discussion The present study compares the differences between the different antihypertensive treatments and the alteration of fluid biomarkers for AD. Previous studies point out that antihypertensive medication is associated with AD risk reduction, but they are mainly based on cognitive test evolution or dementia diagnosis conversion [22,38,39]. In order to follow a standardized biological criterion, CSF biomarkers were used in AD diagnosis. To our knowledge, this is one of the few antihypertensive studies in AD that defines case and control groups based on CSF biomarker levels. For instance, a clinical trial performed in 2012 about ACEi modulation of ACEs activity in CSF included fourteen volunteers [40]. Moreover, the study of Hestad and co-workers included eight patients with subjective memory complaints as a control group out of 72 subjects [8]. Finally, Nation et al. performed a study of antihypertensives based on CSF AD biomarkers in 2016, but it just included 124 patients [41]. This study shows that high SBP and AD are associated, which is consistent with the recent findings of Hestad et al. who found an association between SBP and CSF t-tau concentrations with lower delayed memory [8,41]. In addition, Affleck and co-workers showed in 2020 that the amyloid brain burden was lower in normotensive AD patients than in hypertense AD patients [2]. Hypertension seems to be associated with an increase in ß-secretase, the enzyme responsible for activating the amyloidogenic pathway of Aß production, and an increase in the Aß42/Aß40 ratio [12]. In addition, several studies affirm that the association between SBP and dementia is significant in midlife but not later life [13]. Altogether, it seems that vascular damage is associated with AD. Due to the long period that elapses from when the pathological pathways begin to be altered until the first symptoms appear, it is possible in middle age when this factor becomes especially important. Furthermore, this study compares the association between antihypertensive use and abnormal AD CSF biomarkers. A previous study performed by Affleck and co-workers in 2020 revealed that patients who take this medication have lower neurofibrillary tangle formation [2]. Nevertheless, when Hestad et al. compared antihypertensive consumption and cognitive functions, they showed worse cognitive function in the antihypertensive consumption group [8]. We did not observe AD diagnosis or CSF biomarker differences in our group compared to antihypertensive consumption per se. Nevertheless, it was observed that the AD patients received their first antihypertensive drug at an older age and for more years in our cohort than the control patients. Therefore, antihypertensives may not avoid AD development, but they may affect mild cognitive impairment or progression by minimizing vascular damage at the early stages and through mechanisms other than blood pressure control [16]. As a result, each antihypertensive class was analyzed separately and compared in four AD-biomarker models. First, doxazosin prescription was associated with higher CSF Aß42 concentrations and lower t-tau and a lower tau/Aß42 ratio. In addition, despite scarce literature about doxazosin and AD biomarkers, a recent study showed that doxazosin prevented Akt reduction, avoiding tau phosphorylation in an in vitro model of organotypic hippocampal cultures exposed to Aß [18]. However, our results must be taken carefully due to the reduced number of patients taking this drug in our cohort. Regarding vasoprotective medication, calcium dobesilate releases NO, producing vasodilation [42,43]. The role of NO with biomarkers is controversial since it is involved in GSK-3ß activation and the consequent tau phosphorylation [19], as well as with Akt and cyclic-AMP-response-element-binding protein (CREB), which promotes cell survival and neuroprotection [44]. Recent studies indicate that an NO neuroprotective or neurotoxic effect depends on its concentration. It modulates heme-metals-Aß binding and plays a key role in Aß toxic effects [45]. In our cohort, calcium dobesilate seemed to be associated with higher CSF amyloid concentrations and a lower tau/Aß42 ratio. Nevertheless, only one patient was taking this antihypertensive in our sample, so further studies are needed to obtain conclusions. As for beta-blocking agents, we did not observe any statistical difference between their consumption and AD hallmark alteration, which is consistent with previously published research [16] In other matters, CCB highlights promising results in dementia prevention [15,22,23,24]. Intracellular calcium is elevated in elderly patients and plays a part in neurodegeneration, amyloid production enhancement, and tau hyperphosphorylation [15,16,23,46]. Thus, CCB may downregulate intracellular calcium levels and slow amyloid production [16,23]. In addition, CCB can enhance cerebral vascularization [15] and, in the case of nimodipine, can act as a cerebral vasodilator [46]. Among CCB, the dihydropyridine compounds stand out with promising results in Aß42 clearance [21,23]. Nevertheless, as shown in the work of Bachmeier et al., not all the dihydropyridines have the same effect on brain vasculature, and their effect on Aß42 clearance may not depend on blood–brain barrier (BBB) penetration. Whereas drugs such as nimodipine or nitrendipine are likely to enhance Aß clearance from the blood to the brain; others, such as amlodipine or nifedipine, do not seem to facilitate Aß42 transcytosis across the BBB in in vivo models, despite the fact that all of them can cross the BBB [21]. When we analyzed our cohort, we noticed that CCB was associated with a higher tau/Aß42 ratio and that the most CCB consumed was amlodipine. Moreover, just one patient took nimodipine when the lumbar puncture was performed. A recent study by Sadleir Id and colleagues aimed to explore whether nimodipine could modify amyloid pathogenesis when it begins in mouse models, but it did not show any changes in the Aß42 or total Aß levels nor amyloid plaque deposition [46]. In addition, it was shown in work performed by Murray and colleagues in 2002 that CCBs were not associated with dementia prevention. Most of the prescribed dihydropyridines in our study were the same that did not boost Aß42 clearance in a study performed by Bachmeier and colleagues in 2011 [21,39]. Moreover, in the Baltimore Longitudinal Study of Aging, CCB did not reduce the incidence risk of AD [47], an effect that was neither observed in the Gingko Evaluation of Memory Study [48] nor the NIVALD study, the phase III clinical trial that tested nivaldipine vs. placebo in AD patients [49]. Altogether, it could explain why we did not observe a protective effect in our sample, although further studies are needed to elucidate the exact mechanism by which amlodipine may increase the tau/Aß42 ratio. Lastly, RAS drugs stand out among the antihypertensive drugs thanks to their potential ability to limit Aß plaques [14] and neurofibrillary tangle formation [2,14]. There is evidence of a dysregulation of endogenous RAS activity in AD patients, which has been confirmed in post-mortem brain tissue [14,27]. As recently reviewed by Gouveia and colleagues, ARBs and ACEi may be more effective at preventing AD than other antihypertensives [14,16,24,29]. Nevertheless, the bibliography suggests that certain ACEi are associated with the risk of dementia [12], whereas ARBs may act as neuroprotectors [16,29]. As a result, studying the effects of both drugs and their influence on CSF AD biomarkers is of interest. The ACEi mechanism of action prevents the formation of Angiotensin II (1–8) and the degradation of plasma bradykinin through ACE inhibition, thus, contributing to inflammation, vascular and blood–brain barrier permeability, and impaired cerebral flow [50,51,52,53,54]. Moreover, ACE1 degrades Aß-42 into Aß40, its soluble form [3,55], and studies show that ACEi can modify ACEs activity in CSF [40]. As a result, if ACE becomes blocked by ACEi, the clearance of Aß42 may not succeed, and plaques may accumulate in the brain [41]. Conversely, ACE inhibition may enhance the bradykinin concentrations in plasma and B1R and B2R activity in microglial cells [56]. B2R expresses constitutively under normal conditions, is activated in acute inflammation [51,53,57,58,59], and has a higher affinity for bradykinin and Lys-bradykinin peptides [53,58]. However, B1R is upregulated by chronic inflammation [53,58,60] and has a higher affinity for Lys-des-Arg9-BK and des-Arg9-BK [50,51,53,57,58,61]. Moreover, the B1R-derived pro-inflammatory cytokine release may contribute to BBB permeability and its disruption [58], being an essential pathophysiological mediator of cerebrovascular dysfunction, neuroinflammation, and Aß pathology in AD [62]. Furthermore, higher bradykinin levels are linked to Aß deposition, and its presence may enhance B1R, accentuating amyloid toxicity. In addition, the Aß42-amyloid peptide can induce the plasma contact system and activate the kallikrein-kinin system (KKS) because of its negative charge [51,52,56]. As a result, an increase in bradykinin production takes place, enhancing cerebral inflammation and vascular permeability [50,51,52,53,54] and up-regulating bradykinin receptors again (Figure 4). On the contrary, there is evidence that ARBs reduce the Aß burden in mice models and can reduce p-tau and neurofibrillary tangles in the hippocampus [29]. Their neuroprotector effect is attributed, in part, to AT1R blockade while stimulating AT2R, AT4R, and MasR [63]. AT1R can release aldosterone and cause vasoconstriction, fluid retention, and the M1 phenotype of microglial cell activation, which releases pro-inflammatory cytokines [29,63]. In addition, AT1R is related to hypertension, heart dysfunction, brain ischemia, abnormal stress responses, BBB breakdown, and inflammation [64]. Thus, the AT1R/Ang II axis links to pro-inflammatory and prooxidant effects, increasing BBB permeability [3,29], as well as cognitive impairment and tau hyperphosphorylation through the activation of GSK3ß [14], which has an essential role in the modulation of insulin [7]. Moreover, microglial activation is higher in elderly patients, and Aß pathogenesis may exacerbate this process [3]. Conversely, AT2R causes angiogenesis, an NO increase, vasodilation, and the activation of the M2 phenotype of microglial cells, thereby releasing anti-inflammatory cytokines [29,63]. MasR produces anti-inflammatory, anti-oxidative, anti-fibrotic, vasodilation, and M2 activation effects [27,63], improving memory, learning, and long-period potentiation in mouse models [27]. Finally, insulin-regulated aminopeptidase is associated with vasodilation and long-term potentiation enhancement [3,28]. Interestingly, AT1R is expressed more in the brain than AT2R [29]. As a result, drugs acting as AT1R antagonists may promote AT2R, MasR, and insulin-regulated activation, which may become significant in cognitive abilities. Other described mechanisms of action by which ARBs may have a protector role in AD are neuronal differentiation, DNA repair, the modulation of the cerebral microvasculature, the reversion of oxidative stress and inflammation, and ischemic brain injury prevention [41]. This work shows a positive association between the tau/Aß42 ratio and the use of ACEi, with an opposite effect when compared to using ARBs in combination (Figure 4). These findings are broadly consistent with slower Aß [28,65] and tau progression when ARBs are consumed instead of ACEi. The previously described mechanisms may explain why we observed a higher t-tau/Aß42 ratio in patients taking ACEi and its contrary effect in patients taking ARBs. Compared to published work, metanalysis shows similar results in dementia risk prevention with ARBs consumption, whereas ACEi does not seem to reduce the risk of dementia [16,25] or reduce its risk less than ARBs [26]. In addition, the longitudinal study by Nation et el. in 2016 showed higher CSF Aß42 levels and lower p-tau levels over time when ARBs treated patients were compared to patients not taking antihypertensives. This study showed that Aß42 reduction was independent of age, the most influential risk factor of AD [41]. Finally, a metanalysis performed by D’Silva et al. in 2022 shows how other clinical trials in which ARBs were compared to a placebo obtained conflicting results. One trial showed less deterioration in episodic memory and attention, whereas others did not show differences. Moreover, when compared to CBB, cognitive improvements were not observed, but an increase in cerebral blood flow in several brain regions, including the parietal lobe, was observed [26]. Finally, it must be noted that in our study, ARBs showed a protective effect in combination with diuretics, which is the most prescribed combination. In this sense, several studies pointed out the possible role of diuretics in AD risk reduction [38,48]. Their possible role may be due to the effect of these drugs on reducing cerebrovascular events, such as silent vascular lesions, that are involved in white matter changes, a common hallmark in AD and other dementias [38]. In addition, diuretics may act as AD risk reducers by their vasorelaxant effect, which may counteract the vasoconstriction produced by amyloid pathogenesis [38,48]. Among them, thiazide diuretics and potassium-sparing diuretics stand out as AD risk reducers in the Cache County study [22]. Thus, the protective role of ARBs could be enhanced by the neuroprotector properties that diuretics seem to have. ## Strengths and Limitations A strength of the present study is that the medications were registered according to exact dates and exact doses. In addition, the participants were classified as attending to CSF biomarkers levels, while most antihypertensive studies that correlate this medication with AD are based only on cognitive tests. In this sense, the present study provides an objective and accurate AD diagnosis. It should be considered that the inclusion criteria for this study were to consent to a lumbar puncture, which is an invasive intervention that dissuades potential participants, especially cognitively healthy adults. In spite of the required invasive sampling with some adverse side effects (headaches, pain), a relevant number of cognitively healthy participants was included in the present study. This is a strength because, to our knowledge, there are few studies about antihypertensives with a control sample based on CSF biomarkers, and published work has a few participants. On the contrary, this fact is also a limitation, and future studies including more participants are needed. Lastly, it must be considered that the study was performed at an outpatient consultation center of the Cognitive Disorders Unit, where other healthcare professionals refer patients due to pathological suspicion or memory complaints. Moreover, adherence has not been verified, and genetic risk factors such as APOE e4 have not been analyzed. ## 5. Conclusions High SBP, elderly age, and female gender are variables associated with a higher risk of AD diagnosis. In addition, calcium channel blockers and plain ACEi consumption are associated with a higher tau/Aß42 ratio, whereas consuming ARBs is associated with a lower tau/Aß42 ratio. 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--- title: Data Independent Acquisition Reveals In-Depth Serum Proteome Changes in Canine Leishmaniosis authors: - Franjo Martinković - Marin Popović - Ozren Smolec - Vladimir Mrljak - Peter David Eckersall - Anita Horvatić journal: Metabolites year: 2023 pmcid: PMC10059658 doi: 10.3390/metabo13030365 license: CC BY 4.0 --- # Data Independent Acquisition Reveals In-Depth Serum Proteome Changes in Canine Leishmaniosis ## Abstract Comprehensive profiling of serum proteome provides valuable clues of health status and pathophysiological processes, making it the main strategy in biomarker discovery. However, the high dynamic range significantly decreases the number of detectable proteins, obstructing the insights into the underlying biological processes. To circumvent various serum enrichment methods, obtain high-quality proteome wide information using the next-generation proteomic, and study host response in canine leishmaniosis, we applied data-independent acquisition mass spectrometry (DIA-MS) for deep proteomic profiling of clinical samples. The non-depleted serum samples of healthy and naturally Leishmania-infected dogs were analyzed using the label-free 60-min gradient sequential window acquisition of all theoretical mass spectra (SWATH-MS) method. As a result, we identified 554 proteins, 140 of which differed significantly in abundance. Those were included in lipid metabolism, hematological abnormalities, immune response, and oxidative stress, providing valuable information about the complex molecular basis of the clinical and pathological landscape in canine leishmaniosis. Our results show that DIA-MS is a method of choice for understanding complex pathophysiological processes in serum and serum biomarker development. ## 1. Introduction Blood serum reflects an individual’s phenotype providing a valuable information of physiological and pathological processes in organism making it a valuable source of biomarkers [1]. However, the high dynamic range aggravates the routine identification and quantification of low abundant proteins which are of a great interest to decipher proteome-wide protein functions and their interactions [2]. For that reason, various pre-analytical strategies such as fractionation, as well as enrichment methods including affinity depletion using immobilized antibodies or other molecules that specifically remove up to 22 high abundant proteins, and combinatorial peptide ligand library for proteome normalization are introduced [3,4]. Current depletion methods are costly, time-consuming, lack reproducibility, and often require additional processing (e.g., desalting or sample concentration) as a part of the MS-compatible proteomic analysis workflow. Additional separation steps are time consuming and introduce experimental variability making the results less reliable, especially regarding protein quantification [3]. Furthermore, most of the specific antibody-based depletion columns are constructed to remove the most abundant proteins from human samples unlike animal samples. Mass spectrometry (MS)-based proteomics has become a powerful tool in biomedical research allowing the characterization of thousands of proteins as well as their posttranslational modifications [5]. Over the past couple of decades, MS-based proteomics has been mostly performed in a data-dependent acquisition (DDA) mode using shotgun strategy where proteins are digested by a sequence specific protease and resulting peptides are analyzed by liquid chromatography tandem mass spectrometry (LC- MS/MS) [4]. Herein, the top N most intense peptide’s fragments in MS2 produce a pattern of unique fragment ions spectra used to be assigned to their corresponding peptide sequences for unambiguous protein identification. However, low intensity ions often remain unidentified. Advances in MS-based technology and bioinformatics enabled to overcome the detectable dynamic range restrictions of peptides that ionize the best. Data-independent acquisition (DIA) using sequential window acquisition of all theoretical mass spectra (SWATH-MS) approach has been developed enabling the deep proteome coverage through confident peptide identification over a dynamic range of four orders of magnitude with quantitative consistency and accuracy [6]. The application of SWATH-MS enables the systematic and unbiased fragmentation of all ions within the overlapping precursor isolation windows leading to highly complex fragment ion spectra. Peptide identification is based on sample-specific spectral libraries constructed using DDA data, containing chromatographic and mass spectrometric coordinates determined by using normalized retention time [7]. Unlike DDA-based sample-specific spectral libraries, in silico spectral libraries are built directly from protein sequence databases (FASTA files) without previous DDA data requirements providing better proteome coverage in unbiased way [8]. For that purpose, deep learning algorithms are applied, selecting the list of target peptides from protein sequence databases by predicting the MS detectability of candidate proteotypic peptides [8]. It is worth mentioning that sample-specific spectral libraries (e.g., pan-human DIA libraries) are still the main choice in cancer research, reflecting tumor heterogeneity [9]. Zoonotic visceral leishmaniosis (VL) is a potentially fatal vector-borne disease endemic in South America, South-East Asia, Eastern Africa, and the Mediterranean Region [10]. In Croatia, human and canine leishmaniosis caused by Leishmania infantum has been present in central and southern Dalmatia since the beginning of the 20th century [11], and the dog has remained the main reservoir. Limited drug development and emerging drug resistance, as well as long duration of treatment [12] are making the understanding of the host-related processes in leishmaniosis even more important. In our previous studies, we applied tandem mass tag (TMT)-based DDA-MS methods for treatment monitoring in canine leishmaniosis by analyzing serum, and to understand the disease-related processes in canine saliva [11,12]. In that light, in order to obtain high-quality proteome wide information using the next-generation proteomics and study host response in canine leishmaniosis which could be observed in serum, the aim of this experiment was to construct canine serum proteome spectral library using DDA-MS approach and establish fast and label-free short gradient SWATH-MS method. Our results indicate the DIA-MS approach is extremely sensitive and informative, enabling the identification of canine serum proteins affected by canine leishmaniosis with biomarker potential, their functions and molecular pathways mostly included in lipid metabolism, hematological abnormalities, immune response, and oxidative stress. ## 2.1. Sample Description The study was carried out using 10 archived canine sera previously used in routine leishmaniosis diagnostics at Department for Parasitology and Parasitic Diseases with Clinics, Faculty of Veterinary Medicine, University of Zagreb collected during six month- time interval. It involved sera classified into two groups: sera from healthy control group ($$n = 5$$) were mix breeds, age 2.5–9 years, while the Leishmania-infected group ($$n = 5$$) were mixed breeds, age 2–8 years. Control dogs were considered healthy based on previous serological tests. The infection of Leishmania infantum was diagnosed using three serological tests [13]: indirect fluorescence antibody test (IFAT), enzyme-linked immunosorbent assay (ELISA), and kinesin-related conserved recombinant antigen (rK39 rapid immunochromatographic test evaluating the presence of anti-Leishmania antibody) following the manufacturers’ instructions (Supplementary file S1). All naturally infected dogs (originating from the enzootic region of Croatia) showed clinical signs of Leishmania infection. The sera of infected dogs were taken before the treatment. All canine sera used in this study were tested negative for the presence of Dirofilaria immitis antigen using the antigen rapid test (Fast test HWantigen, Megacor Diagnostik, Vorarlberg, Austria). ## 2.2. Sample Collection Archived, 10 canine sera samples were received from different veterinary stations sent to Department for Parasitology and Parasitic Diseases with Clinics, Faculty of Veterinary Medicine, University of Zagreb, for routine serological leishmaniosis diagnostics. After the diagnostics, sera samples were aliquoted and stored at −80 °C until analyzed to avoid multiple freeze-thaw cycles. Total protein concentration in serum was determined using a Pierce BCA Protein Assay Kit (Thermo Scientific, Rockford, IL, USA). ## 2.3.1. In-Solution Digestion The pooled sample was prepared by mixing equal protein amounts of all ten samples involved in this study and used for in-solution digestion [14]. A total of 50 μg of total protein was mixed with 50 mM NH4HCO3 to a final concentration of 1 mg/mL. After the addition of 5 μL DTT (50 mM) sample was incubated for 30 min at 55 °C and 5 μL IAA (200 mM) was added subsequently. After 30 min, overnight digestion at 37 °C using trypsin gold (1:50 w/w) was performed. Tryptic digest was stored at −20 °C for further analysis [14]. Before the analysis, samples were mixed with 10× iRT peptide solution (Biognosys AG, Schlieren, Switzerland) for subsequent LC-MS/MS analysis. ## 2.3.2. Strong Cation Exchange (SCX) Chromatography SCX was performed using pipette tips [15] with some modifications. Before the SCX chromatography, digested sample was desalted using Cleanup C18 pipette tips (10 μL, Agilent Technologies, Santa Clara, CA, USA) according to manufacturer’s instructions. Finally, peptides were eluted with $80\%$ ACN/$0.1\%$ (v/v) formic acid, dried using vacuum concentrator and dissolved in 10 μL $0.1\%$ formic acid. Strong cation exchange chromatography was performed using OMIX SCX pipette tips (10 μL, Agilent Technologies, Santa Clara, CA, USA). The tips were washed by mixture of $25\%$ ACN in $0.05\%$ formic acid and peptides were subsequently eluted with 100, 200 and 400 mM NH4HCO3 in $25\%$ACN/$0.05\%$ formic acid (v/v). Finally, samples were dried in vacuum concentrator, desalted using Cleanup C18 pipette tips, dried again, and finally mixed with 18 μL loading buffer and 2 μL of 10× iRT peptide solution (Biognosys AG, Schlieren, Switzerland) for DDA analysis. ## 2.3.3. Combinatorial Peptide Ligand Library (ProteoMiner) The ProteoMiner Small-Capacity Kit (Bio-Rad, Hercules, CA, USA) containing a hexapeptide library [16] was used to equalize the protein concentration dynamic range of canine serum samples according to manufacturer’s procedure. Briefly, ProteoMiner column containing 20 μL beads was washed three times with 200 μL phosphate-buffered saline (PBS) buffer by 5 min incubations followed by 1000× g centrifugation. After adding 200 μL of pooled sample, bead-sample slurry was incubated with rotation (2 h at room temperature) and washed repeatedly three times before the elution. The protein elution was conducted by adding 20 µL of elution reagent to the column and vortexing for 15 min, followed by centrifugation at 1000× g. As a part of MS-compatible workflow, eluted proteins were desalted using Microcon filter (10 kD MWCO, Millipore, Darmstadt, Germany). The eluate after ProteoMiner enrichment was mixed with 200 μL of milliQ water followed by centrifugation at 8000× g for 45 min. Proteins were washed twice with milliQ water by centrifugation at 8000× g for 30 min and once with 200 μL 50 mM NH4HCO3. Finally, proteins were collected by inverting the filter assembly followed by centrifugation at 2800× g for 5 min. Due to the reduced sample volume, the total protein concentration was determined by NanoDrop. Finally, in-solution digestion was performed. ## 2.4. MS-Based Proteomic Analysis High resolution LC-MS/MS analysis was carried out using an Ultimate 3000 RSLCnano system (Dionex, Germering, Germany) coupled to a Q Exactive Plus mass spectrometer (Thermo Fisher Scientific, Bremen, Germany). Prior to analysis, tryptic peptides were mixed with iRT peptides (Biognosys) (1:10 v/v), desalted on the trap column and separated on the analytical column (PepMap™ RSLC C18, 50 cm × 75 μm). Ionization was achieved using nanospray Flex ion source (Thermo Fisher Scientific, Bremen, Germany) equipped with a 10 μm-inner diameter SilicaTip emitter (New Objective, Littleton, MA, USA). ## DDA Proteomic Analysis for Spectral Library Generation DDA analysis was performed as reported [14] with some changes. In short, for peptide separation, linear gradient 5–$45\%$ mobile phase B ($0.1\%$ formic acid in $80\%$ ACN, v/v) over 120 min, at the flow rate of 300 nL/min was used. Mobile phase A contained $0.1\%$ formic acid in water. The MS operated in positive ion mode using DDA Top10 method. Full scan MS spectra were acquired in range from m/z 350.0 to m/z 1800.0 with a resolution of 70,000, 120 ms injection time, AGC target 1 × 106, a ±2.0 Da isolation window and the dynamic exclusion 30 s. For HCD fragmentation, step collision energy ($29\%$ and $35\%$ NCE) with a resolution of 17,500 and AGC target of 2 × 105 was used. Precursor ions with charge states of +1 and more than +7, as well as unassigned charge states, were excluded from HCD fragmentation. For DDA protein identification, the SEQUEST algorithm implemented into Proteome Discoverer (version 2.3., Thermo Fisher Scientific) was applied. Database search against database containing Canis lupus familiaris FASTA files (downloaded from UniprotKB database $\frac{14}{10}$/2021, 49,889 entries) combined with Biognosys iRT fusion peptide FASTA file (available at https://biognosys.com/shop/iRT-Kit (accessed on 1 September 2022)) was performed using parameters as follows: two trypsin missed cleavage sites, precursor and fragment mass tolerances of 10 ppm and 0.02 Da, respectively; carbamidomethyl (C) fixed peptide modification, oxidation (M), dynamic modifications. The false discovery rate (FDR) for peptide identification was calculated by the Percolator algorithm within the Proteome Discoverer workflow and was set at $1\%$. The DDA mass spectrometry proteomics data have been deposited to the Consortium via the PRIDE partner repository [17] with the dataset PXD039763. ## 2.5. DIA Proteomic Analysis For DIA analysis, a linear gradient 5–$45\%$ mobile phase B ($0.1\%$ formic acid in $80\%$ ACN, v/v) over 60 min, at the flow rate of 300 nL/min was used. Mobile phase A contained $0.1\%$ formic acid in water. The MS operated in positive ion mode using DIA Full MS method. MS spectra representing 44 overlapping sequential DIA windows with an isolation width of m/z 15 between m/z 450 and m/z 1100 were acquired using resolution of 35,000 and AGC target 1 × 106, MSX 1, and charge state +2. For HCD, fragmentation collision energy $29\%$ (NCE) with a resolution of 17,500 and AGC target of 2 × 105 was used. The raw and analyzed DIA data files have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository [17] with the dataset PXD039765. Obtained data were analyzed using Spectronaut 16 (v. 16.2.220203.530000, Biognosys AG, Schlieren, Switzerland) [18]. Protein identification and quantification was performed using directDIA workflow. Identification was improved by combining of in-house generated spectral library and FASTA files (as described in Section 2.5). Factory settings were used to perform differential expression analysis between two different conditions, e.g., healthy and Leishmania-infected dogs and calculate adjusted p-values (q-values) based on multiple hypotheses testing corrections using Benjamini–Hochberg method. Proteins having adjusted p-value (q-value) < 0.05 were considered as significantly abundant. Principal component analysis (PCA) plot and volcano plot were generated in Spectronaut software. Gene ontology (GO) terms were enriched based on Welch’s t-test with p-value < 0.05 using bioinformatics web platform ExpressAnalyst (https://www.expressanalyst.ca/ (accessed on 30 November 2022)). For the network-based and enrichment analyses, Homo sapiens was selected as model organism. ## 2.6. Spectral Library Generation For spectral libraries generation, DDA raw files and belonging Proteome Discoverer search results of analyzed samples (namely pooled, mixed control, mixed case, ProteoMiner enriched, and 3 SCX fractions all containing iRT peptides for retention time normalization as described in Section 2.3) were imported into Spectronaut 16 software (v. 16.2.220203.530000, Biognosys AG, Schlieren, Switzerland) with default settings. Furthermore, to enable in silico spectral library generation using Canis lupus familiaris FASTA files downloaded from UniprotKB database $\frac{14}{10}$/2021, 49,889 entries) combined with Biognosys iRT fusion peptide FASTA file (available at https://biognosys.com/shop/iRT-Kit (accessed on 1 September 2022)), Pulsar search engine with deep learning augmentation integrated into Spectronaut software was used. For libraries generation, following factory settings were used: Trypsin/P as the digestion enzyme with missed cleavages ≤2, and only peptides with length from 7 to 50 amino acids with mass ≤ 6000 Da were kept. ## 3.1. DDA-Based Proteomic Results To generate high-quality sample-specific spectral library containing a large set of high confident peptides originating from both high and low abundant serum proteins, a pooled and ProteoMiner enriched samples as well as SCX fractions were analyzed by DDA-MS-based strategy. In this way, we identified 1405 proteins within 464 protein groups (464 master proteins), unlike 186 protein groups identified only by analyzing the pooled sample (shotgun approach without depletion and fractionation), as shown in Figure 1. ## 3.2. DIA-Based Proteomic Results DIA-based proteomic analysis was employed to provide the deep insight into proteome-wide changes of host serum in canine leishmaniosis. For generating state-of-the-art libraries from both DDA data, Pulsar search integrated into Spectronaut software was used. The sample-specific spectral library (provided in Supplementary file S2) contained Canis lupus familiaris FASTA file enriched with peptides identified by DDA analysis, e.g., pooled, enriched and/or fractionated serum samples (Pulsar search). Spectral library details are shown in Figure 2. Quantitative proteomic data of non-depleted serum samples were obtained using the SWATH-MS technology as described in Section 2.5. DIA proteomic analysis. As a result, we successfully identified a set of 554 serum proteins with a high quantitative performance. Furthermore, proteomic analysis with a wide dynamic range coverage revealed difference in the abundance of the 140 proteins with 107 being higher and 33 lower in abundance in canine leishmaniosis satisfying the cutoff criteria (q-value < 0.05 and absolute log2FC > 0.5). Belonging volcano plot is depicted in Figure 3b. The principal component analysis (PCA) plot shows differences in serum proteomes between healthy and Leishmania-infected dogs as in Figure 3a. A shortened list containing differentially abundant proteins that change the most (the absolute value) and accompanying details, such as accession numbers and fold changes, is provided within the Table 1. The complete protein list can be found within Supplementary file S3. Gene ontology (GO) analysis of differentially abundant proteins revealed key molecular functions and biological processes affected by Leishmania infection (Figure 4 and Figure 5). The GO term results (Figure 4) indicate that the proteins affected by Leishmania infection play roles in lipid transport (p-value 2.08 × 10−7) and cholesterol metabolism (p-value 8.3 × 10−3), blood coagulation (p-value 2.7 × 10−3), immune response (p-value 9.2 × 10−3), and receptor-mediated endocytosis (p-value 4.7 × 10−4), among others. ## 4. Discussion Serum proteomics is a powerful tool for non-invasive monitoring of biological processes, enabling the understanding of various pathophysiological processes occurring in a living organism as well as biomarker discovery. However, although easily accessible, high abundant molecules, such as albumin (57–$71\%$) or gamma-globulins (8–$26\%$), as well as high dynamic range (12 orders of magnitude) molecules, have been making the serum a complex analyte for DDA bottom-up MS analysis, unlike our DIA-MS study where 554 proteins were identified in non-depleted sample. Although various depletion strategies of high abundant proteins have been introduced, serum albumin is a 66.5 kDa-protein known to act as a carrier for various endogenous and exogenous ligands [19] and other small proteins [20]. So, the removal of these large molecules often results in the loss of molecules of interest (in terms of quantity and/or quality) providing an incomplete picture. Aware of the depletion effect on the results, in our previous studies, we analyzed non-depleted serum samples in dogs with leishmaniosis for treatment monitoring using DDA tandem mass tag (TMT) label-based quantitative proteomic approach which enabled us the identification of 117 canine serum proteins among which 23 were differentially abundant [21]. However, based on the number of total identified proteins, the detection of low abundant proteins remained partially disabled, still giving the incomplete insight into the complex serum proteome. Despite DDA-MS analysis was the main choice in proteomics since its inception, DIA-based proteomics experiments are recently becoming the powerful alternative due to the fast and simplified sample preparation and significantly improved results in terms of reduced instrument time requirements and the increased number of identified proteins [22], which we also showed herein. Moreover, results addressing DIA-MS-based plasma proteomics in dogs have been reported confirming all abovementioned methodological advantages [23]. However, DIA has not yet been applied in the analysis of sera in canine leishmaniosis. Herein, we aimed to implement DIA serum proteomics workflow using next generation proteomic technology to better understand the host-specific processes during Leishmania infection in dogs. For in-depth DIA-MS proteome analysis, we established high-quality sample specific spectral library containing extensive set of 3628 peptides and their relative retention time details obtained by spiked-in non-naturally occurring synthetic peptides for retention time normalization [7] to enable proteome profiling coverage. Having in mind that the spectral library should be sufficiently large, sample-size comparable, and that the results are library (size and fragmentation pattern) dependent [24], we chose the directDIA workflow based on in silico database search (canine FASTA files) enriched with Pulsar search results of our DDA data for the best result outputs. In this way, using SWATH methodology, we identified 554 serum proteins using 60-min gradient time, which is about 4.5 times more protein than in our previous study [8] or about 2.5 times more proteins than performing the DDA without depletion (120-min gradient time). This enabled detailed qualitative and quantitative insights into the serum proteomes of healthy and Leishmania-infected dogs, including both high and low abundant proteins with simplified sample preparation and shorter analysis time. Although the DIA database search was performed, Leishmania proteins were not found (data not shown). It is important to emphasize that some of the leishmaniosis-related serum proteins (such as prosaposin) identified herein by simple sample preparation (in-solution digestion) and SWATH-MS proteomic approach were previously identified only after laborious sample preparation (exosome isolation) and subsequent proteomic analysis [25]. Finally, GO analysis of differentially abundant proteins provided us key molecules and related molecular processes observable in serum affected by Leishmania infection in dogs. Those include lipid metabolism, hematological abnormalities, immune response, oxidative stress, etc. ## 4.1. Lipid Metabolism and Transport Leishmania infantum is an intracellular parasite which relies on host lipid reservoir and synthesis mechanism for its survival [26]. Various studies related to Leishmania infection reported the multiple importance of cholesterol and cholesterol metabolic processes in Leishmania transformation process and sterol metabolism [27]. The cholesterol sequestration by Leishmania parasite begins post infection, with host cells aiming to restore initial cholesterol levels correlating with the upregulation of proteins required for cholesterol metabolism [28]. Accordingly, in our study, cholesterol metabolic processes are shown to be affected by Leishmania infection, with proteins Apo E and Apo A4 being upregulated. The elevated levels of Apo E have already been reported in serum of Leishmania-infected human patients [29]. Apo E (apolipoprotein E) is a 34 kDa glycoprotein critical for cholesterol transport and lipoprotein particle metabolism, playing an important role in lipolytic enzyme activation and immune response [30]. The study involving apolipoprotein E knockout mice infected with Leishmania donovani showed the important role of Apo E in protection against visceral leishmaniosis by displaying hypercholesterolemia, host-protective cytokines, and expansion of antileishmanial CD8 + IFN-γ + and CD8 + IFN-γ +TNF-α + T cells [31]. Apolipoprotein A4 (APOA4) is a plasma lipoprotein involved in the regulation of lipid and glucose metabolism [32], and enhances triglyceride (TG) secretion from the liver [33]. Upregulation of APOA4 protein shown herein could be related with already reported increase in triglyceride levels in patients with visceral leishmaniosis [34]. Except cholesterol, the studies have been published indicating that Leishmania sp. scavenges host sphingolipids (e.g., sphingomyelin, which is not synthesized by Leishmania but is abundant in mammals) needed for amastigote proliferation, virulence and biosynthesis of inositol phosphorylceramide (IPC, major sphingolipid in the genus Leishmania not present in mammals) [35]. In our study, we showed the upregulation of prosaposin, PSAP, which is a large precursor protein that is proteolytically cleaved into four sphingolipid activator proteins that assist in the lysosomal hydrolysis of sphingolipids into ceramide needed for the synthesis of IPC [36,37]. Our results are in accordance with existing data showing the Leishmania infection induces the host ceramide synthesis pathway [38]. ## 4.2. Hematological Abnormalities The progression of the canine leishmaniosis has the effect on hematological parameters, mostly caused by anemia and/or platelet aggregation abnormalities [39]. Our results are supporting these findings. Anemia is present in the majority of symptomatic dogs with leishmaniosis [39]. In our study, we detected the decreased amount of carbonic anhydrase 1 (CA1). CA1 is the most abundant protein in erythrocytes after hemoglobin. Its expression increases in various forms of anemia. However, its expression decreases in hemolytic anemia and for that reason CA1 is used as biomarker for this disease [40]. Coagulation factors, being a part of coagulation cascade, are essential for normal blood clotting. Herein, we determined the relative coagulation factor (F11, F13A1, F13B) deficiency, as well as histidine-rich glycoprotein (HRG) deficiency in Leishmania-infected dogs compared to healthy dogs that is related to decreased coagulation factor activities and fibrinolysis as reported in human patients [41,42,43]. Furthermore, we also found platelet-activating factor (PAF) acetylhydrolase (PLA-AH2) to be upregulated in Leishmania-infected dogs. Platelet-activating factor is a phospholipid that is involved in the activation of thrombotic cascades, induces leukopenia and thrombocytopenia (which are the most common hematological symptoms in leishmaniosis), as well as increases vascular permeability [44]. It is also involved in inflammatory reactions. PAF acetylhydrolase 2, also known as lipoprotein-associated phospholipase A2 (Lp-PLA2), inactivates the PAF and PAF-like oxidized phospholipids found in oxidized LDL by hydrolysis, controlling their actions. The increase in PLA-AH2 activity is positively correlated with activation of inflammatory cells. PAF was reported essential for the control of Leishmania infection. [ 45]. ## 4.3. Immune Response The immune response is a coordinated response of variety of cells and molecules on exposure to foreign antigens. Acute phase proteins (APPs) are the markers of the immune system response whose concentration in serum significantly changes during inflammation, which was also found in our study. The APP profiles and concentrations in combination with animal clinical condition monitored at physical examination may provide a valuable tool for the characterization, management and treatment monitoring of canine leishmaniosis [46]. Canine leishmaniosis is related with the increase of haptoglobin (HB) and C-reactive protein (CRP, or pentraxin) concentration that is measured in clinical practice [47]. Except increase in concentration of HB, CRP, and alpha 2 macroglobulin (A2M) in serum of Leishmania-infected dogs, we also detected negative APPs, transthyretin and retinol-binding protein, showing the decrease in abundance in Leishmania-infected dogs compared to healthy dogs. Interestingly, alpha 1 antitrypsin (ATT), a positive APP, was found to be lowered in Leishmania-infected dogs. Alpha-1 antitrypsin is a protease inhibitor synthesized mainly in the liver. Diffusing into the lung tissue and alveolar fluid, it inactivates neutrophil elastase and protects the lung tissue from the damage. The reduction of circulating levels of alpha-1 antitrypsin result in the increased risk of lung disease [48]. Accordingly, the pulmonary alterations and the inflammatory process defined as interstitial pneumonitis were reported in Leishmania-infected dogs, as well as the presence of amastigotes in canine lungs, which could support our findings [49]. Except the APPS, within the immune response, lysosomal cysteine cathepsin family of proteases, such as cathepsin S (CTSS), play a key role. CTSS, involved in TLR9 processing [50], is involved in dendritic cells activation and resolution of Leishmania major infection in mice [51]. Also, cathepsin S deficient mice are slightly more susceptible against Leishmania major infection [52]. According to those facts, animals with elevated cathepsin S in serum should be resistant against infection with Leishmania, which is not the case in our work. In contrast, in our survey, the amount of cathepsin S was three-fold elevated in positive dogs. As elevated cathepsin S is proven in many human diseases [53,54], a more detailed investigation should be made to show if the cathepsin S is a good marker for the disease diagnostics and prognosis. Although the DIA-SWATH-MS strategy applied herein generated a long list of deregulated proteins, some of which present biomarker potential, further investigation using a larger population of healthy and Leishmania-infected canine patients is needed to determine the diagnostic potential of a single biomarker or biomarker panels, correlating the clinical symptoms and protein concentration. Additionally, it would be interesting to use a DIA-MS approach for canine leishmaniosis treatment monitoring. ## 5. Conclusions Our study demonstrates the advantages of next generation DIA-MS proteomic analysis of serum, enabling deeper insights into altered expression levels of both high and low abundant proteins without enrichment in shorter analysis times. This approach was shown to be extremely useful and informative in the identification of disease-related proteins, their functions, and molecular pathways in canine leishmaniosis. Additionally, our open access canine serum spectral libraries could be useful for in silico generated combined spectral libraries to be applied in various canine serum studies. Finally, this approach may be employed to decipher the pathological processes of various diseases in serum, as well as serum biomarker development. ## References 1. Geyer P.E., Holdt L.M., Teupser D., Mann M.. Revisiting biomarker discovery by plasma proteomics. Mol. Syst. Biol. (2017) 13 942. DOI: 10.15252/msb.20156297 2. Fürsch J., Kammer K.-M., Kreft S.G., Beck M., Stengel F.. 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--- title: Different Species of Marine Sponges Diverge in Osteogenic Potential When Therapeutically Applied as Natural Scaffolds for Bone Regeneration in Rats authors: - Cíntia P. G. Santos - João P. S. Prado - Kelly R. Fernandes - Hueliton W. Kido - Bianca P. Dorileo - Julia R. Parisi - Jonas A. Silva - Matheus A. Cruz - Márcio R. Custódio - Ana C. M. Rennó - Renata N. Granito journal: Journal of Functional Biomaterials year: 2023 pmcid: PMC10059666 doi: 10.3390/jfb14030122 license: CC BY 4.0 --- # Different Species of Marine Sponges Diverge in Osteogenic Potential When Therapeutically Applied as Natural Scaffolds for Bone Regeneration in Rats ## Abstract A highly porous structure, and an inorganic (biosilica) and collagen-like organic content (spongin) makes marine sponges potential candidates to be used as natural scaffolds in bone tissue engineering. The aim of this study was to characterize (through SEM, FTIR, EDS, XRD, pH, mass degradation and porosity tests) scaffolds produced from two species of marine sponges, Dragmacidon reticulatum (DR) and Amphimedon viridis (AV), and to evaluate the osteogenic potential of these scaffolds by using a bone defect model in rats. First, it was shown that the same chemical composition and porosity (84 ± $5\%$ for DR and 90 ± $2\%$ for AV) occurs among scaffolds from the two species. Higher material degradation was observed in the scaffolds of the DR group, with a greater loss of organic matter after incubation. Later, scaffolds from both species were surgically introduced in rat tibial defects, and histopathological analysis after 15 days showed the presence of neo-formed bone and osteoid tissue within the bone defect in DR, always around the silica spicules. In turn, AV exhibited a fibrous capsule around the lesion (19.9 ± $17.1\%$), no formation of bone tissue and only a small amount of osteoid tissue. The results showed that scaffolds manufactured from Dragmacidon reticulatum presented a more suitable structure for stimulation of osteoid tissue formation when compared to Amphimedon viridis marine sponge species. ## 1. Introduction Biomaterial-based therapy has increasingly become a viable strategy for treating bone fractures. Synthetic or naturally occurring, every type of biomaterial has a unique set of characteristics. Polyurethanes, polyesters, metals such as titanium and other synthetic polymers have advantageous properties over natural ones especially because of their abundance, limitless designs and customizable attributes. They require, however, chemical alterations since they lack cell adhesion sites and are, therefore, considered to be less biocompatible [1,2]. As a vast source of natural biomaterials, marine biodiversity has lately been gaining prominence in scientific research around the world. Among the invertebrates that stand out in different studies, marine sponges (Phylum Porifera) are primitive sessile animals characterized by being multicellular, filter-feeding and structurally porous [3]. It is indeed a fact that these animals archaically filter water for feeding with microorganisms that confer them unique characteristics for their use as biomaterials in the engineering of bone tissue. Their porous architecture with interconnected pores would favor, once implanted in patients, the passage of cells and blood vessels and, consequently, tissue regeneration [3]. Thus, adequate structural characteristics of the implant play a fundamental role in the efficiency of the treatment since the formation of the new tissue depends on an adequate migration and proliferation of the cells responsible for this process and also on the invasion of new blood vessels within the implanted scaffold. This infiltration will only properly occur if the scaffold is structurally favorable, especially in terms of porosity, pore size and pore interconnectivity. In addition to being a source of precursor cells that will be later responsible for the new tissue formation, vascularization may also have its relevance since it provides the nutrients needed for cellular metabolism and the removal of its residual products [4,5]. Besides their structural peculiarities, marine sponges have, like the bone itself, a skeleton composed of an organic component, named spongin, and inorganic components such as biosilica [6,7]. Spongin is a protein similar to vertebrate collagen that has also been used in the production of scaffolds for tissue bioregeneration [8] because it allows cell attachment, proliferation and migration through the biomaterial [9]. Based on this, spongin is an excellent alternative to animal collagen, due to the low risk of transmission of infection-causing agents and good biocompatibility [10,11]. Biosilica is an inorganic element that is known to drive bone cell differentiation and increase mineralization [6,11,12]. The ideal scaffold for bone substitution, regardless of whether it is natural or synthetic, needs to be biocompatible, porous, have osteoconductive and osteoinductive capacities, mechanical properties similar to those of bone and a rate of degradation compatible with the process of bone remodeling [3,13]. Previous in vitro studies showed that osteoprogenitor cells were able to grow and attach onto the sponge skeleton. Green et al. [ 14] demonstrated that the skeleton of Spongia sp. enabled human osteoprogenitor cells’ adhesion, expansion and invasion. Alkaline phosphatase and type I collagen histochemical stains showed that the bone matrix could be formed. Lin et al. [ 15], by also evaluating a sponge skeleton with a collagenous fibrous network (Callyspongiidae sp.), showed that mouse primary osteoblasts were able to anchor onto the surface of collagen fibers, express osteoblast markers (osteocalcin and osteopontin) and form mineralization nodules. Likewise, SaOS-2 cells were able to grow and colonize the bioceramic structure of Petrosia ficiformis sponges after calcination [16], addionally demonstrating the advantages conferred by sponge scaffold architecture as a template for bone cell growth, differentiation and mineralization [17]. These ancient multicellular organisms boast a diverse array of skeletal structures that have evolutionary-approved 3D-scaffold-like qualities and appear to be highly suitable for use across a range of fields within modern bioinspired materials science, biomimetics and regenerative medicine [16]. Even though several in vitro studies speculate its potential for use as a scaffold, only one study has been conducted with the aim of analyzing the in vivo potential of using marine sponges in their natural state until now. Nandi et al. [ 18] carried out an investigation to identify and characterize marine sponges as potential bone scaffolds. For this purpose, samples of marine sponge Biemna fortis (class Demospongiae), collected from the intertidal region of Anjuna, India, were implanted in femoral defects in rabbits. After 90 days, the results showed that marine sponges of the mentioned species, combined or not with growth factors (IGF-1 and BMP-2), were biocompatible and biodegradable, and could be considered as a new natural biomaterial for bone tissue engineering purposes. Based on the above, sea sponges, with their porosity, biosilica and spongin, can be potentially considered as innovative bone substitutes, which would allow the development of new therapeutic resources for the improvement of patients’ quality of life. Additionally, since they a natural, abundantly found material, their use would contribute to a reduction in the treatment costs in public health systems. However, this potential is still largely unexplored. Despite several studies evaluating the use of compounds extracted from marine sponges, only one in vivo study was found in the literature evaluating the marine sponge skeleton as a bone-mimicking biomaterial. Moreover, this single study did not perform quantitative evaluations of the bone healing process. Finally, since sponges structurally differ among species, we hypothesize that their osteogenic potential would also be different. In this way, the present study performed a physical-chemical characterization and an evaluation of the in vivo osteogenic potential of scaffolds manufactured from two species of marine sponges with the aim of developing efficient substitutes for guided bone regeneration. The species of Porifera used in this study were Dragmacidon reticulatum and Amphimedon viridis, which are abundantly present on the Brazilian coast. ## 2. Materials and Methods It is important to note that this study is registered in the National Management System of Genetic Patrimony (Sistema Nacional de Gestão do Patrimônio Genético, SisGen, registration number A56D034). The marine sponge species Dragmacidon reticulatum and Amphimedon viridis, both belonging to the class Demospongiae, were used in this study. These two species (Figure 1) were specifically chosen for being abundant and easily found on the Brazilian coast. Both have porous skeletons composed of spongin and biosilica, which are interesting elements in the context of bone repair. The sponges were collected in high hydrodynamic coasts, in the intertidal zone, in the area of São Sebastião, Brazil (23°49′23.76″ S, 45°25′01.79″ W) and in the area of Enseada do Araçá (23 No. 81′73.78″ S, 45° 40′66.39″ W, São Sebastião, Brazil). An amount of 200 g of each marine sponge species was collected for this study. After the collection, the sponges were washed with running water, classified according to their species’ characteristics and kept in the freezer until use. To produce the scaffolds, the sponges were cut with a trephine-type dental drill (3i Implant Innovations Inc., Palm Beach Gardens, Florida, USA) and a scalpel blade for the manufacture of 3 mm diameter × 2 mm thick scaffolds (Figure 1). The produced scaffolds were freeze-dried and sterilized by ethylene oxide (Acecil Central de Esterilização Comércio e Indústria Ltd.a—Campinas/SP, Brazil). The parameters used for the freeze drying were −40 °C and 600 uHG (DIM Liofilizador LT X.X00—Terroni Equipamentos Cientificos Ltd.a—São Carlos/SP, Brazil). Characterization analyses of the scaffolds were performed before and after an incubation period, the conditions of which were determined according to the Kokubo protocol [19,20,21]. For the SEM, FTIR, XRD and EDS aanlyses, the scaffolds were incubated in simulated body fluid (SBF; pH 7.4) in a ratio of 1:10 (mass of the material (g): volume of the SBF (mL)) during a period of 21 days. Samples were evaluated before (day zero) and after incubation at periods 1, 7 and 21 days. For pH and mass loss evaluations, the scaffolds were placed in 3 mL of phosphate-buffered saline (PBS, pH 7.4) and incubated at 37 °C in a water bath on a shaker table (70 rpm) for 21 days. These analyses were performed before (day zero) and after incubation of scaffolds at periods 1, 3, 7, 14 and 21 days. ## 2.1. Surface Morphology Analysis (SEM) A scanning electron microscope (SEM, Le0 440, Carl Zeiss, Jena, Germany), operating at a 10 keV electron beam, was used to morphologically analyze the scaffolds surface. This technique consists of obtaining the enlarged image of the sample from the interaction of an electron beam with the material. For this, the samples were fixed on an aluminum base using a carbon tape. Next, due to the non-conductive properties of the samples (organic origin), they were covered with a thin layer of conductive material; in this case, the material used was gold. Thus, images were obtained with magnification of 500×, in the above-mentioned periods, in order to assess the morphology of the initial surface and the degradation behavior of the biomaterials ($$n = 5$$). ## 2.2. Fourier Transform Infrared Spectroscopy (FTIR) To identify the chemical bonds present in the material, Fourier-transform infrared spectroscopy (IRAffinity-1S-FTIR Shimadzu spectrophotometer, São Paulo, Brazil) was used. The specters were obtained in the range of 4000–400 cm−1, with a resolution of 4 cm1 ($$n = 3$$). ## 2.3. X-ray Diffraction (XRD) The crystalline phase of the material was evaluated by X-ray diffraction (XRD) with Philips X’Pert MPD diffractometer, Cu-Ka ($l = 0.154$ nm), 45 kV, 30 mA. Data were collected at angles between 20° and 60° at the IQSC(USP), São Paulo ($$n = 3$$). ## 2.4. Energy Dispersive X-ray Spectroscopy (EDS) This analysis was carried out by means of equipment IXRF Systems 500 coupled to a scanning electron microscope (SEM) that allowed a qualitative evaluation of the chemical elements present in the samples, with $0.5\%$ mass detection [22] ($$n = 5$$). ## 2.5. pH Evaluation Directly after removing samples from the incubation medium ($$n = 5$$), pH of incubation medium was measured with a pH meter (Orion Star A211, Thermo Scientific, Waltham, MA, USA). ## 2.6. Degradation Analyses The mass loss evaluation was performed to determine the degradation of biomaterials in liquid medium. After the experimental periods of incubation in PBS, the samples were oven-dried overnight at 37 °C and weighed on a precision balance. The relation between the final weight obtained and the initial weight was calculated to quantify the mass loss in percentage, according to the following equation: % Mass loss = ((fm − im)/im) × $100\%$, where fm is the sample mass after immersion in PBS and im is the sample mass before immersion in the same solution ($$n = 5$$). ## 2.7. Porosity Evaluation The porosity of Dragmacidon reticulatum and Amphimedon viridis scaffolds were evaluated according to the Archimedes’ principle (Equation [1]). First, scaffolds (1 cm × 0.4 cm) were obtained by cutting the sponges with a cutter. The scaffolds were dried overnight at 37 °C. The scaffolds were then weighed on a precision balance. The density of water was also calculated (mass/volume). Later, the scaffolds were placed in a glass container with 5 mL of water and the values of mass (grams) and volume (mL) were recorded. The scaffolds were removed from the glass container and the weight of the water was again recorded. The scaffolds’ density was calculated using the values of water + scaffolds and water weight differences. For the porosity calculation, the following formula was used:Porosity (%) = m1 − m3.WD[(m1.WD) + (SM.SD)] − (m3/WD) × 100[1] where m1 is initial mass of water, m3 is water mass after removing the scaffold, WD is the water density, SM is the scaffold mass and SD is the scaffold density ($$n = 5$$). ## 2.8.1. In Vivo Study Thirty male Wistar rats were used (12 weeks old, weight 300–350 g) in this study. All rats were submitted to a surgical procedure in which a unicortical non-critical bone defect was performed in both tibias. The animals were randomly divided into 3 groups: control group (CG)—defects were left unfilled; Dragmacidon reticulatum group (DR)—defects were implanted with scaffolds of marine sponge Dragmacidon reticulatum; Amphimedon viridis group (AV)—scaffolds that were implanted belonged to the species Amphimedon viridis. After surgical procedure, the animals were kept at a controlled temperature, 12 h light–dark period, with free access to water and standard food. This study was approved by the Ethics Committee on the Use of Animals (CEUA) of the Federal University of São Paulo ($\frac{2017}{3011170417}$). ## 2.8.2. Surgical Procedures A non-critical-sized bone defect, 3 mm in diameter, was performed in the upper third of each rat tibia (10 mm below the knee joint) by using a motorized trephine drill (3i Implant Innovations Inc., Palm Beach Gardens, Florida, USA) irrigated with saline solution (Figure 2A). Then, the wounds were closed with resorbable Vicryl® 5-0 (Johnson & Johnson, Sint-Stevens-Woluwe, Belgium). Surgeries were performed according to the ethical principles of animal instrumentation, at standard conditions of asepsis and general anesthesia. Initially, the animals were anesthetized with intraperitoneal injection of ketamine (80 mg/kg), xylazine (8 mg/kg), acepromazine (1 mg/kg) and fentanyl (0.05 mg/kg) in a single syringe. In addition, a single dose of cephalothin antibiotic (60 mg/kg) was given preoperatively. Next, trichotomy and antisepsis were performed with the aid of a shearing machine and sterile gauzes containing $2\%$ degermant iodine, which was followed by three steps of $70\%$ ethanol application in the surgical focus. All animals were then submitted to the surgical creation of bone defects bilaterally in the tibias, but only the animals of DR and AV groups received implants (scaffolds) as treatment. After surgery, anti-inflammatory meloxicam was administered subcutaneously at a dose of 2 mg/kg and, after 24 and 48 h, at a dose of 1 mg/kg. Finally, the animals were placed in individual boxes with free access to water and food and were monitored until anesthesia was completely over. Additionally, postoperative animals were monitored daily throughout the whole treatment period, with pain parameters being constantly evaluated. The animals were euthanized by drug overdose (intraperitoneal injection of ketamine 240 mg/kg and xylazine 24 mg/kg) 15 days after surgery. ## 2.8.3. Histological Procedures After sample collection, the left tibias were dehydrated with $70\%$ ethanol for three days. They were then dehydrated in absolute ethanol ($100\%$) for a further three days, diaphanized in toluene for one day and included in the methyl methacrylate resin (Merck acrylic resin). The obtained blocks were sanded and cut using a microtome (Leica Microsystems SP 1600, Nussloch, Germany). Five-micrometer-thick sections were perpendicularly obtained, considering the medial–lateral axis of the implants. Histological sections were stained with Goldner’s tri-chromium (Merck). ## 2.8.4. Histological Analysis The qualitative analysis of the slides was performed by means of the morphological description of bone defects, according to the following criteria: presence of newly formed bone tissue (primary and secondary bone), granulation tissue, presence of fibrosis and biomaterial. Analyses were performed blindly on the 10× objective. ## 2.8.5. Histomorphometric Analysis A microscope (Labophot 2ª, Nikon, Minato City, Tokyo) coupled to the OsteoMeasure software (OsteoMetrics, Atlanta, GA, USA) was used for the quantitative analyses. Measurements were performed in the fields located in the medial region of the bone defect, from the upper border until the bottom of the defect, using the 10× objective. The total region of interest (ROI) was 1.85 ± 0.38 mm2 (Figure 2B). The following histomorphometric parameters were obtained: bone volume as percentage of tissue volume (BV/TV%), osteoid volume as percentage of tissue volume (OV/TV%), number of osteoblasts per unit area of tissue analyzed (N.Ob/T.Ar mm2), osteoblastic surface as a percentage of bone surface (Ob. S/BS%) and percentage of fibrous tissue volume as a percentage of tissue volume (Fb. V/TV%), according to international standardized nomenclature [23]. A parameter was additionally included in order to analyze the biomaterial present in the ROI: biomaterial volume as a percentage of tissue volume (Bm. V/TV%) ($$n = 5$$). Active (mature) bone-forming osteoblasts were identified by their cylinder-like shape and their arrangement in rows over an area of osteoid tissue. ## 2.8.6. Biomechanical Test Biomechanical analysis was performed using the three-point bending test on the right tibia of animals of all groups. Biomechanical assays were performed on the Instron universal testing machine (model 4444, 825 University Ave Norwood, MA, 02062-2643, US) at room temperature. For the test, a load cell with a maximum capacity of 1 N and a preload of 5 N and a constant speed of 0.5 cm/min was used. Both tibia ends were supported by two metal supports, with the defect region facing downwards. The force was then perpendicularly applied to the longitudinal axis of the bone by a cylindrical rush until the moment of fracture. The force applied and the indentator displacement were monitored and recorded using the equipment’s own software. From the force–displacement curve, fracture energy (J) (ability to absorb energy to breakage), elastic deformation energy (J) (ability to absorb and return energy without apparent deformation) and maximum load (N) (maximum load that the material can support) were obtained [23]. ## 2.8.7. Statistical Analysis Initially, the variable distribution was tested using the Shapiro–Wilk’s normality test. For variables that exhibited normal distribution (BV/TV%; OV/TV%; N.Ob/T. Ar mm2; Ob. S/BS%; Fb. V/TV%; Bm. V/TV%; fracture energy (J); elastic deformation energy (J); maximum load (N)), comparisons among groups were carried out by analysis of variance (ANOVA), followed by Tukey post hoc. The Mann–Whitney test was used for variables not exhibiting normal distribution (characterization tests: pH and mass degradation). The statistical program used was GraphPad Prism version 7.0 and the adopted significance level was $5\%$ (p ≤ 0.05). ## 3.1.1. SEM The qualitative analysis of the surface morphology of scaffolds showed the presence of silica spicules and pores in both materials (scaffolds of Dragmacidon reticulatum and Amphimedon viridis marine sponges) (Figure 1). Dragmacidon reticulatum sponge scaffolds were structurally more porous than Amphimedon viridis sponge scaffolds. Additionally, it was observed that the scaffolds of the Dragmacidon reticulatum species show a greater degradation after incubation when compared to the Amphimedon viridis species (Figure 3). ## 3.1.2. FTIR The scaffolds manufactured from the two species of marine sponges studied (Dragmacidon reticulatum and Amphimedon viridis) exhibited the same functional groups: at 3460 cm−1, a broad peak consistent with the intermolecular OH bond; weak peaks at 2950 cm−1 and 2875 cm−1 for asymmetric and symmetrical -CH2- (OH-linked), respectively; weak signal between 800 cm−1 and 960 cm−1 of rotary motion -CH2-; presence of medium to strong signal between 1260 cm−1 and 1440 cm−1 being positive for primary alcohol; average signal at 770 cm−1 of the silicon–carbon bond; SiOH peaks at 3700 to 3200 cm−1, 1030 cm−1 and 890 cm−1; presence of signals at 1650 cm−1 and 1535 cm−1 consistent with amide I and amide II functions, respectively. However, from the seventh day of incubation, there was loss of the characteristic point of amide I, amide II and primary alcohol (CH2OH)—related to organic matter—only in Dragmacidon reticulatum species, as shown in Figure 4. ## 3.1.3. XRD XRD analysis of the samples revealed that the two species of marine sponges studied are composed of amorphous content, as shown in Figure S1. ## 3.1.4. EDS In the EDS analysis, the scaffolds manufactured from the marine sponge species Dragmacidon reticulatum and Amphimedon viridis showed the same chemical composition as shown in Table S1, and the three most proportionally present chemical elements were carbon, oxygen and silicon, which together represent more than $80\%$ of the sample. ## 3.1.5. pH and Mass Degradation The results of the pH measurements during the incubation period are shown in Figure 5A. The scaffolds of the Dragmacidon reticulatum species showed an initial drop in pH in the periods referring to the 1st and 3rd days of immersion in PBS and subsequent increase from the 14th day, reaching pH similar to the initial value (pH = 7.6) at day 21. The pH of the medium incubated with scaffolds from the species Amphimedon viridis did not show significant variation during the analysis period, remaining practically stable from day 1 to 21. A statistical difference was observed in the comparison between the two species, in the first ($$p \leq 0.0158$$), third ($p \leq 0.0001$) and seventh ($$p \leq 0.0037$$) days of incubation. Figure 5B shows the results of the degradation assays of the scaffolds’ mass after immersion in PBS at different periods. An initial loss of mass in both groups (day 1) was observed, being more pronounced in the species Dragmacidon reticulatum when compared to the species Amphimedon viridis. After the third day, the values remained stable. Statistical difference was verified between species in the first ($$p \leq 0.0003$$), third ($$p \leq 0.0286$$), seventh ($p \leq 0.0001$), fourteenth ($$p \leq 0.0002$$) and twenty-first ($$p \leq 0.0027$$) periods. ## 3.1.6. Porosity The results of the porosity tests (Figure 6) demonstrate an average of 84 ± $5\%$ porosity for Dragmacidon reticulatum scaffolds and 90 ± $2\%$ for Amphimedon viridis. No statistical differences were found between Dragmacidon reticulatum and Amphimedon viridis scaffolds. ## 3.2.1. Qualitative Histological Analysis An overview of representative histological sections for all the experimental groups is shown in Figure 7. For CG, bone formation was observed at the border of the entire defect, with osteoid areas around the newly formed bone. The DR, when compared to AV, presented new bone tissue points and a greater presence of osteoid tissue, mainly around the spicules of silica and newly formed bone tissue. In AV, a fibrous capsule was formed around the lesion area where the scaffold was implanted. Neoformed bone tissue was absent in this group and the areas of osteoid tissue were smaller, with only poorly isolated portions inside the defect. ## 3.2.2. Histomorphometric Analysis Figure 8 shows the mean and standard deviation (SD) for the quantitative histomorphometric variables: BV/TV (%), OV/TV (%), N.Ob/T. Ar (mm2), Ob. S/BS (%), Bm. V/TV (%) and Fb. V/TV (%). For the BV/TV parameter, it was verified that the bone volume that was formed 15 days after the surgical procedure was proportionally higher in the control group compared to the other two groups that included scaffold implants. On average, the percentage of bone volume in the analyzed area of the defect was 32.6 ± $8.5\%$ for CG, 0.05 ± $0.04\%$ for DR and $0.00\%$ for AV. Statistical differences were found between the groups: CG vs. DR ($p \leq 0.0001$) and CG vs. AV ($p \leq 0.0001$), in the ANOVA/Tukey test, as shown in Figure 8A. On the other hand, when evaluating the percentage of osteoid in the analyzed area of the defect (OV/TV%), it was observed that the formation of this tissue was significantly superior in the group with scaffold implantation of the marine sponge Dragmacidon reticulatum (DR; 8.3 ± $2.6\%$) in comparison to the control group (CG, 4.3 ± $1.9\%$) and Amphimedon viridis (AV, 0.7 ± $0.3\%$). A statistically significant difference was observed in the comparisons among all groups: CG vs. DR ($$p \leq 0.0042$$), CG vs. AV (0.0077), DR vs. AV ($p \leq 0.0001$) (Figure 8B). Additionally, in the evaluation of the parameter referring to the percentage of biomaterial in the analyzed tissue (Bm. V/TV%), a significant statistical difference was observed between the groups CG vs. DR and CG vs. AV, where the CG $0\%$, DR 0.03 ± $0.01\%$ and AV 0.04 ± $0.01\%$. Thus, there was no difference between the two types of scaffolds implanted (Figure 8C). The number of osteoblasts per unit area of tissue analyzed (N.Ob/T.Ar mm2) of 132.0 ± 65.3 mm2 for the CG, 56.7 ± 11.3 mm2 for the DR and 13.2 ± 5.0 mm2 for AV was observed. There were statistical differences between the CG vs. DR and CG vs. AV groups (Figure 8D). On the other hand, the osteoblastic surface as a percentage of the bone surface (Ob. S/BS%) was 8.4 ± $5.6\%$ for the CG, 17.7 ± $14.6\%$ for DR and $0.0\%$ for AV. A statistical difference was observed between the DR vs. AV () groups (Figure 8E). In the evaluation of parameter Fb. V/TV (%), regarding the percentage of fibrous tissue in the analyzed tissue, statistical differences were observed between the CG vs. AV ($$p \leq 0.0068$$) and DR vs. AV ($$p \leq 0.0022$$) groups, as fibrosis was only verified in AV (19.9 ± $17.1\%$) (Figure 8F). ## 3.2.3. Biomechanical Analysis In the evaluation of the fracture energy (J), the respective mean values of 0.04 ± 0.02 J, 0.03 ± 0.02 J and 0.04 ± 0.02 J were observed for CG, DR and AV. The evaluation of the variable elastic deformation energy (J) showed the mean values 0.02 ± 0.01 J, 0.02 ± 0.01 J and 0.03 ± 0.01 J for the CG, DR and AV groups, respectively. Finally, in the evaluation of the maximum load (N), an average value of 49.2 ± 5.6 N was observed for CG, 47.6 ± 9.8 N for DR and 46.7 ± 10.9 N for AV. No statistical differences were observed among groups ($p \leq 0.005$) for any of the parameters (Figure 9). ## 4. Discussion This study aimed to evaluate the physical-chemical properties of scaffolds manufactured from two species of marine sponges of the Demospongiae class and to investigate the in vivo biological response of these natural biomaterials once implanted in bone defects in rat tibia. The hypothesis was that, since different species could be physically and morphologically different, the osteogenic potential of these scaffolds would also be distinct. The main results showed that scaffolds of Dragmacidon reticulatum* presented better performance in bone repair when compared to scaffolds of the species Amphimedon viridis. Initially, SEM micrographs showed that the scaffold structures of both species are constituted by a porous material, with interconnected pores and presence of silica spicules, degrading after immersion in PBS. These characteristics are very important, since previous studies prove that the presence of interconnected pores and silica spicules are important characteristics in the scaffolds destined to favor the process of bone repair, as well as the gradual degradation of the scaffold allowing the replacement of the material by bone tissue [24,25]. Interestingly, scaffolds from both species exhibited a great porosity (84 ± $5\%$ for DR and 90 ± $2\%$ for AV), which would be adequate for their use as bone substitutes since the scientific literature establishes a minimum of $80\%$ for an ideal scaffold [26]. In fact, higher porosity is expected to be reflected as an increase in bone formation, as observed in several studies involving different biomaterials, used as raw material for scaffolds’ manufacture [27]. In the study of Nandi et al. [ 15], SEM analysis also showed that the Biemna fortis skeleton has a collagenous fibrous network with highly networked porosity in the size range of 10–220 µm. However, the fibrous material was burnt at 725 °C and the fired material was mixed with naphthalene to induce porosity. After naphthane removal, apparent porosity was determined to be about $52\%$, which is substantially lower than the porosity found for Dragmacidon reticulatum and Amphimedon viridis scaffolds used in the present study (84 ± $5\%$ for DR and 90 ± $2\%$ for AV). This can be explained not only by the species-related difference, but also by the manufacturing method of the scaffolds themselves. In the FTIR analysis, the scaffolds of both species had the same functional groups, with organic amide functions at 1650 cm−1 and 1535 cm−1, a primary alcohol at 2950 cm−1 and 2875 cm−1, inorganic silicon–carbon bonds at 1250 cm−1 and 770 cm−1 and silicon-hydroxyl at 3700 cm−1, 1030 cm−1 and 890 cm−1 [28]. It was observed that from the seventh day of incubation, for the Dragmacidon reticulatum species, there was a reduction in the points referring to the amide and primary alcohol groups, characteristic of oxidation of the organic matter, evidencing the degradation of the sample during the incubation time. This finding confirms our previous results of electron microscopy, which indicated a greater presence of pores and greater degradation in the scaffolds of this same species. For the species Amphimedon viridis the points remained stable during the incubation period evaluated. This difference between the species studied also suggests a better potential of the species Dragmacidon reticulatum when compared to the species Amphimedon viridis, since the study of Kido et al. [ 25] has shown that, in addition to porosity, proper degradation of the scaffold is essential for the bone repair process to occur. It is known that tissue formation depends on space to occur, and that the presence of a biomaterial may be a barrier to the growth of new tissue, especially if the implanted biomaterial does not have adequate porosity or a degradation rate compatible with the rate of bone formation. In the study of Nandi et al. [ 18], FTIR spectra revealed the presence of Si-O-Si groups at about 800 cm−1 and massive carbonate groups at about 1500 cm−1, which is a sign that the freeze-dried Biemna fortis material has a high organic content. The XRD revealed that the scaffolds of the two species of marine sponges studied are composed of amorphous organic content, which coincides with the findings of Nandi et al. [ 18], who also characterized the marine sponge (Biemna fortis) belonging to the same class of species of this study (class Demospongiae). In addition, Schröder et al. [ 29], when studying the structure, biochemical composition and formation mechanism of biosilica produced by living organisms (marine sponges, diatoms and higher plants), reported it to be amorphous silica without evidence of crystalline silica. Gabbai-Armelin et al. [ 12] also found the mostly amorphous nature of biosilica extracted from Dragmacidon reticulatum species, with only a few crystalline peaks being observed. Therefore, these studies agree with the amorphous nature of sponges and their components, and the implication of this finding for bone tissue engineering would be the greatest biodegradation of these natural biomaterials once implanted, considering that the crystalline arrangement would imply greater stability due to the structural configuration of their monomers [3]. This may be beneficial for the replacement of the implant by the natural tissue, although potentially promoting, on the other hand, a significant decrease in the mechanical properties of the biomaterial [3]. For the EDS analysis, the scaffolds of both species had the same chemical composition, the three main components being carbon, oxygen and silicon, and a lower percentage of aluminum, calcium, chlorine, iron, potassium, magnesium, sodium, phosphorus and sulfur. These findings are in line with those obtained in the Sandford [30] study, which carried out a physical-chemical analysis of the siliceous skeletons of six species of marine sponges of two groups (Demospongiae and Hexactinellida), which concluded that the average chemical composition of the spicules of both groups was $85\%$ silica (SiO2) and presented small amounts of the other elements mentioned earlier in this study. Additionally, Schröder et al. [ 29] reinforce that silica spicules, besides silicon and oxygen, present trace amounts of various other elements (mainly aluminum, calcium, chlorine, iron, potassium, sodium and sulfur), where approximately $75\%$ of the body mass of these animals is silica. Interestingly, marine organisms process approximately seven gigatons of silicon to make their silica skeletons, an interesting feature for regenerative medicine in view of the osteoinductive potential (i.e., ability to stimulate differentiation of precursor cells in functional osteoblasts) of this component [31]. For the analysis of pH and mass degradation, a more marked variation of the values was observed, in the sense of an acidification of the medium with the loss of the material, during the first week of immersion of the scaffolds in PBS, reaching stability in the subsequent periods. It is interesting to note that only the DR scaffolds showed the initial drop in pH in the periods referring to the 1st and 3rd days of immersion in PBS and following. This could be explained by the fact that the loss of the scaffolds’ mass after immersion in PBS was remarkably greater in DR according to the degradation assays, with the products of this lixiviation most likely being responsible for the pH alterations. Further, this acidification would be interesting in the context of bone healing since Hazehara-Kunitomo et al. [ 32], who were able to measure the pH in vivo during the healing of a bone fracture, showed that the pH decreased to 6.8 during the inflammatory period (initial 2 days) and that this short-term acidification could help stem cell differentiation towards bone-forming osteoblasts [33]. In the histological analysis of the present study, bone formation was observed around the border of the whole defect in the CG, and histomorphometry (parameter BV/TV%) revealed that the percentage of bone formed was higher in this group than in the other groups that used marine sponge grafts (DR and AV). This can be explained by the adoption of a non-critical bone defect model that allows spontaneous bone repair with complete closure of the defect. In addition, other studies have shown that, initially, the presence of the biomaterial at the lesion site constitutes a barrier to bone growth, since the biomaterial needs to be degraded for the subsequent occurrence of bone tissue formation [34,35,36,37,38,39]. In the study of Nandi et al. [ 18], scaffolds prepared from Biemna fortis sponges (belonging to the same class of sponges of the present study—Demospongiae) were implanted into non-critical femoral bone defects in rabbits and tracked for up to 90 days. No quantifications were performed, but radiological, histological and scanning electron microscopy have demonstrated that bare sponge scaffolds (without any growth factor loading) promoted better osseous tissue formation, with invasion of this new bone across the porous scaffold’s matrix, in comparison to bone defects without any implant, which mostly showed soft tissue formation, with the defect gap still present even after 3 months. In addition to mineralized bone, the formation of osteoid tissue was also evaluated in this study. It was present mostly underlying the newly formed bone tissue and around the sponge silica spicules, being much more evident in the scaffolds created from Dragmacidon reticulatum species. In fact, the analysis of the histomorphometric parameter OV/TV (%) showed a higher osteoid percentage in DR. Therefore, we can indicate more advanced bone repair in the CG due to the greater presence of mineralized bone tissue, followed by DR, with a more important presence of bone matrix that is not yet mineralized and, finally, AV, in which the neoformation of osseous and osteoid bone tissue was lower than the others. Nandi et al. [ 18] also assessed newly formed osteoid tissue in implanted Biemna fortis scaffolds through fluorochrome labeling—oxytetracycline. They showed a greater presence of newly formed bone in sponge scaffolds in comparison to control defects, which were moderately filled with osteoid tissue and where consolidation was under process. It is important to note that the evidence discussed above is consistent with the cellular parameters analysis. Several in vitro studies have shown that the inorganic part of the sponge skeleton (biosilica) induces bone neoformation by attracting osteoprogenitor cells and stimulating their differentiation in osteoblasts [3,26,31,34]. In the present study, the number of osteoblasts per unit area of tissue analyzed (N.Ob/T.Ar/mm2) was higher in the CG compared to the other groups, which is compatible with the presence of a greater amount of neoformed bone tissue. Additionally, analyzing the osteoblastic surface (Ob. S/BS%), which refers to the percentage of bone surface covered by active osteoblasts, a statistical difference was found between the two groups with sponge implants, DR (17.7 ± $14.6\%$) and AV ($0.0\%$), being superior in the Dragmacidon reticulatum species, which again indicates superior osteogenic properties in the scaffolds manufactured from this species. In the study of Nandi et al. [ 18], despite the absence of quantitative parameters, well-formed osteons inside sponge-filled defects exhibited osteoblastic and osteoclastic activities, whereas osteoclasts were prominently observed at the cortical region of non-filled control defects. The authors state that sponge scaffolds most likely serve as a bioactive stimulant for cell maturation, in agreement with other studies that have previously show that, at least in in vitro situations, osteoblast attachment, proliferation, migration and differentiation can be stimulated by marine sponge components [10,11,38]. However, in the present study, in addition to the lower bone and osteoid formation and the lower number of osteoblasts in AV, a fibrous capsule formation was observed around the implant area only in this group, which may indicate an attempt by the organism to isolate the biomaterial, i.e., a rejection of Amphimedon viridis scaffolds [39]. Urabayashi [19] has demonstrated, through the in vitro chemical analysis of the crude sponge extract of this species, a cytotoxic effect in human cell lines from retinal pigment epithelium and breast carcinoma, as well as a hemolytic action in rat cells, which may explain the results of the present study, since severe local and systemic inflammatory and cytotoxic responses caused by the implants may result in delayed or non-healing of the bone [25]. Therefore, despite previous research demonstrating the osteogenic potential of marine sponges in terms of both bone formation and cell stimulation, the current study shows that the benefits may also depend on the species of sponge studied and that the integration of the material with the original tissue can be significantly inferior or even harmful depending on the species, as shown here. As the last histomorphometric parameter, the percentage of biomaterial inside the defect (Bm. V/TV%) was not different between DR and AV, although the characterization assays indicated a more important degradation in scaffolds manufactured from the Dragmacidon reticulatum species. Therefore, studies with longer experimental periods are necessary in order to allow a longer time for the biodegradation of the implanted materials and for the concomitant process of bone consolidation. In the study of Nandi et al. [ 18], evidence of sponge scaffold degradation was found radiologically, mostly from day 60 when the scaffold altered its shape from cylindrical to oval, with the edges of the filling material reducing its size, a sign that newly formed bone tissue was beginning to replace the sponge material. Moreover, the authors found that the enrichment of the scaffolds with the IGF-1 and BMP-2 growth factors promoted bone formation, with the presence of neoformed bone tissue and active osteoblastic cells throughout the defect region, as well as increased biodegradation of the implanted biomaterial. Finally, for all the parameters evaluated in the biomechanical test, no statistical differences were found among the groups, although the CG had a higher bone formation than the others. This may be due to the presence of the biomaterial at the site of the defect in the two other groups, which could imply a greater resistance to fractures. In addition, interestingly, it may indicate a good integration of the implanted materials with the pre-existing living tissue, a hypothesis also reported in the study by Granito et al. [ 3] involving bone defects in tibiae of rats filled or not with bioactive synthetic materials. Together, the characterization analyses and the in vivo study with the scaffolds manufactured from the species Dragmacidon reticulatum and Amphimedon viridis confirmed our hypothesis that different species, because they exhibit different chemical and structural properties, also have different osteogenic properties. Here, the Dragmacidon reticulatum species proved to be a more interesting option as a scaffold in bone tissue engineering and, therefore, the so-called good osteogenic potential is species-dependent, as demonstrated herein in a pioneering way. In a pioneering way, this study compared two abundant species on the Brazilian coast and performed an extensive quantitative analysis of the bone repair process after in vivo implantation of these natural biomaterials. However, there are some limitations that still need to be addressed herein, such as the use of a non-critical bone defect model, which was chosen to allow biomechanical evaluations on a weight-bearing bone, and the short treatment period after scaffold implantion. Therefore, the critical-sized calvarial defect could be the next step of this study, together with longer follow-up periods and the inclusion of other experimental groups for the evaluation of scaffolds manufactured from marine sponges belonging to other species and even other families. Actually, a larger number of different species and families could have their potential evaluated if in silico methods had been employed. Faster outcomes and reduced costs are some of the benefits that computer simulations could bring for the prediction of the implant failure values, as in the study of Putra et al. [ 40]. Finally, another limitation of this study is inherent to the use of a natural biomaterial itself. Structural and morphological variations are expected among specimens collected from the environment. Subsequently, biomaterial availability would be an additional challenge, especially considering the clinical application as the final purpose of this study. Both obstacles could be at least partially overcome with the production of sponge biomass by in situ aquaculture. Mariculture could possibly satisfy the biomaterial demand without compromising natural sponge beds, constituting, therefore, a sustainable approach for biomaterial production [41]. In addition, the biological performance of scaffolds should also be assessed in other experimental animal models, as well as including the evaluation of bone repair in clinical situations in which it is compromised, such as in diabetes, in order to validate the use of these natural biomaterials as promising therapeutic alternatives. ## 5. Conclusions It can be concluded that scaffolds manufactured from the marine sponge species Dragmacidon reticulatum, when compared to Amphimedon viridis species, were more effective as bone substitutes, since their structure was more porous and biodegradable, with a compatible increase in osteoid tissue formation and presence of osteoblastic cells, despite the absence of fibrous tissue formation in the studied period. Thus, sponges of this species may constitute a promising alternative source of biomaterials for use in bone tissue engineering. Further research is still needed for a better understanding of these marine sponge scaffolds. A critical bone defect model in rats should be the next step of this study, as well as other experimental models to evaluate the bone repair when it is compromised, such as an osteoporosis model. 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--- title: The Emerging Importance of Cirsimaritin in Type 2 Diabetes Treatment authors: - Abdelrahim Alqudah - Rabaa Y. Athamneh - Esam Qnais - Omar Gammoh - Muna Oqal - Rawan AbuDalo - Hanan Abu Alshaikh - Nabil AL-Hashimi - Mohammad Alqudah journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10059674 doi: 10.3390/ijms24065749 license: CC BY 4.0 --- # The Emerging Importance of Cirsimaritin in Type 2 Diabetes Treatment ## Abstract Cirsimaritin is a dimethoxy flavon that has different biological activities such as antiproliferative, antimicrobial, and antioxidant activities. This study aims to investigate the anti-diabetic effects of cirsimaritin in a high-fat diet and streptozotocin-(HFD/STZ)-induced rat model of type 2 diabetes mellitus (T2D). Rats were fed HFD, followed by a single low dose of STZ (40 mg/kg). HFD/STZ diabetic rats were treated orally with cirsimaritin (50 mg/kg) or metformin (200 mg/kg) for 10 days before terminating the experiment and collecting plasma, soleus muscle, adipose tissue, and liver for further downstream analysis. Cirsimaritin reduced the elevated levels of serum glucose in diabetic rats compared to the vehicle control group ($p \leq 0.001$). Cirsimaritin abrogated the increase in serum insulin in the treated diabetic group compared to the vehicle control rats ($p \leq 0.01$). The homeostasis model assessment of insulin resistance (HOMA-IR) was decreased in the diabetic rats treated with cirsimaritin compared to the vehicle controls. The skeletal muscle and adipose tissue protein contents of GLUT4 ($p \leq 0.01$ and $p \leq 0.05$, respectively) and pAMPK-α1 ($p \leq 0.05$) were upregulated following treatment with cirsimaritin. Cirsimaritin was able to upregulate GLUT2 and AMPK protein expression in the liver ($p \leq 0.01$, <0.05, respectively). LDL, triglyceride, and cholesterol were reduced in diabetic rats treated with cirsimaritin compared to the vehicle controls ($p \leq 0.001$). Cirsimaritin reduced MDA, and IL-6 levels ($p \leq 0.001$), increased GSH levels ($p \leq 0.001$), and reduced GSSG levels ($p \leq 0.001$) in diabetic rats compared to the vehicle control. Cirsimaritin could represent a promising therapeutic agent to treat T2D. ## 1. Introduction Diabetes is a multifactorial metabolic syndrome characterized by abnormalities in carbohydrates, fat, and protein metabolisms, which lead to hyperglycemia [1]. The most common type of diabetes mellitus is type 2 diabetes (T2D) which is characterized by impaired glucose utilization by skeletal muscle, liver, and adipose tissue resulting from glucose intolerance due to insulin resistance accompanied by insulin deficiency as a result of islet beta-cells injury [2]. Genetic disposition, environmental factors, diet, physical inactivity, and obesity are risk factors that contribute significantly to the progression of insulin resistance and T2D development [3,4,5]. Inflammation and oxidative stress are important biological factors in the pathogenesis of T2D development and its complications [6]. It is not well understood how inflammation contributes to the pathogenesis of T2D; however, it has been observed that pro-inflammatory cytokines such as interleukin-6 (IL-6) are synthesized by adipose tissue, which increases as fat body mass increases, which leads to the development of insulin resistance [7]. Moreover, a large body of evidence has proven that oxidative stress plays a key role in the etiology of T2D [1,8]. The chronic exposure of cells and tissue to hyperglycemia results in the non-enzymatic glycation of proteins, which leads to the production of reactive oxygen species which may cause DNA damage [9]. Furthermore, oxidative stress was found to inhibit the promoter activity and mRNA expression of the insulin gene in pancreatic islet cells, leading to a decrease in insulin gene expression [10]. In addition, oxidative stress is also involved in inducing insulin resistance, thus increasing the incidence of T2D development [11]. Taken together, T2D etiology and its complications are strongly linked to inflammation and oxidative stress. Glucose disposal is mediated by the effect of insulin on its receptors on the cell surfaces of insulin-sensitive tissues, particularly skeletal muscle, adipose tissues, and the liver [12,13]. Once the insulin receptor is activated, glucose transport over the plasma membrane occurs through different members of the glucose transporter (GLUT) family, such as GLUT 4, which is expressed in skeletal muscle and adipose tissue, and GLUT2, which is expressed in the liver [14]. Insulin resistance develops when insulin signaling is impaired; however, insulin resistance is compensated initially by increasing insulin secretion, but eventually, insulin release from pancreatic β-cells becomes insufficient for maintaining normal blood glucose concentration, which leads to T2D [15]. Several studies have shown that the activation of AMP-activated protein kinase (AMPK) stimulates the translocation of GLUT4 and GLUT2 to the cell surface, which increases glucose uptake through an insulin-independent pathway [16,17,18]. Thus, enhancing insulin sensitivity could be achieved through the activation of the AMPK signaling pathway. Cirsimaritin is a dimethoxy flavone (Figure 1) that is found in different plants such as Lithocarpus dealbatus, Artemisia Judaica, Microtea debilis, Cirsium japonicum, and Ocimum sanctum [19]. Previous reports show that cirsimaritin has different biological activities such as antimicrobial, antispasmodic, and antiproliferative activities [20,21]. Moreover, extracts from rosemary leaves containing cirsimaritin showed high antioxidant activity [22,23]. Additionally, cirsimaritin also showed anti-inflammatory activity by inhibiting nitric oxide production and the inducible expression of nitric oxide synthase, in addition to blocking different cytokines, including IL-6 and tumor necrosis factor-α (TNF-α) [24]. Furthermore, several studies showed that cirsimaritin has an anti-diabetic effect. One study demonstrated that extracts from T. polium containing cirsimaritin had an insulinotropic effect on a rat insulinoma cell line, INS1E cells. Moreover, the extracts containing cirsimaritin were able to reduce glucose levels significantly in hyperglycemic rats [25]. Another study performed with visual screening revealed that cirsimaritin has a good affinity for blocking dipeptidyl peptidase 4 (DDP-4), which will increase insulin secretion [26]. Additionally, cirsimaritin showed an ability to enhance glucose uptake rate in TNF-α-treated mouse FL83B hepatocytes, suggesting that cirsimaritin might improve insulin resistance in the liver [27]. These results show that cirsimaritin has an antidiabetic effect, but more research is needed to determine the applicability of cirsimaritin in diabetes mellitus treatment. Therefore, this study aims to assess the effect of cirsimaritin on AMPK-GLUT4 and AMPK-GLUT2 pathways in a high-fat diet (HFD)/STZ-induced rat model. ## 2.1. The Hypoglycemic Effect of Cirsimaritin Serum glucose was significantly higher in the vehicle control diabetic group compared to the non-diabetic group (Figure 2A, $$n = 6$$, $p \leq 0.001$). Treatment with cirsimaritin significantly reduced serum glucose concentrations compared to the vehicle controls in the presence of T2D (Figure 2A, $$n = 6$$, $p \leq 0.001$). Similarly, the mean glucose concentration in the diabetic group was significantly reduced with metformin treatment compared to the vehicle controls (Figure 2A, $$n = 6$$, $p \leq 0.01$). However, glucose concentration was significantly reduced with metformin treatment compared to cirsimaritin treatment (Figure 2A, $$n = 6$$, $p \leq 0.05$). Insulin levels were significantly increased in the vehicle control diabetic group compared to the non-diabetic group (Figure 2B, $$n = 6$$, $p \leq 0.001$); however, treating diabetic rats with cirsimaritin significantly reduced the insulin compared to the vehicle control group (Figure 2B, $$n = 6$$, $p \leq 0.01$). Like cirsimaritin, treating diabetic rats with metformin significantly reduced insulin levels compared to the vehicle control group (Figure 2B, $$n = 6$$, $p \leq 0.001$). However, metformin significantly reduced insulin levels compared to the cirsimaritin-treated group (Figure 2B, $$n = 6$$, $p \leq 0.05$). To determine the effects of cirsimaritin on insulin resistance, HOMA-IR was measured. The presence of T2D was confirmed via HOMA-IR, which significantly increased in the vehicle control diabetic group compared to the non-diabetic group (Figure 2C, $$n = 6$$, $p \leq 0.001$). Interestingly, cirsimaritin was able to restore HOMA-IR in the diabetic group, which was comparable to the non-diabetic group. The same effect on HOMA-IR was observed when diabetic rats were treated with metformin. HOMA-IR was significantly reduced with metformin treatment compared to cirsimaritin treatment (Figure 2C, $$n = 6$$, $p \leq 0.01$). Moreover, the blood glucose level during IPGTT was significantly lower in the cirsimaritin and metformin groups compared to the vehicle control (Figure 3, $$n = 6$$, $p \leq 0.001$). To determine the mechanism by which cirsimaritin improves blood glucose and insulin resistance, GLUT4 and phosphorylated AMPK (pAMPK-α1) protein expression were measured in skeletal muscle tissue. GLUT4 protein expression was significantly downregulated in the presence of T2D (Figure 4A, $$n = 6$$, $p \leq 0.001$); however, treating diabetic rats with cirsimaritin significantly upregulated GLUT4 expression compared to the vehicle control diabetic group (Figure 4A, $$n = 6$$, $p \leq 0.01$). Metformin was also able to upregulate GLUT4 expression compared to the vehicle control diabetic group (Figure 4A, $$n = 6$$, $p \leq 0.001$). Metformin treatment was able to upregulate GLUT4 expression significantly higher compared to cirsimaritin treatment (Figure 4A, $$n = 6$$, $p \leq 0.05$). Similarly, pAMPK-α1 expression was significantly downregulated as a result of T2D (Figure 4B, $$n = 6$$, $p \leq 0.001$), which was abrogated with cirsimaritin or metformin (Figure 4B, $$n = 6$$, $p \leq 0.05$, < 0.001, respectively). pAMPK-α1 was significantly higher with metformin treatment compared to cirsimaritin treatment (Figure 4B, $$n = 6$$, $p \leq 0.05$). Moreover, GLUT4 and pAMPK-α1 protein expression in adipose tissue were measured. GLUT4 protein expression was significantly downregulated in the presence of T2D (Figure 5A, $$n = 6$$, $p \leq 0.001$); whereas the administration of cirsimaritin significantly upregulated GLUT4 expression compared to the vehicle controls (Figure 5A, $$n = 6$$, $p \leq 0.05$). Metformin was also able to upregulate GLUT4 expression compared to the vehicle control diabetic group (Figure 5A, $$n = 6$$, $p \leq 0.01$). GLUT4 expression in adipose tissue was significantly upregulated with the metformin treatment compared to the cirsimaritin treatment (Figure 5A, $$n = 6$$, $p \leq 0.001$). Similarly, pAMPK-α1 expression was significantly downregulated as a result of T2D (Figure 5B, $$n = 6$$, $p \leq 0.001$), and treating diabetic rats with either cirsimaritin or metformin significantly upregulated pAMPK-α1 expression compared to the vehicle control diabetic group (Figure 5B, $$n = 6$$, $p \leq 0.05$, < 0.001, respectively). No difference was observed in pAMPK-α1 expression between the cirsimaritin and metformin groups. To further elucidate the mechanism by which cirsimaritin improves insulin sensitivity and reduces glucose levels, hepatic glucose transporter 2 (GLUT2) and pAMPK-α1 protein expression were measured. GLUT2 protein expression was significantly downregulated in the presence of T2D (Figure 6A, $$n = 6$$, $p \leq 0.001$), whereas cirsimaritin significantly upregulated GLUT2 expression compared to the vehicle control diabetic group (Figure 6A, $$n = 6$$, $p \leq 0.01$). Metformin was also able to upregulate GLUT2 expression compared to the vehicle controls (Figure 6A, $$n = 6$$, $p \leq 0.001$). Similarly, pAMPK-α1 expression was significantly downregulated as a result of T2D (Figure 6B, $$n = 6$$, $p \leq 0.001$), and treating diabetic rats with either cirsimaritin or metformin significantly upregulated pAMPK-α1 expression compared to the vehicle controls (Figure 6B, $$n = 6$$, $p \leq 0.05$, < 0.001, respectively). No difference was observed in GLUT2 and pAMPK-α1 expression between the cirsimaritin and metformin groups. ## 2.2. The Effect of Cirsimaritin on the Lipid Profile As depicted in Figure 7, dyslipidemia was present in diabetic rats. LDL (Figure 7A, $$n = 6$$, $p \leq 0.001$), total cholesterol (Figure 7B, $$n = 6$$, $p \leq 0.05$), and triglycerides (TGs; Figure 7C, $$n = 6$$, $p \leq 0.001$) were significantly higher in the vehicle control diabetic group, compared to the non-diabetic group. Treating diabetic rats with cirsimaritin significantly reduced serum LDL (Figure 7A, $$n = 6$$, $p \leq 0.001$), total cholesterol (Figure 7B, $$n = 6$$, $p \leq 0.001$), and TGs (Figure 7C, $$n = 6$$, $p \leq 0.001$) systemic concentration, compared to the vehicle control diabetic group. Similarly, metformin was able to significantly reduce LDL (Figure 7A, $$n = 6$$, $p \leq 0.001$), cholesterol (Figure 7B, $$n = 6$$, $p \leq 0.01$), and TGs (Figure 7C, $$n = 6$$, $p \leq 0.001$) levels in diabetic rats, compared to the vehicle controls. Interestingly, LDL and TG systemic concentrations were significantly lower in the cirsimaritin group compared to the metformin group (Figure 7A,C, $$n = 6$$, $p \leq 0.05$, <0.001, respectively). ## 2.3. The Effects of Cirsimaritin on GSH, GSSG, MDA, and IL-6 Serum GSH expression was significantly reduced in vehicle-control diabetic rats, compared to non-diabetic rats (Figure 8A, $$n = 6$$, $p \leq 0.001$); however, treating diabetic rats with either cirsimaritin or metformin demonstrated a significant increase in GSH compared to the vehicle control diabetic group (Figure 8A, $$n = 6$$, $p \leq 0.001$, < 0.01, respectively). Moreover, serum GSSG was significantly increased in vehicle-control diabetic rats, compared to non-diabetic rats (Figure 8B, $$n = 6$$, $p \leq 0.001$); however, cirsimaritin and metformin were able to reduce GSSG levels in diabetic rats, compared to the vehicle control (Figure 8B, $$n = 6$$, $p \leq 0.001$). On the other hand, serum MDA (Figure 8C, $$n = 6$$, $p \leq 0.001$) and IL-6 (Figure 8D, $$n = 6$$, $p \leq 0.001$) concentrations were significantly increased in the presence of T2D. Interestingly, cirsimaritin showed an ability to reduce serum MDA and IL-6 levels significantly in diabetic rats, in comparison to the vehicle control group (Figure 8C,D, $$n = 6$$, $p \leq 0.001$). The same effect was observed when diabetic rats were treated with metformin (Figure 8C,D, $$n = 6$$, $p \leq 0.001$). The IL-6 systemic level was significantly lower in the metformin group compared to the cirsimaritin group (Figure 8D, $$n = 6$$, $p \leq 0.05$). ## 3. Discussion Food value is linked to nutritional contents and digestibility, as well as the presence or absence of toxic ingredients [28]. Indeed, the bionutrients that foods offer are essential for life, but also, foods possess other bioactive compounds that are important for health promotion and disease prevention [29]. The consumption of a healthy diet is strongly correlated with a reduction in the risk of several chronic diseases such as cancer, diabetes, cardiovascular diseases and atherosclerosis, neurodegenerative disorders, and inflammation, as well as their complications [30]. These therapeutic properties of food gave rise to medicinal drugs made from certain kinds of food, particularly plants. Numerous medicinal plants have been largely used in the treatment of several diseases, such as cardiovascular diseases [31], cancer [32], diabetes [33], inflammation [34], depression [35,36], and pain management [37]. Therefore, the aim of this study was to assess, for the first time, the antidiabetic efficacy of flavonoid compound, cirsimaritin. The findings of our study revealed that cirsimaritin significantly reduced glucose, insulin, and HOMA-IR in an HFD/STZ-induced diabetic rat model. In addition, cirsimaritin improved insulin resistance by upregulating GLUT4 and AMPK expression in soleus muscle and adipose tissue. Furthermore, cirsimaritin upregulated GLUT2 and AMPK expression in the liver. Moreover, cirsimaritin exerts antioxidant and anti-inflammatory effects. Hyperglycemia and insulin resistance are hallmarks of T2D, and they are implicated in T2D complications such as nephropathy, neuropathy, and retinopathy [38]. Our findings demonstrated that cirsimaritin reduced glucose, insulin, and HOMA-IR. This finding is consistent with the previous literature [39] where cirsimaritin enhanced the glucose uptake rate in diabetic mice hepatocytes. Skeletal muscles and adipose tissue consume a high portion of blood glucose. Several chronic conditions and mechanisms underlie insulin resistance (IR) in these tissues [40,41]. Many studies have linked insulin resistance to impaired GLUT4-mediated glucose uptake [42,43,44]. According to animal models, the reduction in GLUT4 expression was $50\%$ in the skeletal muscles of the hypertriglyceridemia insulin resistance mouse model [43]. Moreover, a $70\%$ reduction in GLUT4 protein expression in the adipose-specific genetic knockout mouse model was associated with insulin resistance [45]. The activation of the AMPK-GLUT4 pathway enhances insulin sensitivity, and it has been shown to improve glucose control in T2D [46,47]. Moreover, GLUT2 is responsible for glucose uptake in the liver, and it is required for the physiological control of glucose-sensitive genes. The inactivation of GLUT2 in the liver leads to impaired glucose-stimulated insulin secretion [13,48]. The findings of the present study demonstrated that cirsimaritin-improved insulin resistance is mediated by the activation of the AMPK-GLUT4 pathway in the skeletal and adipose tissues, and by the activation of the AMPK-GLUT2 in the liver. Dyslipidemia is tightly associated with T2D, and it is a major risk factor leading to T2D-associated complications [49]. Several studies have linked dyslipidemia to microvascular complications associated with T2D, such as diabetic retinopathy, nephropathy, and neuropathy [50]. The present study showed that cirsimaritin improved the lipid profile in high-fat diabetic rats. Interestingly, cirsimaritin-treated animals demonstrated lower LDL-C and TG levels after 10 days of treatment, compared to the vehicle control group. To our knowledge, this is the first study that shows the lipid-lowering effects of pure cirsimaritin. Previous studies using extracted flavonoids, including cirsimaritin, failed to demonstrate similar findings [25]. Although the exact mechanism is yet to be unrevealed, however, these findings highlights could pave the way to further investigate cirsimaritin in T2D and dyslipidemia. Oxidative stress is implicated in the early stages of T2D [51]. Oxidative stress is referred to as an overproduction of reactive oxygen species (ROS), and a reduction in the rate of antioxidant defense mechanisms such as GSH (a non-enzymatic antioxidant) [52]. Additionally, ROS induces the release of MDA, a highly reactive compound that interacts with proteins and nucleic acids, and that causes damage to various tissues and cells [53]. MDA has been used as a biomarker of lipid peroxidation and as an indication of free radical damage in the blood [54]. Our findings indicate that similar to metformin, cirsimaritin was able to decrease elevated MDA levels in the high-fat T2D rat model. Furthermore, cirsimaritin was able to restore the GSH/GSSG balance that was disturbed in the high-fat T2D rat model. Taken together, these findings suggest a powerful antioxidant effect of cirsimaritin. Numerous studies have pointed out the antioxidant effects of cirsimaritin in different assays, as revised in [55]. In those studies, cirsimaritin extracted from Teucrium ramosissimum showed an excellent antioxidant activity, using ABTS assay with a Teac value of 2.04 μM. In addition, cirsimaritin extracted from Cirsium japonicum inhibited DPPH free radicals, with a percentage of between $80\%$ to $100\%$ at a dose of 100 μg/mL. Moreover, cirsimaritin extracted from Combretum fragrans showed potent DPPH radicals scavenging activity. It is postulated that as a flavonoid, cirsimaritin has a broad range of biological actions that could be related to the direct scavenging of ROS [55]. Subclinical chronic inflammation has been implicated in the development and progression of insulin resistance, T2D, and its complications [56]. In particular, the increased levels of the multifunctional cytokine, IL-6, have been linked to the pathogenesis of T2D. Our findings demonstrate that cirsimaritin reduced the circulating IL-6 levels with respect to the untreated group. Previous evidence has shown that cirsimaritin inhibited the production of several cytokines such as IL-6 and TNF-α via transcriptional factor-mediated mechanisms that downregulate gene expression [24]. The limitations of this study include the following aspects: (i) cirsimaritin was administered for a short period of time, and (ii) GLUT4 expression was assessed using immunoblotting that was reflective of its total amount; however, immunohistochemistry may be a better technique for assessing its activity and translocation to the cell membrane. Nevertheless, our findings in this study indicate the important role of cirsimaritin in improving the typical features of T2D. ## 4.1. The Induction of T2D and Experimental Design Animal experimental procedures were approved by the animal ethics committee at the Hashemite University (IRB number: $\frac{14}{4}$/$\frac{2021}{2022}$, 14 April 2022), and were in accordance with the guidelines of the US National Institutes of Health on the use and care of laboratory animals, and with the Animal Research: Reporting of in Vivo Experiments (ARRIVE) guidelines (https://arriveguid elines.org, accessed on 2 May 2022). Thirty-week-old male adult Sprague-Dawley rats (average weight 264 ± 3.5) were maintained under standard conditions, including 12 h light/dark cycles and a 22 ± 2° temperature [57]. T2D was induced by feeding the experimental rats HFD ($60\%$ fat) for 3 weeks, followed by one intraperitoneal injection of streptozotocin (STZ; 40 mg/kg) [58]. The average weight after diabetes induction for the mice fed with HFD was 328.4 ± 4.4. One week after STZ injection, plasma glucose was measured, and rats with a plasma glucose concentration over 200 mg/dL were considered to have developed T2D, and were selected for the subsequent experiments. Rats were randomly divided into four groups ($$n = 6$$ each), as follows: (i) normal non-diabetic control group (non-diabetic, ND) receiving normal diet, (ii) vehicle control (VC) diabetic group treated with dimethyl sulfoxide (DMSO, Panreac Quimica SA, Barcelona, Spain) only, (iii) diabetic group treated with 50 mg/kg cirsimaritin (Sigma-Aldrich, Dorset, UK), and (iv) diabetic group treated with 200 mg/kg metformin (MeRCK, Darmstadt, Germany); the dose of metformin was in line with a previous study that used 200 mg/kg metformin for the treatment of diabetic rats [59]. The dose of cirsimaritin used in this study was based on a previous report showing that the doses between 50–200 mg/kg did not produce any noticeable side effects; thus, the lowest dose (50 mg/kg) was chosen for this study [60]. All treatments were given orally once per day. After 10 days of treatment, rats were euthanized as per local standard operating procedures, using carbon dioxide before blood and skeletal muscle (soleus muscle), adipose tissue, and liver were collected for ex-vivo analysis. ## 4.2.1. Measurements of Serum Glucose, Insulin, and Lipids in Rat Serum Serum glucose and insulin were determined using a commercial kits glucose assay kit (Mybiosource, San Diego, CA, USA), and a rat insulin ELISA kit (Mybiosource, San Diego, CA, USA), respectively, as per the manufacturer’s instructions. Triglyceride (TG, triglyceride assay kit), low-density lipoproteins (LDL, LDL assay kit), and cholesterol (Total Cholesterol assay kit) were also measured using commercially available kits (MybioSource, San Diego, CA, USA) according to the manufacturer’s instructions. ## 4.2.2. Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) This model represents the interaction between fasting plasma insulin and fasting plasma glucose, which is a useful tool for determining insulin resistance. In the current study, we used the following formula to compute HOMA-IR [61]:HOMA-IR=(Fasting glucose (mg/dL)×Fasting insulin (μIU/mL)/405 ## 4.2.3. Intraperitoneal Glucose Tolerance Test Rats were given an intraperitoneal injection of glucose (0.5 g/kg) after being fasted for 18 h. Using a glucometer, blood glucose levels were measured from the tail vein at 0, 30, 60, and 120 min (Accu-Check Performa, Roche Diagnostics). ## 4.2.4. Measurement of Serum Glutathione (GSH), Oxidized Glutathione (GSSG), Malondialdehyde (MDA), and IL-6 Serum Concentrations Reduced glutathione (GSH, GSH assay kit), oxidized glutathione (GSSG, GSSG assay kit), and IL-6 (IL-6 ELISA kit) levels were measured in the serum using commercially available kits (Mybiosource, San Diego, CA, USA). Plasma MDA level was determined by using a commercially available thiobarbituric acid (TBA) Assay Kit (Mybiosource, San Diego, CA, USA) according to the manufacturer’s instructions. ## 4.3. Western Blotting Skeletal muscle tissues (soleus muscle), adipose tissue, and liver were homogenized in radioimmunoprecipitation (RIPA)-lysis buffer, containing a protease inhibitor cocktail (Santa Cruz Biotechnology, USA), using a tissue homogenizer. Homogenates were centrifuged at 13,000 rpm for 20 min at 4 °C, and the supernatant was collected. Total protein was quantified using a bicinchoninic acid assay (Bioquochem, Austurias, Spain). Equal amounts of protein were separated using a sodium dodecyl sulfate–polyacrylamide gel, then transferred onto a nitrocellulose membrane (Thermo Fisher Scientific, Carlsbad, CA, USA). The membrane was blocked for 1 h at room temperature using $3\%$ bovine serum albumin (BSA), before incubating overnight with either pAMPK-α1 (Abcam, Cambridge, UK), GLUT2, or GLUT4 (Mybiosource, San Diego, CA, USA) primary antibodies (1:1000 dilution). The membrane was washed three time with a washing buffer (Tween-20/Tris-buffered saline) before incubating it with the goat-anti-rabbit secondary antibody (Mybiosource, San Diego, CA, USA, 1:5000 dilution) for 1 h at room temperature. Following incubation, the membrane was washed three times before submerging it into the ECL substrate (ThermoScientific, Carlsbad, CA, USA) for one minute, followed by imaging with the chemiLITE Chemiluminescence Imaging System (cleaverscientific, Rugby, UK). To ensure equal protein gel loading, β-actin was used as a housekeeping gene (Mybiosource, San Diego, CA, USA, 1:10,000 dilution). The intensities of the bands were measured using Image J software, and adjusted to β-actin. ## 4.4. Statistical Analysis All analyzed parameters were tested for the normality of the data using the Kolmogorov-Smirnov test. Data are represented as mean ± SEM. Differences between groups were calculated using a one-way analysis of variance (ANOVA) or two-way ANOVA, followed by a Tukey post hoc test using PGraphPad Prism software version (9.3.1). The significance value of difference was considered when the p-value was less than 0.05. ## 5. Conclusions Our findings in this study revealed that cirsimaritin might be a very useful agent for the treatment of T2D due to its ability to reduce insulin resistance, and its activation of the GLUT4-AMPK and GLUT2-AMPK pathways in skeletal muscle, adipose tissue, and liver. 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--- title: Associations between Parents’ Body Weight/Shape Comments and Disordered Eating Amongst Adolescents over Time—A Longitudinal Study authors: - Lucy M. Dahill - Phillipa Hay - Natalie M. V. Morrison - Stephen Touyz - Deborah Mitchison - Kay Bussey - Haider Mannan journal: Nutrients year: 2023 pmcid: PMC10059676 doi: 10.3390/nu15061419 license: CC BY 4.0 --- # Associations between Parents’ Body Weight/Shape Comments and Disordered Eating Amongst Adolescents over Time—A Longitudinal Study ## Abstract Parents are key influencers of adolescents’ attitudes on weight, shape, and eating, and make more positive than negative comments, with negative comments most impactful. This study examined prospective unique associations of parental positive and negative comments in a community sample of adolescents with paediatric psychosocial quality of life (PED-QoL), Eating Disorder Weight/Shape Cognitions (EDEQ-WS), BMI percentile, and Psychological Distress (K10) scales. Data were from 2056 adolescents from the EveryBODY study cohort. Multiple regressions were conducted for the impacts of parental positive and negative comments on four dependent variables at one year after controlling for their stage of adolescence (early, middle, late). Multiple imputation and bootstrapping were used for handling missing data and violations of normality. Results indicated that positive maternal comments on eating were associated with increased EDCs and better quality of life at one year. Paternal positive weight shape comments were associated with a decrease in psychological distress, but positive eating comments saw a decrease in quality of life. Findings highlight the nuances of parental comments and how these are perceived and interpreted, and could alert health care workers and family practitioners who have weight, shape, and eating conversations to be aware of the potential influence of their communication. ## 1. Introduction Parents have been found to be key influences during childhood setting standards for behaviour that continue into adult life [1,2,3]. Whilst parental influence can diminish in middle adolescence [4,5,6], it has been found to have an enduring influence on physical and mental health outcomes with adolescents, particularly for eating disorder cognitions (EDCs), setting longer term foundations of communication and behaviours relating to eating, weight, and shape [5,7,8]. Adolescence is also a key life-stage for the onset of eating disorder risk factors, including body dissatisfaction, low self-esteem, and weight shape concerns [9,10]. Furthermore, it is a life-stage associated with biological, psychological, and emotional change, with complex challenges involving maturation and social emotional development that can impact quality of life and influence the onset of eating disorders [11,12]. Parental comments and weight-talk between parents and adolescents requires further exploration for their health-related and psychosocial outcomes [13]. Parents’ concern for their child’s wellbeing and challenges with their growing independence can result in conflictual communication and miscommunications around weight, shape, and eating [5,8,14,15]. The influence of communication can be direct, such as verbal and targeted (e.g., parent to child), or indirect, such as non-verbal (e.g., eye movements) or when speaking about someone else (e.g., “they look great with a little less weight on their hips”) [13,16,17]. Mothers have been found to comment more frequently, particularly to daughters about their bodies and their eating [5,7,18,19,20,21,22], and maternal delivered content has been more attuned to thin-idealisation, while alternations, such as muscle-ideation, are more likely to be reported in father–son communications [19,23]. ## 1.1. Positive and Negative Comments Research has investigated the prevalence of positive and negative eating and weight/shape-related comments [5,7], the importance and associations of these comments with mothers and fathers [5,20,24], associations between weight talk exposure, psychological distress, and unhealthy eating and/or weight control behaviours [13,15,17], maternal encouragement to diet with boys and girls [25], and the perception and nuances of such communication [5]. In previous research, we [7], examined the prevalence of positive and negative comments to sons and daughters in this adolescent sample. Adolescents reported frequent positive comments more commonly from mothers ($78\%$) than fathers ($51\%$) on weight and shape and on eating (mothers $70\%$ versus fathers $53\%$). Furthermore, daughters, compared to sons, reported more positive (mothers $85\%$ versus fathers $71\%$) and negative (mothers $40\%$ versus fathers $33\%$) comments on weight/shape, and more negative eating comments from their mothers (mothers $66\%$ versus fathers $57\%$). Fathers were reported to comment more negatively on sons’ weight/shape than on daughters (mothers $25\%$ versus fathers $32\%$). Further, for all perceived parental negative weight shape comments and maternal negative eating comments, adolescent stage and biological sex were significantly associated with EDCs and psychological distress [24]. Negative comments can take many forms. For example, a well-recognised form is teasing. Such negative comments may be presented as a form of humour and present a form of humour at a developmental stage of life where markers for understanding such complex forms of communication have not yet developed [26]. Of note, when considering the content of the comments, fathers have been found to be more likely to “tease” both their sons and daughters compared to mothers [27,28]. Furthermore, studies have shown that differing “modes of influence”, such as parents, peers, and other influences can act in concert or counteractively [23] with a cumulation of comments (positive or negative) from parents being associated with more negative outcomes and a lower quality of life than from either parent alone [29]. Longitudinal studies have also considered the long-term effects of negative comments, such as those delivered through weight-based teasing [30,31], the pertinence of age [6], associations of parental comments with EDCs including psychological distress [32], parental teasing and eating disorder risk factors [28], parents as influencing factors [6,33], and considered if the gender of the source of the weight teasing (parents or peers) influenced the effect of appearance and weight esteem [34]. Findings suggest this form of negative communication in families during adolescence leads to a greater risk of unhealthy weight control behaviours (UWCBs) in early adulthood [28,31,32,34], and effects have been shown to vary by gender. Puhl [2017] [31] found women to be more adversely affected by negative maternal comments 15 years later, and although Valois et al., [ 2019] [34] did not find any difference in effect dependent on the gender of the parent performing the appearance teasing, they did suggest that the teaser’s gender should be considered in weight-teasing prevention strategies. A systematic review of population-based studies which included two longitudinal studies considered psychosocial quality of life to be associated with disordered eating behaviour in adolescents [35]. Whilst there are multiple factors that influence quality of life in adolescents, it is imperative that we further consider the long-term effects of negative comments which could adversely influence adolescent psychological and physical health. To our knowledge, there is no other paper that examines comprehensively this topic across both genders in both parents and children, i.e., positive and negative comments about weight shape and eating from both mothers and fathers during adolescence. ## 1.2. Research Question This study aims to explore the associations of mothers’ and fathers’ positive and negative comments on sons and daughters’ psychosocial quality of life, eating disorder cognitions (EDCs), BMI percentile, and psychological distress over time, thereby extending our cross-sectional research [24]. Thus, we will provide more empirical evidence and understanding to inform parents and clinicians working with families in this area around appropriate communication about weight and shape concern. Based on the above previous research, we hypothesised the following:i.Perceived positive parental comments on shape/weight would be significantly associated at the one-year follow-up with lower psychological distress, BMI percentile and eating disorder cognitions for daughters;ii. All perceived negative parental comments on shape/weight or eating would be significantly associated at the one-year follow-up with greater psychological distress, BMI percentile, and EDCs for both sons and daughters;iii. Perceived positive eating comments from mothers and fathers would be significantly associated at the one-year follow-up with reduced psychological distress, BMI percentile, and EDCs.iv. Associations of all perceived comments from mothers and fathers and associations with quality of life are exploratory, but we anticipated that perceived negative comments may be associated with a lower quality of life and that perceived positive comments with a better quality of life at one-year follow-up. ## 2. Methods Data for this study were drawn from a subset of the EveryBODY study, a longitudinal investigation of body image concerns and eating disorders among Australian adolescents. At the time of data collection there had been three data collection points (waves). Included participants captured in both wave 2 (T1) and the one-year follow-up at wave 3 (T2) were from four private and four public schools in New South Wales. The sub-sample in this study were those participants who had indicated they had a mother or father in their life and who completed questions related to parental comments at T1 of the survey. The final sample for T1 ($$n = 2204$$) consisted of $46\%$ boys, and less than $1\%$ reported a non-binary gender or did not respond to this item; participants were aged between 11 and 18 years, with a mean age 14.84 years (SE = 0.58). A variable ‘stage’ was created to indicate early, middle, and late adolescence. Early was classified as grades 7 and 8 ($40.9\%$) which represented the first two years of high school in Australia, usually around 12–14 years; grades 9 and 10 ($42.3\%$) indicated middle adolescence, and grades 11 and 12 ($16.8\%$) were used to indicate late adolescence. These ‘stages’ have been used in previous research [7,36,37]. There were 2056 respondents at the one-year follow-up (T2), and the attrition in the sample was $7\%$ and consisted of $46\%$ boys; less than $1\%$ reported a non-binary gender or did not respond to this item. ## 2.1.1. Specific Parental Comment Questions Maternal and paternal comments on weight/shape and on eating were measured using purpose-designed items by the authoring team and described in previous research [7]. Participants answered an initial question, “Is your mother in your life?” ( or mother figure). Responses were binary (yes/no). Those who gave an affirmative response were asked a series of two questions regarding the frequency of maternal comments on (i) weight and shape and (ii) eating. Responses were rated on a 5-point scale: “never” [1], “rarely” [2], “sometimes” [3], “often” [4], and “all of the time” [5]. The same questions were asked regarding comments from fathers or father figures. There was a maximum of eight questions in total, because if they answered “no” to either the mother or father question, that reduced the number to below eight. These were only collected at T1. The full list of questions is in Supplementary File S1. ## 2.1.2. Eating Disorder Cognitions Twelve items from the Weight Concern and Shape Concern subscales of the Eating Disorder Examination Questionnaire (EDEQ-WS) were used to assess eating disorder psychopathology, referred to as eating disorder cognitions (EDCs) in this study. Participants are asked questions that related to weight/shape concerns over the past 4 weeks (28 days), such as “how dissatisfied have you been with your shape?” Responses were measured with a Likert scale (0 = Not at all through to 6 = Markedly). A mean of the 12 items was used to compute a global score, ranging from 0 to 6, with higher scores conferring greater dissatisfaction. The combined EDEQ-WS score has been used to define overall body image disturbance in the diagnosis of anorexia nervosa [38]. McDonald’s omega estimates for the reliability for the combined weight and shape concern subscale in the present study was 0.96 and 0.94 for girls and boys, respectively [36]. A higher EDEQ-WS score means a higher risk of EDCs. These were collected at T1 and T2. ## 2.1.3. Psychological Distress The K-10 Psychological Distress Scale [39] was used to ask about the frequency of anxiety and depressive symptoms in the past 4 weeks. Participants completed 10 items on how often they experienced specific feelings (e.g., “Tired out for no good reason”) in the last 28 days (4 weeks) on a 5-point Likert scale (1 = None of the time through to 5 = All of the time). Scores range from 10 to 50, with higher scores indicating higher levels of distress. This scale has demonstrated high clinical utility in predicting clinically significant levels of distress in adolescent populations [39,40,41]. McDonald’s omega for the K-10 in the present study was 0.94 and 0.93 for girls and boys, respectively [36]. These were collected at T1 and T2. ## 2.1.4. Quality of Life Quality of life was measured using the psychosocial functioning subscale of the Paediatric Quality of Life scale (PED-QoL) [42,43]. Participants were asked to rate on a 5-point Likert scale (1 = Never through to 5 = Always) how true a series of statements were of them in the past 4 weeks. Scores were combined, reversed, and transformed on a 0–100 scale, with a higher score indicated higher functioning i.e., a better psychosocial quality of life. The psychosocial functioning subscale is a combination of the emotional and social functioning scales. In previous studies with adolescents, the psychosocial functioning subscale has shown good reliability and validity [43]. McDonald’s omega for the PED-QoL in the present study was 0.90 and 0.91 for girls and boys, respectively [36]. These were collected at T1 and T2. ## 2.1.5. Body Mass Index Percentile (BMI%ile) Height and weight were derived from self-report. Body mass index (BMI) (Kg/m2) was calculated and then converted to sex- and age-adjusted BMI percentiles (BMI%iles). These were derived according to the Centers for Disease Control and Prevention guidelines [2017]. These were collected at T1 and T2. ## 2.2. Data Analysis Intention to treat analyses were used. Multiple regressions were conducted for four dependent variables, namely psychosocial PED-QoL, K10, EDEQ-WS subscale, and BMI percentile at Time 2 (wave 3) on parental positive and negative comments at Time 1 (wave 2), after controlling for gender and baseline adolescent stage. Multiple imputation and bootstrapping were used for handling missing data and violations of normality, respectively. For fitting multiple linear regressions, all the dependent variables at T2, namely K10, BMI%ile, EDEQ-WS combined, and psychosocial PED-QoL were found to be not normally distributed, thus, violating the assumption. Consequently, 1000 bootstrap samples were generated to correctly determine the standard errors and $95\%$ confidence intervals for the regression coefficients in multiple linear regression. To account for missing data, the multiple imputation method of 10 imputations was used. The multivariate normal imputation (MVNI) with MCMC algorithm was used for this purpose. All analyses were performed using SAS 9.4 (SAS Institute, Cary, NC, USA, 2013). Sex and baseline stage were not both controlled for throughout the analyses. With the imputed data for T2, the sample size used for multiple linear regression of the relevant T2 outcome was 2056 after controlling for the baseline stage only. However, if we had also controlled for sex, the sample size used for multiple linear regression of the T2 outcome would have been only 1639, hence, losing statistical power. The results presented did not control for sex to avoid the loss of statistical power when the dependent variables were psychological distress and BMI percentile as sensitivity analysis showed that sex was not a confounder for the relationship between comment variables and these outcomes. However, when the dependent variables were psychosocial PED-QoL and EDEQ-WS combined, sex was found to be a confounder and, thus, was appropriately controlled for in the analysis alongside baseline stage. ## 3. Results The prevalence of comments has been previously reported [7] and further illustrated in the introduction for this paper. ## 3.1. Psychological Distress After controlling for baseline stage, both more frequent positive (RE: 0.99; $95\%$ CI: 0.67–1.30; $p \leq 0.000$) and more frequent negative (RE: 0.45; $95\%$ CI: 0.012–0.90 $p \leq 0.05$) maternal weight shape comments at baseline were significantly related to higher psychological distress one year later. On the other hand, greater frequency of positive paternal weight/shape comments were found to be associated with lower psychological distress after one year (RE: −0.41; $95\%$ CI: −0.80–−0.00 $p \leq 0.05$). These results are reported in Table 1. When exploring just daughters (see Table 2), only more frequent maternal positive weight/shape comments were associated with greater psychological distress (RE: 0.55; $95\%$ CI: 0.04–1.05 $p \leq 0.05$). All other effects on psychological distress for daughters were non-significant. When exploring just sons, none of the comment variables were significant (see Table 3). ## 3.2. BMI Percentile There were no significant comment variables when exploring parental comments to all adolescents (see Table 1); however, when exploring gendered dyads, mothers’ positive comments to sons on eating were significantly related to higher BMI at one-year follow-up (RE: 2.49; $95\%$ CI: 0.57–4.41 $p \leq 0.05$) (see Table 3). For daughters, there were no significant comment variables (see Table 2). ## 3.3. Eating Disorder Cognitions (EDCs, EDEQ-WS) Paternal negative eating (RE: 0.02; $95\%$ CI: 0.02–0.12 $p \leq 0.05$) and maternal positive eating (RE: 0.06; $95\%$ CI: 0.01–0.11 $p \leq 0.01$) comments were found to be significantly associated with greater increases in EDCs at 1 year (see Table 1). When looking for gendered effects, only paternal negative eating comments to daughters was significant and associated with greater increases in EDCs (RE: 0.15; $95\%$ CI: 0.01–0.28 $p \leq 0.05$). This is reported in Table 2. ## 3.4. Paediatric Quality of Life (PED-QoL) All maternal comments, except for maternal negative eating comments, were significant for better quality of life (see Table 1). All paternal comments were significant with mixed associations. Whilst paternal positive weight/shape (RE: 2.0; $95\%$ CI: 1.37–2.62 $p \leq 0.000$) and negative eating (RE: 0.74; $95\%$ CI: 0.05–1.44 $p \leq 0.05$) comments were significant for better quality of life, paternal negative weight/shape (RE: −0.92; $95\%$ CI: −1.72–−0.07 $p \leq 0.05$) and positive eating (RE: −1.56; $95\%$ CI: −2.12–−0.95 $p \leq 0.01$) comments were associated with a decrease in quality of life. For gendered effects, only maternal positive eating comments to sons were significant and associated with an increased quality of life (RE: 1.87; $95\%$ CI: 0.28–3.45 $p \leq 0.05$). This finding is reported in Table 3. ## 4. Discussion This study followed a diverse range of adolescents to examine longitudinal associations between perceived positive and negative parental comments on weight, shape, and eating and quality of life, BMI percentile, psychological distress, and EDCs one year later. It considered if this relationship was influenced by stage of adolescence and sex. Findings illustrated the complexity of how words are perceived by adolescents and the adverse outcomes that are associated with both positive and negative comments on weight shape and eating from both mothers and fathers to sons and daughters. Hypothesis 1 was partially supported, as only fathers’ positive comments on weight and shape were significantly associated at one-year follow-up with lower psychological distress. Hypothesis 2 was also partially supported, as only maternal negative weight and shape comments were significantly associated with greater psychological distress. Hypothesis 3 was not supported, as perceived positive eating comments from mothers or fathers were not significantly associated at one-year with reduced psychological distress. Although hypothesis 4, that associations of all comments from mothers and fathers and associations with PED-QoL were exploratory, the anticipated correlation between positive comments being associated with higher score for PED-QoL were not consistently supported with fathers’ positive eating and negative weight/shape comments, which were found to be associated with a decrease in quality of life. The complex nature of what contributes to quality of life suggests that our results warrant further investigation. ## 4.1. Maternal Comments The present study found that more frequent comments from mothers about weight/shape and eating was a significantly predictive factor of EDCs and psychological distress, and that gendered effects were more pronounced with daughters [5,8,20,29]. However, this was not the case for quality of life, where mothers’ communications appeared to become protective and associated with increased quality of life. This could suggest that mothers are potentially more attuned and willing to have those conversations, which is confirmed by prevalence data on maternal comments [5,19,20,22], and, therefore, such comments can create an environment which add to a positive quality of life, even if the comments are not always perceived as positive. However, there are many other contributing factors, such as parental involvement in the home and other family or community influences, which could have contributed to our findings. The statistically significant association between wave 1 and wave 2 EDEQ-WS, K-10, psychosocial PED-QoL, and BMI percentile in all regressions suggests they naturally have an influence on later measures of emotional and psychological wellbeing, and may also be a mediating risk factor for these associations later in life, which could be explored in subsequent research. Of note, maternal positive eating comments to sons were associated with an increase in BMI which could contribute to the fear of talking positively to sons about their eating out of concern that it will encourage them to eat more. This is an area that could be further explored in subsequent mixed-method research exploring parental concerns about the consequences of healthy eating conversations [5,13]. ## 4.2. Paternal Comments In this and other studies, fathers’ comments had an anticipated association, with positive comments on weight and shape being significantly associated with lower psychological distress and EDCs at one-year for daughters [5,19,23]. However, positive comments did not have the same significance. Of note, positive paternal eating comments were not protective of PED-QoL, with or without controlling for baseline stage. Whilst research is sparse, fathers have been found to be more likely to tease or to use humour and sarcasm at a time where their adolescents do not yet have the cognitive ability to understand such complex forms of communication, which could, therefore, encourage literal and detrimental interpretation [23,26,28,44]. Their comments, although less prevalent than mothers, can have significant associations with EDCs and psychological distress [13,27,45]. The findings ask us to explore whether one parents’ comments are more influential, or if the differing modes of influence are acting in concert, leading to the cumulation of comments providing fertile soil for more sensitivity to comments from one parent or another [5,20,23,29,33]. This could extend to the other influences on an adolescents’ physical and psychological wellbeing, peers, siblings, the media, what is said around them, and how their parents talk about their own weight, shape and eating [3,15,17,28,33,34]. ## 4.3. Psychosocial Quality of Life Psychosocial quality of life in adolescence has been explored as influencing the onset of eating disorders [11], yet the paucity of research specific to mothers and fathers’ perceived positive and negative weight, shape, and eating comments to adolescents and associations with psychosocial quality of life offers an opportunity to consider the nuance of gendered and didactic communication in families, the gender of the parent having more of these conversations, and how much value we place on those conversations, as called for in a recent systematic review [13]. Our psychosocial quality of life findings highlight the complexity of parental communication and the nuanced perception of positive and negative comments within the context of other influences in adolescents’ lives. These counter-intuitive results may be interpreted to illustrate that there is no clear rule to share with parents and health care professionals about the valence of words to use when talking to adolescents about weight, shape, and eating, as there are often complex contributing factors to how words are perceived and interpreted that could be making assumptions about intention. They may also reflect a willingness by young people to see value even in questions that make them feel ‘uncomfortable’ or are perceived as ‘negative comments’, or it is possible that adolescents’ quality of life is reflected by parental involvement in their lives and that the frequency of parental comments is a “proxy” variable for parental attention more broadly. However, these findings must be interpreted with caution, as quality of life is associated with many other aspects of people’s lives. It is possible that this is a misleading finding and would need to be replicated. Taken together, these longitudinal results imply that there is no clear rule for whether positive or negative eating or weight/shape comments from mothers or fathers increase the risk of EDCs, BMI, psychological distress, or poor quality of life. Whilst it is salient for parents to be more aware of how they communicate within the family structure and the influence their comments have and how they are perceived, perception is not necessarily indicative of intention. Investigating causation reduces the discussion about eating disorders and parental–adolescent communication to the potential to blame parents. However, there are many contributing factors apart from parents that influence the way that comments are heard and influence quality of life, such as relationship with food, eating, weight, shape and psychological wellbeing, meaning that exclusively, parental blame may not be justified. Thus, an ideal study would look at bidirectional influences between parental commenting and disordered eating and would explore underlying intentions in comments. One of the greatest strengths of this study includes the longitudinal design and the way in which the findings here provide an extension to our previous cross-sectional study [24]. The included cohort consisted of a mix of age and stage, which offers insight into the changing relationships between parents and adolescents as they transition through school into young adult life, and the questions were specifically designed to explore perceived weight, shape, and eating comments from mothers and fathers, from the perspective of sons and daughters. This allowed us to explore the nuances of gendered effects. However, limitations include the fact that we did not ask about recency in our survey questions or the type of family the young person belonged to, such as non-traditional families including mother/father-only households, blended families, two mothers/fathers or living with, or only living with, grandparents, etc. Furthermore, we relied on self-report, which could give rise to recall bias. Using quality of life as a measure does not account for other potential influences in adolescents’ lives that might influence our interpretation of the data. However, the psychosocial functioning subscale has shown good reliability and validity in previous studies with adolescents [43] and resulted in a valuable discussion on the perceived valence of parent comments to adolescents which adds to the existing literature [35]. A further limitation was the wide age range studied. This could be addressed in future studies by following similar age adolescents over a period of time to ensure that the adolescents’ maturity and other influencing factors particular to stages of development can be explored. Whilst the initial recruitment was a representative sample, by waves 2 and 3, there was incomplete data, which is, however, not unusual for a longitudinal study. The consequent intention to treat analysis means that the findings are not affected by attrition or loss of statistical power. ## 4.4. Public Health Implications These findings suggest that although we cannot determine other influencing factors, the way adolescents perceive what their mothers and fathers say about weight, shape, and eating has influence over them, and that perceived positive comments do not necessarily result in better outcomes than perceived negative comments. The negative associations with these comments tend to follow similar patterns through adolescence into adult life, with sex and age playing a mediating role in the severity of those outcomes. Therefore, rather than focus on blame, it is important for health care workers, practitioners working with families, and parents themselves to be aware of the intention behind their comments and the potential influence of their communication. ## 5. Conclusions and Recommendations The present study found that maternal and paternal comments were perceived differently by their adolescent sons and daughters. This research illustrates the complex nature of communication around weight, shape, and eating in a family environment during a key developmental period. Further studies are needed that consider the make-up of non-traditional families and consider how younger people in early adolescence interpret what is perceived as a positive or negative comment. 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